Documentation: ACS 2008 -- 2012 (5-Year Estimates)
you are here: choose a survey survey document chapter
Publisher: U.S. Census Bureau
Document: ACS 2012-5yr Summary File: Technical Documentation
citation:
Social Explorer; U.S. Census Bureau; American Community Survey 2008-2012 Summary File: Technical Documentation.
Chapter Contents
2008-2012 Subject Definitions
Housing Variables
Population Variables
American Community Survey/Puerto Rico Community Survey
ACS 2012-5yr Summary File: Technical Documentation
Appendix A: Supplemental Documentation
Code List
Ancestry Code List
Code Write-In
001-099 WESTERN EUROPE (EXCEPT SPAIN)
001 ALSATIAN
002 ANDORRAN
003 AUSTRIAN
004 TIROL
005 BASQUE
006 FRENCH BASQUE
007 SPANISH BASQUE
008 BELGIAN
009 FLEMISH
010 WALLOON
011 BRITISH
012 BRITISH ISLES
013 CHANNEL ISLANDER
014 GIBRALTAR
015 CORNISH
016 CORSICAN
017 CYPRIOT
018 GREEK CYPRIOTE
019 TURKISH CYPRIOTE
020 DANISH
021 DUTCH
022 ENGLISH
023 FAROE ISLANDER
024 FINNISH
025 KARELIAN
026 FRENCH
027 LORRAINE
028 BRETON
029 FRISIAN
030 FRIULIAN
031 LADIN
032 GERMAN
033 BAVARIA
034 BERLIN
035 HAMBURG
036 HANNOVER
037 HESSIAN
038 LUBECKER
039 POMERANIAN
040 PRUSSIAN
041 SAXON
042 SUDETENLANDER
043 WESTPHALIAN
044 EAST GERMAN
045 WEST GERMAN
046 GREEK
047 CRETAN
048 CYCLADES
049 ICELANDER
050 IRISH
051 ITALIAN
052 TRIESTE
053 ABRUZZI
054 APULIAN
055 BASILICATA
056 CALABRIAN
057 AMALFIN
058 EMILIA ROMAGNA
059 ROME
060 LIGURIAN
061 LOMBARDIAN
062 MARCHE
063 MOLISE
064 NEAPOLITAN
065 PIEDMONTESE
066 PUGLIA
067 SARDINIAN
068 SICILIAN
069 TUSCANY
070 TRENTINO
071 UMBRIAN
072 VALLE DAOST
073 VENETIAN
074 SANMARINO
075 LAPP
076 LIECHTENSTEINER
077 LUXEMBURGER
078 MALTESE
079 MANX
080 MONEGASQUE
081 NORTH IRISH
082 NORWEGIAN
083 OCCITAN
084 PORTUGUESE
085 AZORES ISLANDER
086 MADEIRA ISLANDER
087 SCOTCH IRISH
088 SCOTTISH
089 SWEDISH
090 ALAND ISLANDER
091 SWISS
092 SUISSE
093 SWITZER
094 IRISH SCOTCH
095 ROMANSCH
096 SUISSE ROMANE
097 WELSH
098 SCANDINAVIAN
099 CELTIC
 
100-180 EASTERN EUROPE AND SOVIET UNION
100 ALBANIAN
101 AZERBAIJANI
102 BELORUSSIAN
103 BULGARIAN
104 CARPATHO RUSYN
105 CARPATHIAN
106 RUSYN
107 RUTHENIAN
108 COSSACK
109 CROATIAN
110 NOT USED
111 CZECH
112 BOHEMIAN
113 MORAVIAN
114 CZECHOSLOVAKIAN
115 ESTONIAN
116 LIVONIAN
117 FINNOUGRIAN
118 MORDOVIAN
119 VOYTAK
120 GRUZIIA
121 NOT USED
122 GERMAN FROM RUSSIA
123 VOLGA
124 ROM
125 HUNGARIAN
126 MAGYAR
127 KALMYK
128 LATVIAN
129 LITHUANIAN
130 MACEDONIAN
131 MONTENEGRIN
132 NORTH CAUCASIAN
133 NORTH CAUCASIAN TURKIC
134-139 NOT USED
140 OSSETIAN
141 NOT USED
142 POLISH
143 KASHUBIAN
144 ROMANIAN
145 BESSARABIAN
146 MOLDAVIAN
147 WALLACHIAN
148 RUSSIAN
149 NOT USED
150 MUSCOVITE
151 NOT USED
152 SERBIAN
153 SLOVAK
154 SLOVENE
155 SORBIAN/WEND
156 SOVIET TURKIC
157 BASHKIR
158 CHUVASH
159 GAGAUZ
160 MESKNETIAN
161 TUVINIAN
162 NOT USED
163 YAKUT
164 SOVIET UNION
165 TATAR
166 NOT USED
167 SOVIET CENTRAL ASIA
168 TURKESTANI
169 UZBEG
170 GEORGIA CIS
171 UKRAINIAN
172 LEMKO
173 BIOKO
174 HUSEL
175 WINDISH
176 YUGOSLAVIAN
177 HERZEGOVINIAN
178 SLAVIC
179 SLAVONIAN
180 TAJIK
 
181-199 EUROPE, N.E.C.
181 CENTRAL EUROPEAN
182 NOT USED
183 NORTHERN EUROPEAN
184 NOT USED
185 SOUTHERN EUROPEAN
186 NOT USED
187 WESTERN EUROPEAN
188-189 NOT USED
190 EASTERN EUROPEAN
191 BUKOVINA
192 NOT USED
193 SILESIAN
194 GERMANIC
195 EUROPEAN
196 GALICIAN
197-199 NOT USED
 
200-299 HISPANIC CATEGORIES (INCLUDING SPAIN)
200 SPANIARD
201 ANDALUSIAN
202 ASTURIAN
203 CASTILLIAN
204 CATALONIAN
205 BALEARIC ISLANDER
206 GALLEGO
207 VALENCIAN
208 CANARY ISLANDER
209 NOT USED
210 MEXICAN
211 MEXICAN AMERICAN
212 MEXICANO
213 CHICANO
214 LARAZA
215 MEXICAN AMERICAN INDIAN
216-217 NOT USED
218 MEXICAN STATE
219 MEXICAN INDIAN
220 NOT USED
221 COSTA RICAN
222 GUATEMALAN
223 HONDURAN
224 NICARAGUAN
225 PANAMANIAN
226 SALVADORAN
227 CENTRAL AMERICAN
228 NOT USED
229 CANAL ZONE
230 NOT USED
231 ARGENTINEAN
232 BOLIVIAN
233 CHILEAN
234 COLOMBIAN
235 ECUADORIAN
236 PARAGUAYAN
237 PERUVIAN
238 URUGUAYAN
239 VENEZUELAN
240-247 NOT USED
248 CRIOLLO
249 SOUTH AMERICAN
250 LATIN AMERICAN
251 LATIN
252 LATINO
253-260 NOT USED
261 PUERTO RICAN
262-270 NOT USED
271 CUBAN
272-274 NOT USED
275 DOMINICAN
276-289 NOT USED
290 HISPANIC
291 SPANISH
292 CALIFORNIO
293 TEJANO
294 NUEVO MEXICANO
295 SPANISH AMERICAN
296-299 NOT USED
 
300-359 WEST INDIES (EXCEPT HISPANIC)
300 BAHAMIAN
301 BARBADIAN
302 BELIZEAN
303 BERMUDAN
304 CAYMAN ISLANDER
305-307 NOT USED
308 JAMAICAN
309 NOT USED
310 DUTCH WEST INDIES
311 ARUBA ISLANDER
312 ST MAARTEN ISLANDER
313 NOT USED
314 TRINIDADIAN TOBAGONIAN
315 TRINIDADIAN
316 TOBAGONIAN
317 U S VIRGIN ISLANDER
318 ST CROIX ISLANDER
319 ST JOHN ISLANDER
320 ST THOMAS ISLANDER
321 BRITISH VIRGIN ISLANDER
322 BRITISH WEST INDIES
323 TURKS AND CAICOS ISLANDER
324 ANGUILLA ISLANDER
325 ANTIGUA AND BARBUDA
326 MONTSERRAT ISLANDER
327 KITTS/NEVIS ISLANDER
328 DOMINICA ISLANDER
329 GRENADIAN
330 VINCENT GRENADINE ISLANDER
331 ST LUCIA ISLANDER
332 FRENCH WEST INDIES
333 GUADELOUPE ISLANDER
334 CAYENNE
335 WEST INDIAN
336 HAITIAN
337-359 NOT USED
 
360-399 CENTRAL AND SOUTH AMERICA (EXCEPT HISPANIC)
360 BRAZILIAN
361-364 NOT USED
365 SAN ANDRES
366-369 NOT USED
370 GUYANESE
371-374 NOT USED
375 PROVIDENCIA
376-379 NOT USED
380 SURINAM
381-399 NOT USED
 
400-499 NORTH AFRICA AND SOUTH WEST ASIA
400 ALGERIAN
401 NOT USED
402 EGYPTIAN
403 NOT USED
404 LIBYAN
405 NOT USED
406 MOROCCAN
407 IFNI
408 TUNISIAN
409-410 NOT USED
411 NORTH AFRICAN
412 ALHUCEMAS
413 BERBER
414 RIO DE ORO
415 BAHRAINI
416 IRANIAN
417 IRAQI
418 NOT USED
419 ISRAELI
420 NOT USED
421 JORDANIAN
422 TRANSJORDAN
423 KUWAITI
424 NOT USED
425 LEBANESE
426 NOT USED
427 SAUDI ARABIAN
428 NOT USED
429 SYRIAN
430 NOT USED
431 ARMENIAN
432-433 NOT USED
434 TURKISH
435 YEMENI
436 OMANI
437 MUSCAT
438 TRUCIAL STATES
439 QATAR
440 NOT USED
441 BEDOUIN
442 KURDISH
443 NOT USED
444 KURIA MURIA ISLANDER
445-464 NOT USED
465 PALESTINIAN
466 GAZA STRIP
467 WEST BANK
468-469 NOT USED
470 SOUTH YEMEN
471 ADEN
472-479 NOT USED
480 UNITED ARAB EMIRATES
481 NOT USED
483 ASSYRIAN
484 CHALDEAN
485 SYRIAC
486-489 NOT USED
490 MIDEAST
491-494 NOT USED
495 ARAB
496 ARABIC
497-499 NOT USED
 
500-599 SUBSAHARAN AFRICA
500 ANGOLAN
501 NOT USED
502 BENIN
503 NOT USED
504 BOTSWANA
505 NOT USED
506 BURUNDIAN
507 NOT USED
508 CAMEROON
509 NOT USED
510 CAPE VERDEAN
511 NOT USED
512 CENTRAL AFRICAN REPUBLIC
513 CHADIAN
514 NOT USED
515 CONGOLESE
516 CONGO BRAZZAVILLE
517-518 NOT USED
519 DJIBOUTI
520 EQUATORIAL GUINEA
521 CORSICO ISLANDER
522 ETHIOPIAN
523 ERITREAN
524 NOT USED
525 GABONESE
526 NOT USED
527 GAMBIAN
528 NOT USED
529 GHANAIAN
530 GUINEAN
531 GUINEA BISSAU
532 IVORY COAST
533 NOT USED
534 KENYAN
535-537 NOT USED
538 LESOTHO
539-540 NOT USED
541 LIBERIAN
542 NOT USED
543 MADAGASCAN
544 NOT USED
545 MALAWIAN
546 MALIAN
547 MAURITANIAN
548 NOT USED
549 MOZAMBICAN
550 NAMIBIAN
551 NIGER
552 NOT USED
553 NIGERIAN
554 FULANI
555 HAUSA
556 IBO
557 TIV
558 YORUBA
559-560 NOT USED
561 RWANDAN
562-563 NOT USED
564 SENEGALESE
565 NOT USED
566 SIERRA LEONEAN
567 NOT USED
568 SOMALIAN
569 SWAZILAND
570 SOUTH AFRICAN
571 UNION OF SOUTH AFRICA
572 AFRIKANER
573 NATALIAN
574 ZULU
575 NOT USED
576 SUDANESE
577 DINKA
578 NUER
579 FUR
580 BAGGARA
581 NOT USED
582 TANZANIAN
583 TANGANYIKAN
584 ZANZIBAR ISLANDER
585 NOT USED
586 TOGO
587 NOT USED
588 UGANDAN
589 UPPER VOLTAN
590 VOLTA
591 ZAIRIAN
592 ZAMBIAN
593 ZIMBABWEAN
594 AFRICAN ISLANDS (EXCEPT MADAGASCAR)
595 MAURITIAN
596 CENTRAL AFRICAN
597 EASTERN AFRICAN
598 WESTERN AFRICAN
599 AFRICAN
 
600-699 SOUTH ASIA
600 AFGHANISTAN
601 BALUCHISTAN
602 PATHAN
603 BANGLADESHI
604-606 NOT USED
607 BHUTANESE
608 NOT USED
609 NEPALI
610-614 NOT USED
615 ASIAN INDIAN
616 KASHMIR
617 NOT USED
618 BENGALI
619 NOT USED
620 EAST INDIAN
621 NOT USED
622 ANDAMAN ISLANDER
623 NOT USED
624 ANDHRA PRADESH
625 NOT USED
626 ASSAMESE
627 NOT USED
628 GOANESE
629 NOT USED
630 GUJARATI
631 NOT USED
632 KARNATAKAN
633 NOT USED
634 KERALAN
635 NOT USED
636 MADHYA PRADESH
637 NOT USED
638 MAHARASHTRAN
639 NOT USED
640 MADRAS
641 NOT USED
642 MYSORE
643 NOT USED
644 NAGALAND
645 NOT USED
646 ORISSA
647 NOT USED
648 PONDICHERRY
649 NOT USED
650 PUNJAB
651 NOT USED
652 RAJASTHAN
653 NOT USED
654 SIKKIM
655 NOT USED
656 TAMIL NADU
657 NOT USED
658 UTTAR PRADESH
659-674 NOT USED
675 EASTINDIES
676-679 NOT USED
680 PAKISTANI
681-689 NOT USED
690 SRILANKAN
691 SINGHALESE
692 VEDDAH
693-694 NOT USED
695 MALDIVIAN
696-699 NOT USED
 
700-799 OTHER ASIA
700 BURMESE
701 NOT USED
702 SHAN
703 CAMBODIAN
704 KHMER
705 NOT USED
706 CHINESE
707 CANTONESE
708 MANCHURIAN
709 MANDARIN
710-711 NOT USED
712 MONGOLIAN
713 NOT USED
714 TIBETAN
715 NOT USED
716 HONG KONG
717 NOT USED
718 MACAO
719 NOT USED
720 FILIPINO
721-729 NOT USED
730 INDONESIAN
731 NOT USED
732 BORNEO
733 NOT USED
734 JAVA
735 NOT USED
736 SUMATRA
737-739 NOT USED
740 JAPANESE
741 ISSEI
742 NISEI
743 SANSEI
744 YONSEI
745 GONSEI
746 RYUKYU ISLANDER
747 NOT USED
748 OKINAWAN
749 NOT USED
750 KOREAN
751-764 NOT USED
765 LAOTIAN
766 MEO
767 NOT USED
768 HMONG
769 NOT USED
770 MALAYSIAN
771 NORTH BORNEO
772-773 NOT USED
774 SINGAPOREAN
775 NOT USED
776 THAI
777 BLACK THAI
778 WESTERN LAO
779-781 NOT USED
782 TAIWANESE
783 FORMOSAN
784 NOT USED
785 VIETNAMESE
786 KATU
787 MA
788 MNONG
789 NOT USED
790 MONTAGNARD
791 NOT USED
792 INDO CHINESE
793 EURASIAN
794 AMERASIAN
795 ASIAN
796-799 NOT USED
 
800-899 PACIFIC
800 AUSTRALIAN
801 TASMANIAN
802 AUSTRALIAN ABORIGINE
803 NEW ZEALANDER
804 TUVALUAN
805 NORFOLK ISLANDER
806-807 NOT USED
808 POLYNESIAN
809 KAPINGAMARANGAN
810 MAORI
811 HAWAIIAN
812 NOT USED
813 PART HAWAIIAN
814 SAMOAN
815 TONGAN
816 TOKELAUAN
817 COOK ISLANDER
818 TAHITIAN
819 NIUEAN
820 MICRONESIAN
821 GUAMANIAN
822 CHAMORRO ISLANDER
823 SAIPANESE
824 PALAUAN
825 MARSHALLESE
826 KOSRAEAN
827 PONAPEAN
828 TRUKESE (CHUUKESE)
829 YAPESE
830 CAROLINIAN
831 KIRIBATESE
832 NAURUAN
833 TARAWA ISLANDER
834 TINIAN ISLANDER
835-839 NOT USED
840 MELANESIAN
841 FIJIAN
842 NOT USED
843 NEW GUINEAN
844 PAPUAN
845 SOLOMON ISLANDER
846 NEW CALEDONIAN
847 VANUATUAN
848-849 NOT USED
850 PACIFIC ISLANDER
851-859 NOT USED
860 PACIFIC
861 NOT USED
862 CHAMOLINIAN
863-899 NOT USED
 
900-994 NORTH AMERICA (EXCEPT HISPANIC)
900 AFRO AMERICAN
901 AFRO
902 AFRICAN AMERICAN
903 BLACK
904 NEGRO
905 NONWHITE
906 COLORED
907 CREOLE
908 MULATTO
909- NOT USED
913 CENTRAL AMERICAN INDIAN
914 SOUTH AMERICAN INDIAN
915- NOT USED
917 NATIVE AMERICAN
918 INDIAN
919 CHEROKEE
920 AMERICAN INDIAN
921 ALEUT
922 ESKIMO
923 INUIT
924 WHITE
925 ANGLO
926 NOT USED
927 APPALACHIAN
928 ARYAN
929 PENNSYLVANIA GERMAN
930 GREENLANDER
931 CANADIAN
932 NOT USED
933 NEWFOUNDLAND
934 NOVA SCOTIA
935 FRENCH CANADIAN
936 ACADIAN
937 CAJUN
938 NOT USED
939 AMERICAN
940 UNITED STATES
941 ALABAMA
942 ALASKA
943 ARIZONA
944 ARKANSAS
945 CALIFORNIA
946 COLORADO
947 CONNECTICUT
948 DISTRICT OF COLUMBIA
949 DELAWARE
950 FLORIDA
951 IDAHO
952 ILLINOIS
953 INDIANA
954 IOWA
955 KANSAS
956 KENTUCKY
957 LOUISIANA
958 MAINE
959 MARYLAND
960 MASSACHUSETTS
961 MICHIGAN
962 MINNESOTA
963 MISSISSIPPI
964 MISSOURI
965 MONTANA
966 NEBRASKA
967 NEVADA
968 NEW HAMPSHIRE
969 NEW JERSEY
970 NEW MEXICO
971 NEW YORK
972 NORTH CAROLINA
973 NORTH DAKOTA
974 OHIO
975 NOT USED
976 OKLAHOMA
977 OREGON
978 PENNSYLVANIA
979 RHODE ISLAND
980 SOUTH CAROLINA
981 SOUTH DAKOTA
982 TENNESSEE
983 TEXAS
984 UTAH
985 VERMONT
986 VIRGINIA
987 WASHINGTON
988 WEST VIRGINIA
989 WISCONSIN
990 WYOMING
991 GEORGIA
992 NOT USED
993 SOUTHERNER
994 NORTH AMERICAN
 
995-999 RESIDUAL AND NORESPONSE
995 MIXTURE
996 UNCODABLE ENTRIES
997 NOT USED
998 OTHER RESPONSES
999 NOT REPORTED

Group Quarters Classifications
Institutional Group Quarters:
Correctional facilities for adults
101. Federal detention centers
102. Federal prisons
103. State prisons
104. Local jails and other municipal confinement facilities
105. Correctional residential facilities
106. Military disciplinary barracks and jails
 
Juvenile facilities
201. Group homes for juveniles (non-correctional)
202. Residential treatment centers for juveniles (non-correctional)
203. Correctional facilities intended for juveniles
 
Nursing facilities/skilled-nursing facilities
301. Nursing facilities/skilled-nursing facilities
 
Other institutional facilities
401. Mental (psychiatric) hospitals and psychiatric units in other hospitals
402. Hospitals with patients who have no usual home elsewhere
403. In-patient hospice facilities
404. Military treatment facilities with assigned patients
405. Residential schools for people with disabilities
 
Noninstitutional Group Quarters:
 
College/university student housing
501. College/university student housing
 
Military Quarters
601. Military quarters
602. Military ships
 
Other noninstitutional facilities
701. Emergency and transitional shelters (with sleeping facilities) for people experiencing homelessness
801. Group homes intended for adults
802. Residential treatment centers for adults
901. Workers' group living quarters and Job Corps centers
902. Religious group quarters

Hispanic Origin Code List

001-199, 300-999

Not Spanish/Hispanic

200-209 Spaniard 210-220 Mexican
221-230 Central American 231-249 South American 250-259 Latin American
260-269 Puerto Rican 270-274 Cuban 275-279 Dominican

280-299

Other Spanish/Hispanic

   
     
001-199 Not Spanish/Hispanic
001-099 Not used

100 Not Hispanic/Spanish

(CHECK BOX)

101 Not Hispanic/Spanish
102-109 Not Used 110 Portuguese 111 Azorean
112 Brazilian 113-115 Not Used 116 Belizean
117 British Honduran 118 Haitian 119 Dominica Island
120 Basque 121 Sephardic 122-129 Not used
130 White 131-134 Not used 135 Black (African American)
136-144 Not used 145 American Indian 146 Alaska Native
147-149 Not used 150 Other Asian 151 Asian Indian
152 Chinese 153 Filipino 154 Japanese
155 Korean 156 Vietnamese 157-159 Not used
160 Native Hawaiian 161-165 Not used 166 Other Pacific Islander
167 Guamanian or Chamorro 168 Samoan 169-199 Not used
     
200-209 Spaniard
200 Spaniard 201 Andalusian 202 Asturian
203 Castillian 204 Catalonian 205 Balearic Islander
206 Gallego 207 Valencian 208 Canarian
209 Spanish Basque    
     
210-220 Mexican
210 Mexican (CHECK BOX) 211 Mexican 212 Mexican American
213 Mexicano 214 Chicano 215 La Raza
216 Mexican American Indian 217 Not Used 218 Mexican State
219 Mexican Indian 220 Not Used  
     
221-230 Central American
221 Costa Rican 222 Guatemalan 223 Honduran
224 Nicaraguan 225 Panamanian 226 Salvadoran
227 Central American 228 Central American Indian 229 Canal Zone
230 Not Used    
     
231-249 South American
231 Argentinean 232 Bolivian 233 Chilean
234 Colombian 235 Ecuadorian 236 Paraguayan
237 Peruvian 238 Uruguayan 239 Venezuelan
240 South American Indian 241 Criollo 242 South American
243-249 Not Used    
     
250-259 Latin American
250 Latin American 251 Latin 252 Latino
253-259 Not Used    
     
260-269 Puerto Rican
260 Puerto Rican (CHECK BOX) 261 Puerto Rican 262-269 Not Used
     
270-274 Cuban
270 Cuban (CHECK BOX) 271 Cuban 272-274 Not used
     
275-279 Dominican
275 Dominican 276-279 Not Used  
     
280-299 Other Spanish/Hispanic
280 Other Spanish/Hispanic (CHECK BOX) 281 Hispanic 282 Spanish
283 Californio 284 Tejano 285 Nuevo Mexicano
286 Spanish American 287 Spanish American Indian 288 Meso American Indian
289 Mestizo 290 Caribbean 291-298 Not Used
299 Other Spanish/Hispanic, N.E.C.    


Industry Code List
  Industry 2007 Description 2007 Census Code 2007 NAICS Code
       
Agriculture, Forestry, Fishing, and Hunting, and Mining 0170-0490 11-21
       
  Agriculture, Forestry, Fishing, and Hunting 0170-0290 11
       
  Crop production 0170 111
  Animal production 0180 112
  Forestry except logging 0190 1131, 1132
  Logging 0270 1133
  Fishing, hunting and trapping 0280 114
  Support activities for agriculture and forestry 0290 115
       
  Mining, Quarrying, and Oil and Gas Extraction 0370-0490 21
       
  Oil and gas extraction 0370 211
  Coal mining 0380 2121
  Metal ore mining 0390 2122
  Nonmetallic mineral mining and quarrying 0470 2123
  Not specified type of mining 0480 Part of 21
  Support activities for mining 0490 213
       
Construction 0770 23
       
  Construction (the cleaning of buildings and dwellings is incidental during construction and immediately after construction) 0770 23
       
Manufacturing 1070-3990 31-33
       
  Animal food, grain and oilseed milling 1070 3111, 3112
  Sugar and confectionery products 1080 3113
  Fruit and vegetable preserving and specialty food manufacturing 1090 3114
  Dairy product manufacturing 1170 3115
  Animal slaughtering and processing 1180 3116
  Retail bakeries 1190 311811
  Bakeries, except retail 1270 3118 exc. 311811
  Seafood and other miscellaneous foods, n.e.c. 1280 3117, 3119
  Not specified food industries 1290 Part of 311
  Beverage manufacturing 1370 3121
  Tobacco manufacturing 1390 3122
  Fiber, yarn, and thread mills 1470 3131
  Fabric mills, except knitting mills 1480

3132 exc.

31324

  Textile and fabric finishing and fabric coating mills 1490 3133
  Carpet and rug mills 1570 31411
  Textile product mills, except carpet and rug 1590

314 exc.

31411

  Knitting fabric mills, and apparel knitting mills 1670 31324, 3151
  Cut and sew apparel manufacturing 1680 3152
  Apparel accessories and other apparel manufacturing 1690 3159
  Footwear manufacturing 1770 3162
  Leather tanning and finishing and other allied products manufacturing 1790 3161, 3169
  Pulp, paper, and paperboard mills 1870 3221
  Paperboard containers and boxes 1880 32221
  Miscellaneous paper and pulp products 1890 32222,32223,32229
  Printing and related support activities 1990 3231
  Petroleum refining 2070 32411
  Miscellaneous petroleum and coal products 2090 32412,32419
  Resin, synthetic rubber, and fibers and filaments manufacturing 2170 3252
  Agricultural chemical manufacturing 2180 3253
  Pharmaceutical and medicine manufacturing 2190 3254
  Paint, coating, and adhesive manufacturing 2270 3255
  Soap, cleaning compound, and cosmetics manufacturing 2280 3256
  Industrial and miscellaneous chemicals 2290 3251, 3259
  Plastics product manufacturing 2370 3261
  Tire manufacturing 2380 32621
  Rubber products, except tires, manufacturing 2390 32622, 32629
  Pottery, ceramics, and plumbing fixture manufacturing 2470 32711
  Structural clay product manufacturing 2480 32712
  Glass and glass product manufacturing 2490 3272
  Cement, concrete, lime, and gypsum product manufacturing 2570 3273, 3274
  Miscellaneous nonmetallic mineral product manufacturing 2590 3279
  Iron and steel mills and steel product manufacturing 2670 3311, 3312
  Aluminum production and processing 2680 3313
  Nonferrous metal (except aluminum) production and processing 2690 3314
  Foundries 2770 3315
  Metal forgings and stampings 2780 3321
  Cutlery and hand tool manufacturing 2790 3322
  Structural metals, and boiler, tank, and shipping container manufacturing 2870 3323, 3324
  Machine shops; turned product; screw, nut, and bolt manufacturing 2880 3327
  Coating, engraving, heat treating, and allied activities 2890 3328
  Ordnance 2970

332992,

332993,

332994,

332995

  Miscellaneous fabricated metal products manufacturing 2980

3325,

3326,

3329 exc.

332992,

332993,

332994,

332995

  Not specified metal industries 2990 Part of 331 and 332
  Agricultural implement manufacturing 3070 33311
  Construction, and mining and oil and gas field machinery manufacturing 3080 33312, 33313
  Commercial and service industry machinery manufacturing 3090 3333
  Metalworking machinery manufacturing 3170 3335
  Engines, turbines, and power transmission equipment manufacturing 3180 3336
  Machinery manufacturing, n.e.c. 3190 3332, 3334, 3339
  Not specified machinery manufacturing 3290 Part of 333
  Computer and peripheral equipment manufacturing 3360 3341
  Communications, and audio and video equipment manufacturing 3370 3342, 3343
  Navigational, measuring, electromedical, and control instruments manufacturing 3380 3345
  Electronic component and product manufacturing, n.e.c. 3390 3344, 3346
  Household appliance manufacturing 3470 3352
  Electric lighting and electrical equipment manufacturing, and other electrical component manufacturing, n.e.c. 3490 3351, 3353, 3359
  Motor vehicles and motor vehicle equipment manufacturing 3570 3361, 3362, 3363
  Aircraft and parts manufacturing 3580

336411,

336412,

336413

  Aerospace products and parts manufacturing 3590

336414,

336415,

336419

  Railroad rolling stock manufacturing 3670 3365
  Ship and boat building 3680 3366
  Other transportation equipment manufacturing 3690 3369
  Sawmills and wood preservation 3770 3211
  Veneer, plywood, and engineered wood products 3780 3212
  Prefabricated wood buildings and mobile homes 3790 321991, 321992
  Miscellaneous wood products 3870

3219 exc.

321991,

321992

  Furniture and related product manufacturing 3890 337
  Medical equipment and supplies manufacturing 3960 3391
  Sporting and athletic goods, and doll, toy and game manufacturing 3970 33992, 33993
  Miscellaneous manufacturing, n.e.c. 3980 3399 exc. 33992, 33993
  Not specified manufacturing industries 3990 Part of 31, 32, 33
       
Wholesale Trade 4070-4590 42
       
  Motor vehicles, parts and supplies merchant wholesalers 4070 4231
  Furniture and home furnishing merchant wholesalers 4080 4232
  Lumber and other construction materials merchant wholesalers 4090 4233
  Professional and commercial equipment and supplies merchant wholesalers 4170 4234
  Metals and minerals, except petroleum, merchant wholesalers 4180 4235
  Electrical and electronic goods merchant wholesalers 4190 4236
  Hardware, plumbing and heating equipment, and supplies merchant wholesalers 4260 4237
  Machinery, equipment, and supplies merchant wholesalers 4270 4238
  Recyclable material merchant wholesalers 4280 42393
  Miscellaneous durable goods merchant wholesalers 4290

4239 exc.

42393

  Paper and paper products merchant wholesalers 4370 4241
  Drugs, sundries, and chemical and allied products merchant wholesalers 4380 4242, 4246
  Apparel, fabrics, and notions merchant wholesalers 4390 4243
  Groceries and related products merchant wholesalers 4470 4244
  Farm product raw materials merchant wholesalers 4480 4245
  Petroleum and petroleum products merchant wholesalers 4490 4247
  Alcoholic beverages merchant wholesalers 4560 4248
  Farm supplies merchant wholesalers 4570 42491
  Miscellaneous nondurable goods merchant wholesalers 4580

4249 exc.

42491

  Wholesale electronic markets and agents and brokers 4585 4251
  Not specified wholesale trade 4590 Part of 42
       
Retail Trade 4670-5790 44-45
       
  Automobile dealers 4670 4411
  Other motor vehicle dealers 4680 4412
  Auto parts, accessories, and tire stores 4690 4413
  Furniture and home furnishings stores 4770 442
  Household appliance stores 4780 443111
  Radio, TV, and computer stores 4790

443112,

44312

  Building material and supplies dealers 4870

4441 exc.

44413

  Hardware stores 4880 44413
  Lawn and garden equipment and supplies stores 4890 4442
  Grocery stores 4970 4451
  Specialty food stores 4980 4452
  Beer, wine, and liquor stores 4990 4453
  Pharmacies and drug stores 5070 44611
  Health and personal care, except drug, stores 5080

446 exc.

44611

  Gasoline stations 5090 447
  Clothing stores 5170 4481
  Shoe stores 5180 44821
  Jewelry, luggage, and leather goods stores 5190 4483
  Sporting goods, camera, and hobby and toy stores 5270 44313, 45111, 45112
  Sewing, needlework, and piece goods stores 5280 45113
  Music stores 5290 45114, 45122
  Book stores and news dealers 5370 45121
  Department stores and discount stores 5380 45211
  Miscellaneous general merchandise stores 5390 4529
  Retail florists 5470 4531
  Office supplies and stationery stores 5480 45321
  Used merchandise stores 5490 4533
  Gift, novelty, and souvenir shops 5570 45322
  Miscellaneous retail stores 5580 4539
  Electronic shopping 5590 454111
  Electronic auctions 5591 454112
  Mail order houses 5592 454113
  Vending machine operators 5670 4542
  Fuel dealers 5680 45431
  Other direct selling establishments 5690 45439
  Not specified retail trade 5790 Part of 44, 45
       
Transportation and Warehousing and Utilities 6070-6390, 0570-0690 48-49, 22
       
  Transportation and Warehousing 6070-6390 48-49
       
  Air transportation 6070 481
  Rail transportation 6080 482
  Water transportation 6090 483
  Truck transportation 6170 484
  Bus service and urban transit 6180 4851, 4852, 4854, 4855, 4859
  Taxi and limousine service 6190 4853
  Pipeline transportation 6270 486
  Scenic and sightseeing transportation 6280 487
  Services incidental to transportation 6290 488
  Postal Service 6370 491
  Couriers and messengers 6380 492
  Warehousing and storage 6390 493
       
  Utilities 0570-0690 22
       
  Electric power generation, transmission and distribution 0570 2211
  Natural gas distribution 0580 2212
  Electric and gas, and other combinations 0590 Pts. 2211, 2212
  Water, steam, air-conditioning, and irrigation systems 0670 22131, 22133
  Sewage treatment facilities 0680 22132
  Not specified utilities 0690 Part of 22
       
Information 6470-6780 51
       
  Newspaper publishers 6470 51111
  Periodical, book, and directory publishers 6480

5111 exc.

51111

  Software publishers 6490 5112
  Motion picture and video industries 6570 5121
  Sound recording industries 6590 5122
  Radio and television broadcasting and cable subscription programming 6670 515
  Internet publishing and broadcasting and web search portals 6672 51913
  Wired telecommunications carriers 6680 5171
  Other telecommunications services 6690

517 exc.

5171

  Data processing, hosting, and related services 6695 5182
  Libraries and archives 6770 51912
  Other information services 6780

5191 exc.

51912,

51913

       
Finance and Insurance, and Real Estate, and Rental and Leasing 6870-7190 52-53
       
  Finance and Insurance 6870-6990 52
       
  Banking and related activities 6870 521, 52211,52219
  Savings institutions, including credit unions 6880 52212, 52213
  Non-depository credit and related activities 6890 5222, 5223
  Securities, commodities, funds, trusts, and other financial investments 6970 523, 525
  Insurance carriers and related activities 6990 524
       
  Real Estate and Rental and Leasing 7070-7190 53
       
  Real estate 7070 531
  Automotive equipment rental and leasing 7080 5321
  Video tape and disk rental 7170 53223
  Other consumer goods rental 7180 53221, 53222, 53229, 5323
  Commercial, industrial, and other intangible assets rental and leasing 7190 5324, 533
       
Professional, Scientific, and Management, and Administrative, and Waste Management Services 7270-7790 54-56
       
  Professional, Scientific, and Technical Services 7270-7490 54
       
  Legal services 7270 5411
  Accounting, tax preparation, bookkeeping, and payroll services 7280 5412
  Architectural, engineering, and related services 7290 5413
  Specialized design services 7370 5414
  Computer systems design and related services 7380 5415
  Management, scientific, and technical consulting services 7390 5416
  Scientific research and development services 7460 5417
  Advertising and related services 7470 5418
  Veterinary services 7480 54194
  Other professional, scientific, and technical services 7490

5419 exc.

54194

       
  Management of companies and enterprises 7570 55
       
  Management of companies and enterprises 7570 55
       
  Administrative and support and waste management services 7580-7790 56
       
  Employment services 7580 5613
  Business support services 7590 5614
  Travel arrangements and reservation services 7670 5615
  Investigation and security services 7680 5616
  Services to buildings and dwellings (except cleaning during construction and immediately after construction) 7690

5617 exc.

56173

  Landscaping services 7770 56173
  Other administrative and other support services 7780 5611, 5612, 5619
  Waste management and remediation services 7790 562
       
Educational Services, and Health Care and Social Assistance 7860-8470 61-62
       
  Educational Services 7860-7890 61
       
  Elementary and secondary schools 7860 6111
  Colleges and universities, including junior colleges 7870 6112, 6113
  Business, technical, and trade schools and training 7880 6114, 6115
  Other schools and instruction, and educational support services 7890 6116, 6117
       
  Health Care and Social Assistance 7970-8470 62
       
  Offices of physicians 7970 6211
  Offices of dentists 7980 6212
  Offices of chiropractors 7990 62131
  Offices of optometrists 8070 62132
  Offices of other health practitioners 8080

6213 exc.

62131, 62132

  Outpatient care centers 8090 6214
  Home health care services 8170 6216
  Other health care services 8180 6215,6219
  Hospitals 8190 622
  Nursing care facilities 8270 6231
  Residential care facilities, without nursing 8290 6232, 6233, 6239
  Individual and family services 8370 6241
  Community food and housing, and emergency services 8380 6242
  Vocational rehabilitation services 8390 6243
  Child day care services 8470 6244
       
Arts, Entertainment, and Recreation, and Accommodation and Food Services 8560-8690 71-72
       
  Arts, Entertainment, and Recreation 8560-8590 71
       
  Independent artists, performing arts, spectator sports, and related industries 8560 711
  Museums, art galleries, historical sites, and similar institutions 8570 712
  Bowling centers 8580 71395
  Other amusement, gambling, and recreation industries 8590

713 exc.

71395

       
  Accommodation and Food Services 8660-8690 72
       
  Traveler accommodation 8660 7211
  Recreational vehicle parks and camps, and rooming and boarding houses 8670 7212, 7213
  Restaurants and other food services 8680 722 exc. 7224
  Drinking places, alcoholic beverages 8690 7224
       
Other Services, Except Public Administration 8770-9290 81
       
  Automotive repair and maintenance 8770

8111 exc.

811192

  Car washes 8780 811192
  Electronic and precision equipment repair and 8790 8112
  maintenance    
  Commercial and industrial machinery and equipment repair and maintenance 8870 8113
  Personal and household goods repair and maintenance 8880

8114 exc.

81143

  Footwear and leather goods repair 8890 81143
  Barber shops 8970 812111
  Beauty salons 8980 812112
  Nail salons and other personal care services 8990 812113, 81219
  Drycleaning and laundry services 9070 8123
  Funeral homes, and cemeteries and crematories 9080 8122
  Other personal services 9090 8129
  Religious organizations 9160 8131
  Civic, social, advocacy organizations, and grantmaking and giving services 9170 8132, 8133, 8134
  Labor unions 9180 81393
  Business, professional, political, and similar organizations 9190

8139 exc.

81393

  Private households 9290 814
       
Public Administration 9370-9590 92
       
  Executive offices and legislative bodies 9370

92111, 92112,

92114, pt.

92115

  Public finance activities 9380 92113
  Other general government and support 9390 92119
  Justice, public order, and safety activities 9470 922, pt. 92115
  Administration of human resource programs 9480 923
  Administration of environmental quality and housing programs 9490 924,925
  Administration of economic programs and space research 9570 926, 927
  National security and international affairs 9590 928
       
Military 9670-9870 928110
       
  U. S. Army 9670 928110
  U. S. Air Force 9680 928110
  U. S. Navy 9690 928110
  U. S. Marines 9770 928110
  U. S. Coast Guard 9780 928110
  Armed Forces, Branch not specified 9790 928110
  Military Reserves or National Guard 9870 928110
       
  Unemployed and last worked 5 years ago or earlier or never worked 9920 none


Language Code List
601  Jamaican Creole 602  Krio 603  Hawaiian Pidgi
604  Pidgin 605  Gullah 606  Saramacca
607  German 608  Pennsylvania Dutch 609 Yiddish
610  Dutch 611  Afrikaans 612  Frisian
613  Luxembourgian 614  Swedish 615  Danish
616  Norwegian 617  Icelandic 618  Faroese
619  Italian 620  French 621  Provencal
622  Patois 623  French Creole 624  Cajun
625  Spanish 626  Catalonian 627  Ladino
628  Pachuco 629  Portuguese 630  Papia Mentae
631  Romanian 632  Rhaeto-Romanic 633  Welsh
634  Breton 635  Irish Gaelic 636  Scottic Gaelic
637  Greek 638  Albanian 639  Russian
640  Bielorussian 641  Ukrainian 642  Czech
643  Kashubian 644  Lusatian 645  Polish
646  Slovak 647  Bulgarian 648  Macedonian
649  Serbocroatian 650  Croatian 651  Serbian
652  Slovene 653  Lithuanian 654  Latvian
655  Armenian 656  Persian 657  Pashto
658  Kurdish 659  Balochi 660  Tadzhik
661  Ossete 662  India N.E.C. 663  Hindi
664  Bengali 665  Panjabi 666  Marathi
667  Gujarati 668 Bihari 669  Rajasthani
670  Oriya 671  Urdu 672  Assamese
673  Kashmiri 674  Nepali 675  Sindhi
676  Pakistan N.E.C. 677  Sinhalese 678  Romany
679  Finnish 680  Estonian 681  Lapp
682  Hungarian 683  Other Uralic Lang. 684  Chuvash
685  Karakalpak 686  Kazakh 687  Kirghiz
688  Karachay 689  Uighur 690  Azerbaijani
691  Turkish 692  Turkmen 693  Yakut
694  Mongolian 695  Tungus 696  Caucasian
697  Basque 698  Dravidian 699  Brahui
700  Gondi 701  Telugu 702  Kannada
703  Malayalam 704  Tamil 705  Kurukh
706  Munda 707  Burushaski 708  Chinese
709  Hakka 710  Kan, Hsiang 711  Cantonese
712  Mandarin 713  Fuchow 714  Formosan
715  Wu 716  Tibetan 717  Burmese
718  Karen 719  Kachin 720  Thai
721  Mien 722  Hmong 723  Japanese
724  Korean 725  Laotian 726  Mon-Khmer, Cambodian
727  Paleo-Siberian 728  Vietnamese 729  Muong
730  Buginese 731  Moluccan 732  Indonesian
733  Achinese 734  Balinese 735  Cham
736  Javanese 737  Madurese 738  Malagasy
739  Malay 740  Minangkabau 741  Sundanese
742  Tagalog 743  Bisayan 744  Sebuano
745  Pangasinan 746 Ilocano 747  Bikol
748  Pampangan 749  Gorontalo 750  Micronesian
751  Carolinian 752  Chamorro 753  Gilbertese
754  Kusaiean 755  Marshallese 756  Mokilese
757  Mortlockese 758  Nauruan 759  Palau
760  Ponapean 761  Trukese 762  Ulithean
763  Woleai-Ulithi 764  Yapese 765  Melanesian
766  Polynesian 767  Samoan 768  Tongan
769  Niuean 770  Tokelauan 771  Fijian
772  Marquesan 773  Rarotongan 774  Maori
775  Nukuoro 776  Hawaiian 777  Arabic
778  Hebrew 779  Syriac 780  Amharic
781  Berber 782  Chadic 783  Cushite
784  Sudanic 785  Nilotic 786  Nilo-Hamitic
787  Nubian 788  Saharan 789  Nilo-Saharan
790  Khoisan 791  Swahili 792  Bantu
793  Mande 794  Fulani 795  Gur
796  Kru, Ibo, Yoruba 797  Efik 798  Mbum (And Related)
799  African 800  Unangan/Aleut 801  Alutiiq/Sugpiaq
802  Eskimo 803  Inupiaq 804  St Lawrence Island Yupik
805  Central Alaskan Yup'ik 806  Algonquian 807  Arapaho
808  Atsina 809  Blackfoot 810  Cheyenne
811  Cree 812  Delaware 813  Fox
814  Kickapoo 815  Menomini 816  French Cree
817  Miami 818  Micmac 819  Ojibwa
820  Ottawa 821  Passamaquoddy 822  Penobscot
823  Abnaki 824  Potawatomi 825  Shawnee
826  Wiyot 827  Yurok 828 Kutenai
829  Makah 830  Kwakiutl 831  Nootka
833  Lower Chehalis 834  Upper Chehalis 835  Clallam
836  Coeur D'Alene 837  Columbia 838  Cowlitz
839  Salish 840  Nootsack 841  Okanogan
842  Puget Sound Salish 843  Quinault 844  Tillamook
845  Twana 846  Haida 847  Athapascan
848  Ahtena 849  Han 850  Ingalit
851  Koyukon 852  Kuchin 853  Upper Kuskokwim
854  Tanaina 855  Tanana 856  Tanacross
857  Upper Tanana 858  Tutchone 859  Chasta Costa
860  Hupa 861  Other Athapascan Eyak 862  Apache
863  Kiowa 864  Navaho 865  Eyak
866  Tlingit 867  Mountain Maidu 868  Northwest Maidu
869  Southern Maidu 870  Coast Miwok 871  Plains Miwok
872  Sierra Miwok 873  Nomlaki 874  Patwin
875  Wintun 876  Foothill North Yokuts 877  Tachi
878  Santiam 879  Siuslaw 880  Klamath
881  Nez Perce 882  Sahaptian 883  Upper Chinook
884  Tsimshian 885  Achumawi 886  Atsugewi
887  Karok 888  Pomo 889  Shastan
890  Washo 891  Up River Yuman 892  Cocomaricopa
893  Mohave 894  Yuma 895 Diegueno
896  Delta River Yuman 897  Upland Yuman 898  Havasupai
899  Walapai 900  Yavapai 901  Chumash
902  Tonkawa 903  Yuchi 904  Crow
905  Hidatsa 906  Mandan 907  Dakota
908  Chiwere 909  Winnebago 910  Kansa
911  Omaha 912  Osage 913  Ponca
914  Quapaw 915  Alabama 916  Choctaw
917  Mikasuki 918  Hichita 919  Koasati
920  Muskogee 921  Chetemacha 922  Yuki
923  Wappo 924  Keres 925  Iroquois
926  Mohawk 927  Oneida 928  Onondaga
929  Cayuga 930  Seneca 931  Tuscarora
932  Wyandot 933  Cherokee 934  Arikara
935  Caddo 936  Pawnee 937  Wichita
938  Comanche 939  Mono 940  Paiute
941  Northern Paiute 942  Southern Paiute 943  Chemehuevi
944  Kawaiisu 945  Ute 946  Shoshoni
947  Panamint 948  Hopi 949  Cahuilla
950  Cupeno 951  Luiseno 952  Serrano
953  Tubatulabal 954  Pima 955  Yaqui
956  Aztecan 957  Sonoran, n.e.c. 959  Picuris
960  Tiwa 961  Sandia 962  Tewa
963  Towa 964 Zuni 965  Chinook Jargon
966  American Indian 967  Misumalpan 968  Mayan Languages
969  Tarascan 970  Mapuche 971  Oto-Manguen
972  Quechua 973  Aymara 974  Arawakian
975  Chibchan 976  Tupi-Guarani 977  Jicarilla
978  Chiricahua 979  San Carlos 980  Kiowa-apache
981  Kalispel 982  Spokane 983-997  Not Used
998  Specified Not Listed 999  Not Specified  

Occupation Code List
  Occupation 2010 Description 2010 Census Code 2010 SOC Code
       
  The 2010 census occupation classification list has 539 codes including 4 military codes.    
       
Management, Business, Science, and Arts Occupations: 0010-3540 11-0000 - 29-0000
       
  Management, Business, and Financial Occupations: 0010-0950 11-0000 - 13-0000
       
  Management Occupations: 0010-0430 11-0000
       
  Chief executives 0010 11-1011
  General and operations managers 0020 11-1021
  Legislators 0030 11-1031
  Advertising and promotions managers 0040 11-2011
  Marketing and sales managers 0050 11-2020
  Public relations and fundraising managers 0060 11-2031
  Administrative services managers 0100 11-3011
  Computer and information systems managers 0110 11-3021
  Financial managers 0120 11-3031
  Compensation and benefits managers 0135 11-3111
  Human resources managers 0136 11-3121
  Training and development managers 0137 11-3131
  Industrial production managers 0140 11-3051
  Purchasing managers 0150 11-3061
  Transportation, storage, and distribution managers 0160 11-3071
  Farmers, ranchers, and other agricultural managers 0205 11-9013
  Construction managers 0220 11-9021
  Education administrators 0230 11-9030
  Architectural and engineering managers 0300 11-9041
  Food service managers 0310 11-9051
  Funeral service managers 0325 11-9061
  Gaming managers 0330 11-9071
  Lodging managers 0340 11-9081
  Medical and health services managers 0350 11-9111
  Natural sciences managers 0360 11-9121
  Postmasters and mail superintendents 0400 11-9131
  Property, real estate, and community association managers 0410 11-9141
  Social and community service managers 0420 11-9151
  Emergency management directors 0425 11-9161
  Managers, all other 0430 11-9199
       
  Business and Financial Operations Occupations: 0500-0950 13-0000
       
  Agents and business managers of artists, performers, and athletes 0500 13-1011
  Buyers and purchasing agents, farm products 0510 13-1021
  Wholesale and retail buyers, except farm products 0520 13-1022
  Purchasing agents, except wholesale, retail, and farm products 0530 13-1023
  Claims adjusters, appraisers, examiners, and investigators 0540 13-1030
  Compliance officers 0565 13-1041
  Cost estimators 0600 13-1051
  Human resources workers 0630 13-1070
  Compensation, benefits, and job analysis specialists 0640 13-1141
  Training and development specialists 0650 13-1151
  Logisticians 0700 13-1081
  Management analysts 0710 13-1111
  Meeting, convention, and event planners 0725 13-1121
  Fundraisers 0726 13-1131
  Market research analysts and marketing specialists 0735 13-1161
  Business operations specialists, all other 0740 13-1199
  Accountants and auditors 0800 13-2011
  Appraisers and assessors of real estate 0810 13-2021
  Budget analysts 0820 13-2031
  Credit analysts 0830 13-2041
  Financial analysts 0840 13-2051
  Personal financial advisors 0850 13-2052
  Insurance underwriters 0860 13-2053
  Financial examiners 0900 13-2061
  Credit counselors and loan officers 0910 13-2070
  Tax examiners and collectors, and revenue agents 0930 13-2081
  Tax preparers 0940 13-2082
  Financial specialists, all other 0950 13-2099
       
  Computer, Engineering, and Science Occupations: 1000-1965 15-0000 - 19-0000
       
  Computer and mathematical occupations: 1000-1240 15-0000
       
  Computer and information research scientists 1005 15-1111
  Computer systems analysts 1006 15-1121
  Information security analysts 1007 15-1122
  Computer programmers 1010 15-1131
  Software developers, applications and systems software 1020 15-113X
  Web developers 1030 15-1134
  Computer support specialists 1050 15-1150
  Database administrators 1060 15-1141
  Network and computer systems administrators 1105 15-1142
  Computer network architects 1106 15-1143
  Computer occupations, all other 1107 15-1199
  Actuaries 1200 15-2011
  Mathematicians 1210 15-2021
  Operations research analysts 1220 15-2031
  Statisticians 1230 15-2041
  Miscellaneous mathematical science occupations 1240 15-2090
       
  Architecture and Engineering Occupations: 1300-1560 17-0000
       
  Architects, except naval 1300 17-1010
  Surveyors, cartographers, and photogrammetrists 1310 17-1020
  Aerospace engineers 1320 17-2011
  Agricultural engineers 1330 17-2021
  Biomedical engineers 1340 17-2031
  Chemical engineers 1350 17-2041
  Civil engineers 1360 17-2051
  Computer hardware engineers 1400 17-2061
  Electrical and electronics engineers 1410 17-2070
  Environmental engineers 1420 17-2081
  Industrial engineers, including health and safety 1430 17-2110
  Marine engineers and naval architects 1440 17-2121
  Materials engineers 1450 17-2131
  Mechanical engineers 1460 17-2141
  Mining and geological engineers, including mining safety engineers 1500 17-2151
  Nuclear engineers 1510 17-2161
  Petroleum engineers 1520 17-2171
  Engineers, all other 1530 17-2199
  Drafters 1540 17-3010
  Engineering technicians, except drafters 1550 17-3020
  Surveying and mapping technicians 1560 17-3031
       
  Life, Physical, and Social Science Occupations: 1600-1965 19-0000
       
  Agricultural and food scientists 1600 19-1010
  Biological scientists 1610 19-1020
  Conservation scientists and foresters 1640 19-1030
  Medical scientists 1650 19-1040
  Life scientists, all other 1660 19-1099
  Astronomers and physicists 1700 19-2010
  Atmospheric and space scientists 1710 19-2021
  Chemists and materials scientists 1720 19-2030
  Environmental scientists and geoscientists 1740 19-2040
  Physical scientists, all other 1760 19-2099
  Economists 1800 19-3011
  Survey researchers 1815 19-3022
  Psychologists 1820 19-3030
  Sociologists 1830 19-3041
  Urban and regional planners 1840 19-3051
  Miscellaneous social scientists and related workers 1860 19-3090
  Agricultural and food science technicians 1900 19-4011
  Biological technicians 1910 19-4021
  Chemical technicians 1920 19-4031
  Geological and petroleum technicians 1930 19-4041
  Nuclear technicians 1940 19-4051
  Social science research assistants 1950 19-4061
  Miscellaneous life, physical, and social science technicians 1965 19-4090
       
  Education, Legal, Community Service, Arts, and Media Occupations: 2000-2960 21-0000 - 27-0000
       
  Community and Social Service Occupations: 2000-2060 21-0000
       
  Counselors 2000 21-1010
  Social workers 2010 21-1020
  Probation officers and correctional treatment specialists 2015 21-1092
  Social and human service assistants 2016 21-1093
  Miscellaneous community and social service specialists, including health educators and community health workers 2025 21-109X
  Clergy 2040 21-2011
  Directors, religious activities and education 2050 21-2021
  Religious workers, all other 2060 21-2099
       
  Legal Occupations: 2100-2160 23-0000
       
  Lawyers 2100 23-1011
  Judicial law clerks 2105 23-1012
  Judges, magistrates, and other judicial workers 2110 23-1020
  Paralegals and legal assistants 2145 23-2011
  Miscellaneous legal support workers 2160 23-2090
       
  Education, Training, and Library Occupations: 2200-2550 25-0000
       
  Postsecondary teachers 2200 25-1000
  Preschool and kindergarten teachers 2300 25-2010
  Elementary and middle school teachers 2310 25-2020
  Secondary school teachers 2320 25-2030
  Special education teachers 2330 25-2050
  Other teachers and instructors 2340 25-3000
  Archivists, curators, and museum technicians 2400 25-4010
  Librarians 2430 25-4021
  Library technicians 2440 25-4031
  Teacher assistants 2540 25-9041
  Other education, training, and library workers 2550 25-90XX
       
  Arts, Design, Entertainment, Sports, and Media Occupations: 2600-2960 27-0000
       
  Artists and related workers 2600 27-1010
  Designers 2630 27-1020
  Actors 2700 27-2011
  Producers and directors 2710 27-2012
  Athletes, coaches, umpires, and related workers 2720 27-2020
  Dancers and choreographers 2740 27-2030
  Musicians, singers, and related workers 2750 27-2040
  Entertainers and performers, sports and related workers, all other 2760 27-2099
  Announcers 2800 27-3010
  News analysts, reporters and correspondents 2810 27-3020
  Public relations specialists 2825 27-3031
  Editors 2830 27-3041
  Technical writers 2840 27-3042
  Writers and authors 2850 27-3043
  Miscellaneous media and communication workers 2860 27-3090
  Broadcast and sound engineering technicians and radio operators 2900 27-4010
  Photographers 2910 27-4021
  Television, video, and motion picture camera operators and editors 2920 27-4030
  Media and communication equipment workers, all other 2960 27-4099
       
  Healthcare Practitioners and Technical Occupations: 3000-3540 29-0000
       
  Chiropractors 3000 29-1011
  Dentists 3010 29-1020
  Dietitians and nutritionists 3030 29-1031
  Optometrists 3040 29-1041
  Pharmacists 3050 29-1051
  Physicians and surgeons 3060 29-1060
  Physician assistants 3110 29-1071
  Podiatrists 3120 29-1081
  Audiologists 3140 29-1181
  Occupational therapists 3150 29-1122
  Physical therapists 3160 29-1123
  Radiation therapists 3200 29-1124
  Recreational therapists 3210 29-1125
  Respiratory therapists 3220 29-1126
  Speech-language pathologists 3230 29-1127
  Exercise physiologists 3235 29-1128
  Therapists, all other 3245 29-1129
  Veterinarians 3250 29-1131
  Registered nurses 3255 29-1141
  Nurse anesthetists 3256 29-1151
  Nurse midwives 3257 29-1161
  Nurse practitioners 3258 29-1171
  Health diagnosing and treating practitioners, all other 3260 29-1199
  Clinical laboratory technologists and technicians 3300 29-2010
  Dental hygienists 3310 29-2021
  Diagnostic related technologists and technicians 3320 29-2030
  Emergency medical technicians and paramedics 3400 29-2041
  Health practitioner support technologists and technicians 3420 29-2050
  Licensed practical and licensed vocational nurses 3500 29-2061
  Medical records and health information technicians 3510 29-2071
  Opticians, dispensing 3520 29-2081
  Miscellaneous health technologists and technicians 3535 29-2090
  Other healthcare practitioners and technical occupations 3540 29-9000
       
Service Occupations: 3600-4650 31-0000 - 39-0000
       
  Healthcare Support Occupations: 3600-3655 31-0000
       
  Nursing, psychiatric, and home health aides 3600 31-1010
  Occupational therapy assistants and aides 3610 31-2010
  Physical therapist assistants and aides 3620 31-2020
  Massage therapists 3630 31-9011
  Dental assistants 3640 31-9091
  Medical assistants 3645 31-9092
  Medical transcriptionists 3646 31-9094
  Pharmacy aides 3647 31-9095
  Veterinary assistants and laboratory animal caretakers 3648 31-9096
  Phlebotomists 3649 31-9097
  Healthcare support workers, all other, including medical equipment preparers 3655 31-909X
       
  Protective Service Occupations: 3700-3955 33-0000
       
  First-line supervisors of correctional officers 3700 33-1011
  First-line supervisors of police and detectives 3710 33-1012
  First-line supervisors of fire fighting and prevention workers 3720 33-1021
  First-line supervisors of protective service workers, all other 3730 33-1099
  Firefighters 3740 33-2011
  Fire inspectors 3750 33-2020
  Bailiffs, correctional officers, and jailers 3800 33-3010
  Detectives and criminal investigators 3820 33-3021
  Fish and game wardens 3830 33-3031
  Parking enforcement workers 3840 33-3041
  Police and sheriff's patrol officers 3850 33-3051
  Transit and railroad police 3860 33-3052
  Animal control workers 3900 33-9011
  Private detectives and investigators 3910 33-9021
  Security guards and gaming surveillance officers 3930 33-9030
  Crossing guards 3940 33-9091
  Transportation security screeners 3945 33-9093
  Lifeguards and other recreational, and all other protective service workers 3955 33-909X
       
  Food Preparation and Serving Related Occupations: 4000-4160 35-0000
       
  Chefs and head cooks 4000 35-1011
  First-line supervisors of food preparation and serving workers 4010 35-1012
  Cooks 4020 35-2010
  Food preparation workers 4030 35-2021
  Bartenders 4040 35-3011
  Combined food preparation and serving workers, including fast food 4050 35-3021
  Counter attendants, cafeteria, food concession, and coffee shop 4060 35-3022
  Waiters and waitresses 4110 35-3031
  Food servers, nonrestaurant 4120 35-3041
  Dining room and cafeteria attendants and bartender helpers 4130 35-9011
  Dishwashers 4140 35-9021
  Hosts and hostesses, restaurant, lounge, and coffee shop 4150 35-9031
  Food preparation and serving related workers, all other 4160 35-9099
       
  Building and Grounds Cleaning and Maintenance Occupations: 4200-4250 37-0000
       
  First-line supervisors of housekeeping and janitorial workers 4200 37-1011
  First-line supervisors of landscaping, lawn service, and groundskeeping workers 4210 37-1012
  Janitors and building cleaners 4220 37-201X
  Maids and housekeeping cleaners 4230 37-2012
  Pest control workers 4240 37-2021
  Grounds maintenance workers 4250 37-3010
       
  Personal Care and Service Occupations: 4300-4650 39-0000
       
  First-line supervisors of gaming workers 4300 39-1010
  First-line supervisors of personal service workers 4320 39-1021
  Animal trainers 4340 39-2011
  Nonfarm animal caretakers 4350 39-2021
  Gaming services workers 4400 39-3010
  Motion picture projectionists 4410 39-3021
  Ushers, lobby attendants, and ticket takers 4420 39-3031
  Miscellaneous entertainment attendants and related workers 4430 39-3090
  Embalmers and funeral attendants 4460 39-40XX
  Morticians, undertakers, and funeral directors 4465 39-4031
  Barbers 4500 39-5011
  Hairdressers, hairstylists, and cosmetologists 4510 39-5012
  Miscellaneous personal appearance workers 4520 39-5090
  Baggage porters, bellhops, and concierges 4530 39-6010
  Tour and travel guides 4540 39-7010
  Childcare workers 4600 39-9011
  Personal care aides 4610 39-9021
  Recreation and fitness workers 4620 39-9030
  Residential advisors 4640 39-9041
  Personal care and service workers, all other 4650 39-9099
       
Sales and Office Occupations: 4700-5940 41-0000 - 43-0000
       
  Sales and Related Occupations: 4700-4965 41-0000
       
  First-line supervisors of retail sales workers 4700 41-1011
  First-line supervisors of non-retail sales workers 4710 41-1012
  Cashiers 4720 41-2010
  Counter and rental clerks 4740 41-2021
  Parts salespersons 4750 41-2022
  Retail salespersons 4760 41-2031
  Advertising sales agents 4800 41-3011
  Insurance sales agents 4810 41-3021
  Securities, commodities, and financial services sales agents 4820 41-3031
  Travel agents 4830 41-3041
  Sales representatives, services, all other 4840 41-3099
  Sales representatives, wholesale and manufacturing 4850 41-4010
  Models, demonstrators, and product promoters 4900 41-9010
  Real estate brokers and sales agents 4920 41-9020
  Sales engineers 4930 41-9031
  Telemarketers 4940 41-9041
  Door-to-door sales workers, news and street vendors, and related workers 4950 41-9091
  Sales and related workers, all other 4965 41-9099
       
  Office and Administrative Support Occupations: 5000-5940 43-0000
       
  First-line supervisors of office and administrative support workers 5000 43-1011
  Switchboard operators, including answering service 5010 43-2011
  Telephone operators 5020 43-2021
  Communications equipment operators, all other 5030 43-2099
  Bill and account collectors 5100 43-3011
  Billing and posting clerks 5110 43-3021
  Bookkeeping, accounting, and auditing clerks 5120 43-3031
  Gaming cage workers 5130 43-3041
  Payroll and timekeeping clerks 5140 43-3051
  Procurement clerks 5150 43-3061
  Tellers 5160 43-3071
  Financial clerks, all other 5165 43-3099
  Brokerage clerks 5200 43-4011
  Correspondence clerks 5210 43-4021
  Court, municipal, and license clerks 5220 43-4031
  Credit authorizers, checkers, and clerks 5230 43-4041
  Customer service representatives 5240 43-4051
  Eligibility interviewers, government programs 5250 43-4061
  File clerks 5260 43-4071
  Hotel, motel, and resort desk clerks 5300 43-4081
  Interviewers, except eligibility and loan 5310 43-4111
  Library assistants, clerical 5320 43-4121
  Loan interviewers and clerks 5330 43-4131
  New accounts clerks 5340 43-4141
  Order clerks 5350 43-4151
  Human resources assistants, except payroll and timekeeping 5360 43-4161
  Receptionists and information clerks 5400 43-4171
  Reservation and transportation ticket agents and travel clerks 5410 43-4181
  Information and record clerks, all other 5420 43-4199
  Cargo and freight agents 5500 43-5011
  Couriers and messengers 5510 43-5021
  Dispatchers 5520 43-5030
  Meter readers, utilities 5530 43-5041
  Postal service clerks 5540 43-5051
  Postal service mail carriers 5550 43-5052
  Postal service mail sorters, processors, and processing machine operators 5560 43-5053
  Production, planning, and expediting clerks 5600 43-5061
  Shipping, receiving, and traffic clerks 5610 43-5071
  Stock clerks and order fillers 5620 43-5081
  Weighers, measurers, checkers, and samplers, recordkeeping 5630 43-5111
  Secretaries and administrative assistants 5700 43-6010
  Computer operators 5800 43-9011
  Data entry keyers 5810 43-9021
  Word processors and typists 5820 43-9022
  Desktop publishers 5830 43-9031
  Insurance claims and policy processing clerks 5840 43-9041
  Mail clerks and mail machine operators, except postal service 5850 43-9051
  Office clerks, general 5860 43-9061
  Office machine operators, except computer 5900 43-9071
  Proofreaders and copy markers 5910 43-9081
  Statistical assistants 5920 43-9111
  Office and administrative support workers, all other 5940 43-9199
       
  Farming, Fishing, and Forestry Occupations: 6005-6130 45-0000
       
  First-line supervisors of farming, fishing, and forestry workers 6005 45-1011
  Agricultural inspectors 6010 45-2011
  Animal breeders 6020 45-2021
  Graders and sorters, agricultural products 6040 45-2041
  Miscellaneous agricultural workers 6050 45-2090
  Fishers and related fishing workers 6100 45-3011
  Hunters and trappers 6110 45-3021
  Forest and conservation workers 6120 45-4011
  Logging workers 6130 45-4020
       
  Construction and Extraction Occupations: 6200-6940 47-0000
       
  Boilermakers 6210 47-2011
  Brickmasons, blockmasons, and stonemasons 6220 47-2020
  Carpenters 6230 47-2031
  Carpet, floor, and tile installers and finishers 6240 47-2040
  Cement masons, concrete finishers, and terrazzo workers 6250 47-2050
  Construction laborers 6260 47-2061
  Paving, surfacing, and tamping equipment operators 6300 47-2071
  Pile-driver operators 6310 47-2072
  Operating engineers and other construction equipment operators 6320 47-2073
  Drywall installers, ceiling tile installers, and tapers 6330 47-2080
  Electricians 6355 47-2111
  Glaziers 6360 47-2121
  Insulation workers 6400 47-2130
  Painters, construction and maintenance 6420 47-2141
  Paperhangers 6430 47-2142
  Pipelayers, plumbers, pipefitters, and steamfitters 6440 47-2150
  Plasterers and stucco masons 6460 47-2161
  Reinforcing iron and rebar workers 6500 47-2171
  Roofers 6515 47-2181
  Sheet metal workers 6520 47-2211
  Structural iron and steel workers 6530 47-2221
  Solar photovoltaic installers 6540 47-2231
  Helpers, construction trades 6600 47-3010
  Construction and building inspectors 6660 47-4011
  Elevator installers and repairers 6700 47-4021
  Fence erectors 6710 47-4031
  Hazardous materials removal workers 6720 47-4041
  Highway maintenance workers 6730 47-4051
  Rail-track laying and maintenance equipment operators 6740 47-4061
  Septic tank servicers and sewer pipe cleaners 6750 47-4071
  Miscellaneous construction and related workers 6765 47-4090
  Derrick, rotary drill, and service unit operators, oil, gas, and mining 6800 47-5010
  Earth drillers, except oil and gas 6820 47-5021
  Explosives workers, ordnance handling experts, and blasters 6830 47-5031
  Mining machine operators 6840 47-5040
  Roof bolters, mining 6910 47-5061
  Roustabouts, oil and gas 6920 47-5071
  Helpers-extraction workers 6930 47-5081
  Other extraction workers 6940 47-50XX
       
  Installation, Maintenance, and Repair Occupations: 7000-7630 49-0000
       
  First-line supervisors of mechanics, installers, and repairers 7000 49-1011
  Computer, automated teller, and office machine repairers 7010 49-2011
  Radio and telecommunications equipment installers and repairers 7020 49-2020
  Avionics technicians 7030 49-2091
  Electric motor, power tool, and related repairers 7040 49-2092
  Electrical and electronics installers and repairers, transportation equipment 7050 49-2093
  Electrical and electronics repairers, industrial and utility 7100 49-209X
  Electronic equipment installers and repairers, motor vehicles 7110 49-2096
  Electronic home entertainment equipment installers and repairers 7120 49-2097
  Security and fire alarm systems installers 7130 49-2098
  Aircraft mechanics and service technicians 7140 49-3011
  Automotive body and related repairers 7150 49-3021
  Automotive glass installers and repairers 7160 49-3022
  Automotive service technicians and mechanics 7200 49-3023
  Bus and truck mechanics and diesel engine specialists 7210 49-3031
  Heavy vehicle and mobile equipment service technicians and mechanics 7220 49-3040
  Small engine mechanics 7240 49-3050
  Miscellaneous vehicle and mobile equipment mechanics, installers, and repairers 7260 49-3090
  Control and valve installers and repairers 7300 49-9010
  Heating, air conditioning, and refrigeration mechanics and installers 7315 49-9021
  Home appliance repairers 7320 49-9031
  Industrial and refractory machinery mechanics 7330 49-904X
  Maintenance and repair workers, general 7340 49-9071
  Maintenance workers, machinery 7350 49-9043
  Millwrights 7360 49-9044
  Electrical power-line installers and repairers 7410 49-9051
  Telecommunications line installers and repairers 7420 49-9052
  Precision instrument and equipment repairers 7430 49-9060
  Wind turbine service technicians 7440 49-9081
  Coin, vending, and amusement machine servicers and repairers 7510 49-9091
  Commercial divers 7520 49-9092
  Locksmiths and safe repairers 7540 49-9094
  Manufactured building and mobile home installers 7550 49-9095
  Riggers 7560 49-9096
  Signal and track switch repairers 7600 49-9097
  Helpers-installation, maintenance, and repair workers 7610 49-9098
  Other installation, maintenance, and repair workers 7630 49-909X
       
Production, Transportation, and Material Moving Occupations: 7700-9750 51-0000 - 53-0000
       
  Production Occupations: 7700-8965 51-0000
       
  First-line supervisors of production and operating workers 7700 51-1011
  Aircraft structure, surfaces, rigging, and systems assemblers 7710 51-2011
  Electrical, electronics, and electromechanical assemblers 7720 51-2020
  Engine and other machine assemblers 7730 51-2031
  Structural metal fabricators and fitters 7740 51-2041
  Miscellaneous assemblers and fabricators 7750 51-2090
  Bakers 7800 51-3011
  Butchers and other meat, poultry, and fish processing workers 7810 51-3020
  Food and tobacco roasting, baking, and drying machine operators and tenders 7830 51-3091
  Food batchmakers 7840 51-3092
  Food cooking machine operators and tenders 7850 51-3093
  Food processing workers, all other 7855 51-3099
  Computer control programmers and operators 7900 51-4010
  Extruding and drawing machine setters, operators, and tenders, metal and plastic 7920 51-4021
  Forging machine setters, operators, and tenders, metal and plastic 7930 51-4022
  Rolling machine setters, operators, and tenders, metal and plastic 7940 51-4023
  Cutting, punching, and press machine setters, operators, and tenders, metal and plastic 7950 51-4031
  Drilling and boring machine tool setters, operators, and tenders, metal and plastic 7960 51-4032
  Grinding, lapping, polishing, and buffing machine tool setters, operators, and tenders, metal and plastic 8000 51-4033
  Lathe and turning machine tool setters, operators, and tenders, metal and plastic 8010 51-4034
  Milling and planing machine setters, operators, and tenders, metal and plastic 8020 51-4035
  Machinists 8030 51-4041
  Metal furnace operators, tenders, pourers, and casters 8040 51-4050
  Model makers and patternmakers, metal and plastic 8060 51-4060
  Molders and molding machine setters, operators, and tenders, metal and plastic 8100 51-4070
  Multiple machine tool setters, operators, and tenders, metal and 8120 51-4081
  plastic    
  Tool and die makers 8130 51-4111
  Welding, soldering, and brazing workers 8140 51-4120
  Heat treating equipment setters, operators, and tenders, metal and plastic 8150 51-4191
  Layout workers, metal and plastic 8160 51-4192
  Plating and coating machine setters, operators, and tenders, metal and plastic 8200 51-4193
  Tool grinders, filers, and sharpeners 8210 51-4194
  Metal workers and plastic workers, all other 8220 51-4199
  Prepress technicians and workers 8250 51-5111
  Printing press operators 8255 51-5112
  Print binding and finishing workers 8256 51-5113
  Laundry and dry-cleaning workers 8300 51-6011
  Pressers, textile, garment, and related materials 8310 51-6021
  Sewing machine operators 8320 51-6031
  Shoe and leather workers and repairers 8330 51-6041
  Shoe machine operators and tenders 8340 51-6042
  Tailors, dressmakers, and sewers 8350 51-6050
  Textile bleaching and dyeing machine operators and tenders 8360 51-6061
  Textile cutting machine setters, operators, and tenders 8400 51-6062
  Textile knitting and weaving machine setters, operators, and tenders 8410 51-6063
  Textile winding, twisting, and drawing out machine setters, operators, and tenders 8420 51-6064
  Extruding and forming machine setters, operators, and tenders, synthetic and glass fibers 8430 51-6091
  Fabric and apparel patternmakers 8440 51-6092
  Upholsterers 8450 51-6093
  Textile, apparel, and furnishings workers, all other 8460 51-6099
  Cabinetmakers and bench carpenters 8500 51-7011
  Furniture finishers 8510 51-7021
  Model makers and patternmakers, wood 8520 51-7030
  Sawing machine setters, operators, and tenders, wood 8530 51-7041
  Woodworking machine setters, operators, and tenders, except 8540 51-7042
  sawing    
  Woodworkers, all other 8550 51-7099
  Power plant operators, distributors, and dispatchers 8600 51-8010
  Stationary engineers and boiler operators 8610 51-8021
  Water and wastewater treatment plant and system operators 8620 51-8031
  Miscellaneous plant and system operators 8630 51-8090
  Chemical processing machine setters, operators, and tenders 8640 51-9010
  Crushing, grinding, polishing, mixing, and blending workers 8650 51-9020
  Cutting workers 8710 51-9030
  Extruding, forming, pressing, and compacting machine setters, operators, and tenders 8720 51-9041
  Furnace, kiln, oven, drier, and kettle operators and tenders 8730 51-9051
  Inspectors, testers, sorters, samplers, and weighers 8740 51-9061
  Jewelers and precious stone and metal workers 8750 51-9071
  Medical, dental, and ophthalmic laboratory technicians 8760 51-9080
  Packaging and filling machine operators and tenders 8800 51-9111
  Painting workers 8810 51-9120
  Photographic process workers and processing machine operators 8830 51-9151
  Semiconductor processors 8840 51-9141
  Adhesive bonding machine operators and tenders 8850 51-9191
  Cleaning, washing, and metal pickling equipment operators and tenders 8860 51-9192
  Cooling and freezing equipment operators and tenders 8900 51-9193
  Etchers and engravers 8910 51-9194
  Molders, shapers, and casters, except metal and plastic 8920 51-9195
  Paper goods machine setters, operators, and tenders 8930 51-9196
  Tire builders 8940 51-9197
  Helpers-production workers 8950 51-9198
  Production workers, all other 8965 51-9199
       
  Transportation and Material Moving Occupations: 9000-9750 53-0000
       
  Transportation Occupations: 9000-9420 53-1000 - 53-6000
       
  Supervisors of transportation and material moving workers 9000 53-1000
  Aircraft pilots and flight engineers 9030 53-2010
  Air traffic controllers and airfield operations specialists 9040 53-2020
  Flight attendants 9050 53-2031
  Ambulance drivers and attendants, except emergency medical technicians 9110 53-3011
  Bus drivers 9120 53-3020
  Driver/sales workers and truck drivers 9130 53-3030
  Taxi drivers and chauffeurs 9140 53-3041
  Motor vehicle operators, all other 9150 53-3099
  Locomotive engineers and operators 9200 53-4010
  Railroad brake, signal, and switch operators 9230 53-4021
  Railroad conductors and yardmasters 9240 53-4031
  Subway, streetcar, and other rail transportation workers 9260 53-40XX
  Sailors and marine oilers 9300 53-5011
  Ship and boat captains and operators 9310 53-5020
  Ship engineers 9330 53-5031
  Bridge and lock tenders 9340 53-6011
  Parking lot attendants 9350 53-6021
  Automotive and watercraft service attendants 9360 53-6031
  Transportation inspectors 9410 53-6051
  Transportation attendants, except flight attendants 9415 53-6061
  Other transportation workers 9420 53-60XX
       
  Material Moving Occupations: 9500-9750 53-7000
       
  Conveyor operators and tenders 9500 53-7011
  Crane and tower operators 9510 53-7021
  Dredge, excavating, and loading machine operators 9520 53-7030
  Hoist and winch operators 9560 53-7041
  Industrial truck and tractor operators 9600 53-7051
  Cleaners of vehicles and equipment 9610 53-7061
  Laborers and freight, stock, and material movers, hand 9620 53-7062
  Machine feeders and offbearers 9630 53-7063
  Packers and packagers, hand 9640 53-7064
  Pumping station operators 9650 53-7070
  Refuse and recyclable material collectors 9720 53-7081
  Mine shuttle car operators 9730 53-7111
  Tank car, truck, and ship loaders 9740 53-7121
  Material moving workers, all other 9750 53-7199
       
Military Specific Occupations: 9800-9830 55-0000
       
  Military officer special and tactical operations leaders 9800 55-1010
  First-line enlisted military supervisors 9810 55-2010
  Military enlisted tactical operations and air/weapons specialists and crew members 9820 55-3010
  Military, rank not specified 9830 none
       
  Unemployed, with no work experience in the last 5 years or earlier or never worked 9920 none


Place of Birth, Migration, & Place of Work Code List
This section contains the numerical list of U.S. States, U.S. Island Areas, foreign countries and other areas. This list was used to assign a three-digit code to birthplaces and state or foreign country of previous residences and places of work reported by each person. The alphabetical list used in coding included abbreviations and alternate names, including some historical names for countries and names of States, provinces, counties, or other subdivisions of countries.

The following list does not include any of these alternate names, but does include continent and area names used as defaults if a specific country was not named but a broader region or area was reported. The names of foreign countries shown on this list and in the publications reflect the most commonly used names for this country, not their official or legal names. Each entry shown on the following list has a unique code.

The U.S. States and U.S. Island Areas were assigned their Federal Information Processing Standards (FIPS) code preceded by a zero. Foreign countries codes were generally assigned by listing the countries or areas in alphabetical order within eight broad continent or regional areas: (1) Europe, (2) Asia, (3) Northern America, (4) Central America, (5) Caribbean, (6) South America, (7) Africa, and (8) Oceania.
001-059 United States 060-099 U.S. Outlying Areas and Puerto Rico
100-157, 160, 162-199 Europe 158-159, 161, 200-299 Asia
300-399 Americas 400-499 Africa
500-553 Oceania 554-999 At Sea/Abroad, Not Reported
 
001-059 United States
 
001 Alabama 002 Alaska 003 Not Used
004 Arizona 005 Arkansas 006 California
007 Not Used 008 Colorado 009 Connecticut
010 Delaware 011 District of Columbia 012 Florida
013 Georgia 014 Not Used 015 Hawaii
016 Idaho 017 Illinois 018 Indiana
019 Iowa 020 Kansas 021 Kentucky
022 Louisiana 023 Maine 024 Maryland
025 Massachusetts 026 Michigan 027 Minnesota
028 Mississippi 029 Missouri 030 Montana
031 Nebraska 032 Nevada 033 New Hampshire
034 New Jersey 035 New Mexico 036 New York
037 North Carolina 038 North Dakota 039 Ohio
040 Oklahoma 041 Oregon 042 Pennsylvania
043 Not Used 044 Rhode Island 045 South Carolina
046 South Dakota 047 Tennessee 048 Texas
049 Utah 050 Vermont 051 Virginia
052 Not Used 053 Washington 054 West Virginia
055 Wisconsin 056 Wyoming 057-059 Not Used
 
060-099 U.S. Outlying Areas and Puerto Rico
 
060 American Samoa 066 Guam 067 Johnston Atoll
069 Northern Marianas 071 Midway Islands 072 Puerto Rico
076 Navassa Island 078 U.S. Virgin Islands 079 Wake Island
081 Baker Island 084 Howland Island 086 Jarvis Island
089 Kingman Reef 095 Palmyra Atoll 096 U.S. Island Area
097-099 Not Used    
 
100-157, 160, 162-199 Europe
 
106-108,118,119,121,127,135,136,138-145 Northern Europe
101,102,103,109,110,122,123,125,126,137 Western Europe
115,116,120,124,129-131,133,134,146 Southern Europe
 
100,104,105,117,128,132,147-157,160,162,163,164,165,167, 168 Eastern Europe
     
100 Albania 101 Andorra 102 Austria
103 Belgium 104 Bulgaria 105 Czechoslovakia
106 Denmark 107 Faroe Islands 108 Finland
109 France 110 Germany 111-114 Not Used
115 Gibraltar 116 Greece 117 Hungary
118 Iceland 119 Ireland 120 Italy
121 Jan Mayan 122 Liechtenstein 123 Luxembourg
124 Malta 125 Monaco 126 Netherlands
127 Norway 128 Poland 129 Portugal
130 Azores Islands 131 Madeira Islands 132 Romania
133 San Marino 134 Spain 135 Svalbard
136 Sweden 137 Switzerland 138 United Kingdom
139 England 140 Scotland 141 Wales
142 Northern Ireland 143 Guernsey 144 Jersey
145 Isle of Man 146 Vatican City 147 Yugoslavia
148 Czech Republic 149 Slovakia 150 Bosnia and Herzegovina
151 Croatia 152 Macedonia 153 Slovenia
154 Serbia 155 Estonia 156 Latvia
157 Lithuania 160 Belarus 162 Moldova
163 Russia 164 Ukraine 165 USSR
166 Europe 167 Kosovo 168 Montenegro
 
169-199 Not Used
138,139,140,141,142,143,144,145 United Kingdom
138,141,142,143,144,145 United Kingdom, excluding England and Scotland
127, 121, 135 Norway
129,130,131 Portugal
105,148,149 Czechoslovakia (includes Czech Republic and Slovakia)
147,154,167 Yugoslavia
 
158-159, 161, 200-299 Asia
 
207,209,215,217,220,221,225,228,232,240 Eastern Asia
200,202,203,210,212,218,219,227,229,231,238,241,244,246 South Central Asia
204,205,206,211,223,226,233,236,242,247,250 South Eastern Asia
158,159,161,201,208,213,214,216,222,224,230,234,235,239,243,245,248 Western Asia
 
158 Armenia 159 Azerbaijan 161 Georgia
200 Afghanistan 201 Bahrain 202 Bangladesh
203 Bhutan 204 Brunei 205 Burma (Myanmar)
206 Cambodia 207 China 208 Cyprus
209 Hong Kong 210 India 211 Indonesia
212 Iran 213 Iraq 214 Israel
215 Japan 216 Jordan 217 Korea
218 Kazakhstan 219 Kyrgyzstan 220 South Korea
221 North Korea 222 Kuwait 223 Laos
224 Lebanon 225 Macau 226 Malaysia
227 Maldives 228 Mongolia 229 Nepal
230 Oman 231 Pakistan 232 Paracel Islands
233 Philippines 234 Qatar 235 Saudi Arabia
236 Singapore 237 Spratley Islands 238 Sri Lanka
239 Syria 240 Taiwan 241 Tajikistan
242 Thailand 243 Turkey 244 Turkmenistan
245 United Arab Emirates 246 Uzbekistan 247 Vietnam
248 Yemen 249 Asia 250 East Timor
 
251-299 Not Used
207,209,232,240,225 China
207, 232, 225 China, excluding Hong Kong and Taiwan
217, 220, 221 Korea
 
300-399 Americas
 
    300-302, 304-309 Northern America
 
300 Bermuda 301 Canada 302 Greenland
304 St. Pierre & Miquelon 305 North America 306-309 Not Used
 
    303, 310-399 Latin America
 
        303, 310-317 Central America
 
303 Mexico 310 Belize 311 Costa Rica
312 El Salvador 313 Guatemala 314 Honduras
315 Nicaragua 316 Panama 317 Central America
318-319 Not Used    
 
    320-359 Caribbean
 
320 Anguilla 321 Antigua & Barbuda 322 Aruba
323 Bahamas 324 Barbados 325 British Virgin Islands
326 Cayman Islands 327 Cuba 328 Dominica
329 Dominican Republic 330 Grenada 331 Guadeloupe
332 Haiti 333 Jamaica 334 Martinique
335 Montserrat 336 Netherlands Antilles 337 St. Barthelemy
338 St. Kitts-Nevis 339 St. Lucia 340 St. Vincent & the Grenadines
341 Trinidad & Tobago 342 Turks & Caicos Islands 343 West Indies
344 Bonaire 345 Curacao 346 Saba
347 Sint Eustatius 348 Sint Maarten 349-359 Not Used
 
    360-399 South America
 
360 Argentina 361 Bolivia 362 Brazil
363 Chile 364 Colombia 365 Ecuador
366 Falkland Islands 367 French Guiana 368 Guyana
369 Paraguay 370 Peru 371 Suriname
372 Uruguay 373 Venezuela 374 South America
375-399 Not Used    
 
400-499 Africa
 
404,406,411,413,416-418,422,426,427,431,432,435,437,441,442,445,446,448,453,455,457,460,461 Eastern Africa
401,407,409,410,412,415,419,443,459 Middle Africa
400,414,430,436,451,456,458,463 Northern Africa
403,428,438,449,452 Southern Africa
402,405,408,420,421,423-425,429,433,434,439,440,444,447,450,454 Western Africa
 
400 Algeria 401 Angola 402 Benin
403 Botswana 404 British Indian Ocean Territory 407 Cameroon
405 Burkina Faso 406 Burundi 410 Chad
408 Cape Verde 409 Central African Republic 413 Djibouti
411 Comoros 412 Congo 416 Ethiopia
414 Egypt 415 Equatorial Guinea 419 Gabon
417 Eritrea 418 Europa Island 422 Glorioso Islands
420 Gambia 421 Ghana 425 Ivory Coast
423 Guinea 424 Guinea-Bissau 428 Lesotho
426 Juan De Nova Island 427 Kenya 431 Madagascar
429 Liberia 430 Libya 434 Mauritania
432 Malawi 433 Mali 437 Mozambique
435 Mayotte 436 Morocco 440 Nigeria
438 Namibia 439 Niger 443 Sao Tome & Principe
441 Reunion 442 Rwanda 446 Seychelles
444 Senegal 445 Mauritius 449 South Africa
447 Sierra Leone 448 Somalia 452 Swaziland
450 St. Helena 451 Sudan 455 Tromelin Island
453 Tanzania 454 Togo 458 Western Sahara
456 Tunisia 457 Uganda 461 Zimbabwe
459 Democratic Republic of Congo (Zaire) 460 Zambia 464-499 Not Used
462 Africa 463 South Sudan  
 
500-553 Oceania
 
501,502,506,507,515,517 Australia and New Zealand Subregion
 
500 Not Used 501 Australia 502 Christmas Island, Indian Ocean
503-504 Not Used 505 Cook Islands 506 Coral Sea Islands
507 Heard & McDonald Islands 508 Fiji 509 French Polynesia
510 Kiribati 511 Marshall Islands 512 Micronesia
513 Nauru 514 New Caledonia 515 New Zealand
516 Niue 517 Norfolk Island 518 Palau
519 Papua New Guinea 520 Pitcairn Islands 521 Solomon Islands
522 Tokelau 523 Tonga 524 Tuvalu
525 Vanuatu 526 Wallis & Futuna Islands 527 Samoa
528 Oceania 529-553 Not Used  
501,506,507 Australia    
 
554-999 At Sea/Abroad, Not Reported
 
554 At Sea 555 Abroad 556-999 Not Used

Race Code List
 
CODE RACE
   
100-199 WHITE
   
100 White (Checkbox)
101 White ethnic group, not elsewhere classified
102 Arab
103 English
104 French
105 German
106 Irish
107 Italian
108 Near Easterner
109 Polish
110 Scottish
111 Armenian
112 Assyrian
113 Egyptian
114 Iranian
115 Iraqi
116 Lebanese
117 Middle East
118 Palestinian
119 Syrian
120 Other Arab
121 Afghanistani
122 Israeli
123 Not Used
124 Cajun
125 Moroccan
126 North African
127 United Arab Emirates
128 Azerbaijani
129 Aryan
130-139 Not Used
140 Multiple WHITE responses
141-149 Not Used
150 White
151 Caucasian
152-199 Not Used
   
200-299 BLACK OR AFRICAN AMERICAN
   
200 Black, African Am, or Negro (Checkbox)
201 Black ethnic group, not elsewhere classified
202 African
203 African American
204 Afro-American
205 Nigritian
206 Negro
207 Bahamian
208 Barbadian
209 Batswana (Botswana)
210-212 Not Used
213 Ethiopian
214 Haitian
215 Jamaican
216 Liberian
217 Not Used
218 Namibian
219 Nigerian
220 Other African
221-222 Not Used
223 Trinidad and Tobago
224 West Indies
225 Zaire
226-227 Not Used
228 South African
229 Not Used
230 Dominica Islander
231-233 Not Used
234 Cayenne
235-239 Not Used
240 Multiple BLACK OR AFRICAN AMERICAN responses
241-249 Not Used
250 Black
251-299 Not Used
   
300-399, A01-Z99 AMERICAN INDIAN AND ALASKA NATIVE
   
300 American Indian or Alaska Native (Checkbox)
301-399 Not Used
   
                              AMERICAN INDIAN TRIBES
   
  Abenaki
A01 Abenaki Nation of Missisquoi
A02 Koasek (Cowasuck) Traditional Band of the Sovereign Abenaki Nation
A03-A04 Not Used
   
  Algonquian
A05 Algonquian
A06-A08 Not Used
   
  Apache
A09 Apache
A10 Not Used
A11 Fort Sill Apache (Chiricahua)
A12 Jicarilla Apache Nation
A13 Lipan Apache
A14 Mescalero Apache Tribe of the Mescalero Reservation, New Mexico
A15 Apache Tribe of Oklahoma
A16 Tonto Apache Tribe of Arizona
A17 San Carlos Apache Tribe of the San Carlos Reservation
A18 White Mountain Apache Tribe of the Fort Apache Reservation, Arizona
A19-A23 Not Used
   
  Arapaho
A24 Arapaho
A25 Northern Arapaho
A26 Southern Arapaho
A27 Arapaho Tribe of the Wind River Reservation, Wyoming
A28-A33 Not Used
   
  Assiniboine
A34 Assiniboine
A35-A37 Not Used
   
  Assiniboine Sioux
A38 Assiniboine Sioux
A39 Fort Peck Assiniboine and Sioux Tribes of the Fort Peck Indian Reservation
A40 Fort Peck Assiniboine
A41 Fort Peck Sioux
A42-A44 Not Used
   
  Blackfeet
A45 Blackfeet Tribe of the Blackfeet Indian Reservation of Montana
A46-A50 Not Used
   
  Brotherton
A51 Brotherton
A52 Not Used
   
  Burt Lake
A53 Burt Lake Chippewa
A54 Burt Lake Band of Ottawa and Chippewa Indians
A55 Burt Lake Ottawa
   
  Caddo
A56 Caddo
A57 Caddo Nation of Oklahoma
A58 Caddo Adais Indians
A59-A60 Not Used
   
  Cahuilla
A61 Agua Caliente Band of Cahuilla Indians
A62 Augustine Band of Cahuilla Indians
A63 Cabazon Band of Mission Indians
A64 Cahuilla
A65 Los Coyotes Band of Cahuilla and Cupeno Indians
A66 Morongo Band of Cahuilla Mission Indians
A67 Santa Rosa Band of Cahuilla Indians
A68 Torres-Martinez Desert Cahuilla Indians
A69 Ramona Band or Village of Cahuilla
A70-A74 Not Used
   
  California Tribes
A75 Cahto Indian Tribe of the Laytonville Rancheria
A76 Chimariko
A77-A78 Not Used
A79 Kawaiisu
A80 Kern River Paiute Council
A81 Mattole
A82 Red Wood
A83 Santa Rosa Indian Community
A84 Takelma
A85 Wappo
A86 Yana
A87 Yuki
A88 Bear River Band of Rohnerville Rancheria
A89 California Valley Miwok Tribe
A90 Redding Rancheria, California
A91 (see under Tolowa)
A92 Cher-Ae Heights Indian Community of the Trinidad Rancheria
A93-A99 Not Used
B01-B03 Not Used
   
  Catawba
B04 Catawba Indian Nation
B05-B06 Not Used
   
  Cayuse
B07 Cayuse
B08-B10 Not Used
   
  Chehalis
B11 Confederated Tribes of the Chehalis Reservation, Washington
B12-B13 Not Used
   
  Chemakuan
B14 Chemakuan
B15 Hoh Indian Tribe of the Hoh Reservation, Washington
B16 Quileute Tribe of the Quileute Reservation, Washington
B17-B18 Not Used
   
  Chemehuevi
B19 Chemehuevi Indian Tribe
B20 Not Used
   
  Cherokee
B21 Cherokee
B22 Cherokee Alabama
B23 Cherokee Tribe of Northeast Alabama
B24 Cher-O-Creek Intratribal Indians
B25 Eastern Band of Cherokees
B26 Echota Cherokee Tribe of Alabama
B27 Georgia Eastern Cherokee
B28 Northern Cherokee Nation of Missouri and Arkansas
B29 Tuscola
B30 United Keetoowah Band of Cherokee
B31 Cherokee Nation of Oklahoma (Western Cherokee)
B32 Southeastern Cherokee Council
B33 Sac River Band of the Chickamauga-Cherokee
B34 White River Band of the Chickamauga-Cherokee
B35 Four Winds Cherokee
B36 Cherokee of Georgia
B37 Piedmont American Indian Association-Lower Eastern Cherokee Nation SC (PAIA)
B38 United Cherokee Ani-Yun-Wiya Nation
B39 Cherokee Bear Clan of South Carolina
   
  Cheyenne
B40 Cheyenne
B41 Northern Cheyenne Tribe of the Northern Cheyenne Reservation, Montana
B42 Southern Cheyenne
B43-B45 Not Used
   
  Cheyenne-Arapaho
B46 Cheyenne and Arapaho Tribes, Oklahoma
B47-B48 Not Used
   
  Chickahominy
B49 Chickahominy Indian Tribe
B50 Chickahominy Eastern Band
B51-B52 Not Used
   
  Chickasaw
B53 Chickasaw Nation
B54 Chaloklowa Chickasaw
B55-B56 Not Used
   
  Chinook
B57 Chinook
B58 Clatsop
B59 Columbia River Chinook
B60 Kathlamet
B61 Upper Chinook
B62 Wakiakum Chinook
B63 Willapa Chinook
B64 Wishram
B65-B66 Not Used
   
  Chippewa
B67 Bad River Band of the Lake Superior Tribe
B68 Bay Mills Indian Community
B69 Bois Forte Band of Chippewa
B70 Not Used
B71 Chippewa
B72 Fond du Lac
B73 Grand Portage
B74 Grand Traverse Band of Ottawa and Chippewa Indians
B75 Keweenaw Bay Indian Community
B76 Lac Court Oreilles Band of Lake Superior Chippewa
B77 Lac du Flambeau
B78 Lac Vieux Desert Band of Lake Superior Chippewa Indians
B79 Lake Superior Chippewa
B80 Leech Lake
B81 Little Shell Tribe of Chippewa Indians of Montana
B82 Mille Lacs
B83 Minnesota Chippewa
B84 Not Used
B85 Red Cliff Band of Lake Superior Chippewa
B86 Red Lake Band of Chippewa Indians
B87 Saginaw Chippewa Indian Tribe
B88 St Croix Chippewa
B89 Sault Ste Marie Tribe of Chippewa Indians
B90 Sokaogon Chippewa Community
B91 Turtle Mountain Band of Chippewa Indians of North Dakota
B92 White Earth
B93 Swan Creek Black River Confederate Tribe
B94-B99 Not Used
   
  Chippewa Cree
C01 Not Used
C02 Chippewa-Cree Indians of the Rocky Boy's Reservation
C03-C04 Not Used
   
  Chitimacha
C05 Chitimacha Tribe of Louisiana
C06 Pointe Au-Chien Indian Tribe
C07 Not Used
   
  Choctaw
C08 Choctaw
C09 Clifton Choctaw
C10 Jena Band of Choctaw
C11 Mississippi Band of Choctaw Indians
C12 MOWA Band of Choctaw Indians
C13 Choctaw Nation of Oklahoma
C14-C16 Not Used
   
  Choctaw-Apache
C17 Choctaw-Apache Community of Ebarb
C18-C19 Not Used
   
  Chumash
C20 Chumash
C21 Santa Ynez Band of Chumash Mission Indians
C22 San Luis Rey Mission Indian
C23-C24 Not Used
   
  Clear Lake
C25 Clear Lake
   
  Coeur D'Alene
C26 Coeur D'Alene Tribe
C27-C28 Not Used
   
  Coharie
C29 Coharie Indian Tribe
C30-C31 Not Used
   
  Colorado River Indian
C32 Colorado River Indian Tribes
C33-C34 Not Used
   
  Colville
C35 Confederated Tribes of the Colville Reservation
C36-C38 Not Used
   
  Comanche
C39 Comanche Nation, Oklahoma
C40-C43 Not Used
   
  Coos, Lower Umpqua, and Siuslaw
C44 Confederated Tribes of Coos, Lower Umpqua, and Siuslaw Indians
C45 Not Used
   
  Coos
C46 Coos
   
  Coquille
C47 Coquille Indian Tribe
C48 Not Used
   
  Costanoan
C49 Costanoan
C50-C51 Not Used
   
  Coushatta
C52 Alabama-Coushatta Tribe of Texas
C53 Coushatta
C54-C55 Not Used
   
  Cowlitz
C56 Cowlitz Indian Tribe
C57-C58 Not Used
   
  Cree
C59 Cree
C60-C63 Not Used
   
  Creek
C64 Alabama Creek
C65 Alabama Quassarte Tribal Town
C66 Muscogee (Creek) Nation
C67 Eastern Creek
C68 Eastern Muscogee
C69 Kialegee Tribal Town
C70 Lower Muscogee Creek Tama Tribal Town
C71 MaChis Lower Creek Indian Tribe
C72 Poarch Band of Creek Indians
C73 Principal Creek Indian Nation
C74 Lower Creek Muscogee Tribe East, Star Clan
C75 Thlopthlocco Tribal Town
C76 Tuckabachee
C77-C80 Not Used
   
  Croatan
C81 Croatan
C82 Not Used
   
  Crow
C83 Crow Tribe of Montana
C84-C86 Not Used
   
  Cumberland
C87 Cumberland County Association for Indian People
C88 Not Used
   
  Cupeno
C89 Agua Caliente
C90 Cupeno
C91-C92 Not Used
   
  Delaware
C93 Delaware (Lenni-Lenape)
C94 Delaware Tribe of Indians, Oklahoma
C95 Not Used
C96 Munsee
C97 Delaware Nation
C98 Ramapough Lenape Nation (Ramapough Mountain)
C99 New Jersey Sand Hill Band of Indians, Inc
D01 Allegheny Lenape
D02-D04 Not Used
   
  Diegueno (Kumeyaay)
D05 Barona Group of Capitan Grande Band
D06 Campo Band of Diegueno Mission Indians
D07 Capitan Grande Band of Diegueno Mission Indians
D08 Ewiiaapaayp Band of Kumeyaay Indians
D09 Diegueno (Kumeyaay)
D10 La Posta Band of Diegueno Mission Indians
D11 Manzanita Band of Diegueno Mission Indians
D12 Mesa Grande Band of Diegueno Mission Indians
D13 San Pasqual Band of Diegueno Mission Indians
D14 Iipay Nation of Santa Ysabel
D15 Sycuan Band of the Kumeyaay Nation
D16 Viejas (Baron Long) Group of Capitan Grande Band
D17 Inaja Band of Diegueno Mission Indians of the Inaja and Cosmit Reservation
D18 Jamul Indian Village
D19 Not Used
   
  Eastern Tribes
D20 Attacapa
D21 Biloxi
D22 Georgetown
D23 Moor
D24 Nansemond Indian Tribe
D25 Natchez Indian Tribe of South Carolina (Kusso-Natchez; Edisto)
D26 Nausu Waiwash
D27 (see under Nipmuc)
D28 Golden Hill Paugussett
D29 Pocomoke Acohonock
D30 Southeastern Indians
D31 Susquehanock
D32 Biloxi-Chitimacha-Choctaw Confederation
D33 Tunica Biloxi Indian Tribe of Louisiana
D34 Waccamaw Siouan Indian Tribe
D35 Beaver Creek Indians
D36 Wicomico
D37 Meherrin Indian Tribe
D38 Santee Indian Organization
D39 Santee Indian Nation of South Carolina
D40 Pee Dee Indian Tribe of South Carolina
D41 Pee Dee Indian Nation of Upper South Carolina
   
  Esselen
D42 Esselen
D43 Not Used
   
  Fort Belknap
D44 Fort Belknap Indian Community of the Fort Belknap Reservation
   
  Three Affiliated Tribes of North Dakota
D45 Three Affiliated Tribes of Ft Berthold Reservation, North Dakota
D46 Mandan
D47 Hidatsa
D48 Arikara (Sahnish)
   
  Fort McDowell
D49 Fort McDowell Yavapai Nation
D50 Not Used
   
  Fort Hall
D51 Shoshone-Bannock Tribes of the Fort Hall Reservation
D52 Lemhi-Shoshone
D53 Bannock
D54 Not Used
   
  Gabrieleno
D55 Gabrieleno
   
  Fernandeno Tataviam Band of Mission Indians
D56 Fernandeno Tataviam Band of Mission Indians
   
  Grand Ronde
D57 Confederated Tribes of the Grand Ronde Community of Oregon
   
  Guilford
D58 Guilford Native American Association
D59 Not Used
   
  Gros Ventres
D60 Atsina
D61 Gros Ventres
D62-D63 Not Used
   
  Haliwa-Saponi
D64 Haliwa-Saponi Indian Tribe
D65-D67 Not Used
   
  Ho-Chunk Nation
D68 Ho-Chunk Nation
D69 Not Used
   
  Hoopa
D70 Hoopa Valley Tribe
D71 Trinity
D72 Whilkut
D73 Not Used
   
  Hopi
D74 Hopi Tribe of Arizona
D75 Arizona Tewa
   
  Hoopa Extension
D76 Hoopa Extension
D77 Not Used
   
  Houma
D78 United Houma Nation
D79-D86 Not Used
   
  Iowa
D87 Iowa
D88 Iowa Tribe of Kansas and Nebraska
D89 Iowa Tribe of Oklahoma
D90 Not Used
   
  Sappony (Indians of Person County)
D91 Sappony
D92 Not Used
   
  Iroquois
D93 Cayuga Nation
D94 Iroquois
D95 Mohawk
D96 Oneida
D97 Onondaga Nation
D98 Seneca
D99 Seneca Nation
E01 Seneca-Cayuga Tribe of Oklahoma
E02 Tonawanda Band of Seneca Indians
E03 Tuscarora Nation
E04 Wyandotte Nation, Oklahoma
E05 Oneida Nation of New York
E06-E09 Not Used
   
  Juaneno (Acjachemem)
E10 Juaneno (Acjachemem)
E11-E12 Not Used
   
  Kalispel
E13 Kalispel Indian Community
E14-E16 Not Used
   
  Karuk
E17 Karuk Tribe of California
E18-E20 Not Used
   
  Kaw
E21 Kaw Nation
E22-E23 Not Used
   
  Kickapoo
E24 Kickapoo
E25 Kickapoo Tribe of Oklahoma
E26 Kickapoo Traditional Tribe of Texas
E27 Kickapoo Tribe of Indians in Kansas
E28-E29 Not Used
   
  Kiowa
E30 Kiowa
E31 Kiowa Indian Tribe of Oklahoma
E32-E36 Not Used
   
  S'Klallam
E37 Jamestown S'Klallam Tribe of Washington
E38 Klallam
E39 Lower Elwha Tribal Community of the Lower Elwha Reservation, Washington
E40 Port Gamble S'Klallam Tribe
E41-E43 Not Used
   
  Klamath
E44 Klamath Indian Tribe of Oregon
E45-E47 Not Used
   
  Konkow
E48 Konkow
E49 Not Used
   
  Kootenai
E50 Kootenai
E51 Kootenai Tribe of Idaho
E52 Not Used
   
  Lassik
E53 Lassik
E54-E58 Not Used
   
  Long Island
E59 Matinecock
E60 Montauk
E61 Poospatuck
E62 Setauket
E63-E65 Not Used
   
  Luiseno
E66 La Jolla Band of Luiseno Mission Indians
E67 Luiseno
E68 Pala Band of Luiseno Mission Indians
E69 Pauma Band of Luiseno Mission Indians
E70 Pechanga Band of Luiseno Mission Indians
E71 Soboba Band of Luiseno Indians
E72 Twenty-Nine Palms Band of Luiseno Mission Indians
E73 Temecula
E74 Rincon Band of Luiseno Mission Indians
E75-E77 Not Used
   
  Lumbee
E78 Lumbee Indian Tribe
E79-E83 Not Used
   
  Lummi
E84 Lummi Tribe
E85 Not Used
   
  Maidu
E86 United Auburn Indian Community
E87 Mooretown Rancheria of Maidu Indians
E88 Maidu
E89 Mountain Maidu
E90 Nisenen (Nishinam)
E91 Mechoopda Indian Tribe of Chico Rancheria
E92 Berry Creek Rancheria of Maidu Indians
E93 Enterprise Rancheria of Maidu Indians
E94 Greenville Rancheria of Maidu Indians
   
  Makah
E95 Makah Indian Tribe
E96-E99 Not Used
   
  Maliseet
F01 Maliseet
F02 Houlton Band of Maliseet Indians
F03-F08 Not Used
   
  Mattaponi
F09 Mattaponi Indian Tribe
F10 Upper Mattaponi Tribe
   
  Menominee
F11 Menominee Indian Tribe
F12-F14 Not Used
   
  Metrolina
F15 Metrolina Native American Association
F16 Not Used
   
  Miami
F17 Illinois Miami
F18 Indiana Miami
F19 Miami
F20 Miami Tribe of Oklahoma
F21-F23 Not Used
   
  Miccosukee
F24 Miccosukee Tribe of Indians of Florida
F25-F26 Not Used
   
  Micmac
F27 Aroostook Band of Micmac Indians
F28 Micmac
F29-F30 Not Used
   
  Mission Indians
F31 Mission Indians
F32 Cahuilla Band of Mission Indians
F33 Not Used
   
  Miwok/Me-Wuk
F34 Ione Band of Miwok Indians
F35 Shingle Springs Band of Miwok Indians
F36 Miwok/Me-Wuk
F37 Jackson Rancheria of Me-Wuk Indians of California
F38 Tuolumne Band of Me-Wuk Indians of California
F39 Buena Vista Rancheria of Me-Wuk Indians of California
F40 Chicken Ranch Rancheria of Me-Wuk Indians
F41 Not Used
   
  Modoc
F42 Modoc
F43 Modoc Tribe of Oklahoma
F44-F45 Not Used
   
  Mohegan
F46 Mohegan Indian Tribe
F47 Not Used
   
  Monacan
F48 Monacan Indian Nation
   
  Mono
F49 Mono
F50 North Fork Rancheria of Mono Indians
F51 Cold Springs Rancheria of Mono Indians
F52 Big Sandy Band of Western Mono Indians
   
  Nanticoke
F53 Nanticoke
F54-F55 Not Used
   
  Nanticoke Lenni-Lenape
F56 Nanticoke Lenni-Lenape
   
  Narragansett
F57 Narragansett Indian Tribe
F58-F61 Not Used
   
  Navajo
F62-F63 Not Used
F64 Navajo Nation
F65-F70 Not Used
   
  Nez Perce
F71 Nez Perce Tribe of Idaho (Nimiipuu)
F72-F74 Not Used
   
  Nipmuc
F75 Hassanamisco Band of the Nipmuc Nation
F76 Chaubunagungamaug Nipmuck
D27 Nipmuc
   
  Nomlaki
F77 Nomlaki
F78 Paskenta Band of Nomlaki Indians
F79 Not Used
   
  Northwest Tribes
F80 Alsea
F81 Celilo
F82 Columbia
F83 Kalapuya
F84 Molalla
F85 Talakamish
F86 Tenino
F87 Tillamook
F88 Wenatchee
F89-F94 Not Used
   
  Omaha
F95 Omaha Tribe of Nebraska
F96-F98 Not Used
   
  Oneida Tribe
F99 Oneida Tribe of Indians of Wisconsin
   
  Oregon Athabascan
G01 Oregon Athabascan
G02-G03 Not Used
   
  Osage
G04 Osage Tribe, Oklahoma
G05-G09 Not Used
   
  Otoe-Missouria
G10 Otoe-Missouria Tribe of Indians
G11-G13 Not Used
   
  Ottawa
G14 Not Used
G15 Little River Band of Ottawa Indians of Michigan
G16 Ottawa Tribe of Oklahoma
G17 Ottawa
G18 Little Traverse Bay Bands of Odawa Indians
G19 Grand River Band of Ottawa Indians
G20-G22 Not Used
   
  Paiute
G23 Big Pine Paiute Tribe of the Owens Valley
G24 Bridgeport Paiute Indian Colony
G25 Burns Paiute Tribe
G26 Cedarville Rancheria
G27 Fort Bidwell Indian Community
G28 Fort Independence Indian Community
G29 Kaibab Band of Paiute Indians of the Kaibab Indian Reservation
G30 Las Vegas Tribe of Paiute Indians of the Las Vegas Indian Colony
G31 Not Used
G32 Lovelock Paiute Tribe of the Lovelock Indian Colony, Nevada
G33 Malheur Paiute
G34 Moapa Band of Paiute Indians of the Moapa River Indian Reservation, Nevada
G35 Northern Paiute
G36 Not Used
G37 Paiute
G38 Pyramid Lake Paiute Tribe of the Pyramid Lake Reservation, Nevada
G39 San Juan Southern Paiute Tribe of Arizona
G40 Paiute Indian Tribe of Utah (Southern Paiute)
G41 Summit Lake Paiute Tribe of Nevada
G42 Utu Utu Gwaitu Paiute Tribe of the Benton Paiute Reservation, California
G43 Walker River Paiute Tribe of the Walker River Reservation, Nevada
G44 Yerington Paiute Tribe of the Yerington Colony and Campbell Ranch, Nevada
G45 Yahooskin Band of Snake
G46 Not Used
G47 Susanville Indian Rancheria, California
G48 Winnemucca Indian Colony of Nevada
G49 Not Used
   
  Pamunkey
G50 Pamunkey Indian Tribe
G51-G52 Not Used
   
  Passamaquoddy
G53 Indian Township
G54 Passamaquoddy Tribe of Maine
G55 Pleasant Point Passamaquoddy
G56-G60 Not Used
   
  Pawnee
G61 Pawnee Nation of Oklahoma
G62 Pawnee
G63-G67 Not Used
   
  Penobscot
G68 Penobscot Tribe of Maine
G69-G71 Not Used
   
  Peoria
G72 Peoria Tribe of Indians of Oklahoma
G73 Peoria
G74-G76 Not Used
   
  Pequot
G77 Mashantucket Pequot Tribe of Connecticut
G78 Pequot
G79 Paucatuck Eastern Pequot
G80 Eastern Pequot
G81-G83 Not Used
   
  Pima
G84 Gila River Indian Community of the Gila River Indian Reservation
G85 Pima
G86 Salt River Pima-Maricopa Indian Community
G87 Peeposh
G88-G91 Not Used
   
  Piscataway
G92 Piscataway
G93-G95 Not Used
   
  Pit River
G96 Pit River Tribe of California
G97 Alturas Indian Rancheria
G98 Not Used
   
  Pomo
G99 Big Valley Band of Pomo Indians of the Big Valley Rancheria
H01 Central Pomo
H02 Dry Creek Rancheria of Pomo Indians
H03 Eastern Pomo
H04 Kashia Band of Pomo Indians of the Stewarts Point Rancheria
H05 Northern Pomo
H06 Pomo
H07 Scotts Valley Band of Pomo Indians of California
H08 Stonyford
H09 Elem Indian Colony of the Sulphur Bank Rancheria
H10 Sherwood Valley Rancheria of Pomo Indians of California
H11 Guidiville Rancheria of California
H12 Lytton Rancheria of California
H13 Cloverdale Rancheria of Pomo Indians of California
H14 Coyote Valley Band of Pomo Indians of California
H15-H20 (see under Ponca)
H21-H33 (see under Potawatomi)
H34-H37 (see under Powhatan)
H38-H65 (see under Pueblo)
H66 Hopland Band of Pomo Indians
H67 Manchester Band of Pomo Indians of the Manchester-Point Arena Rancheria
H68 Middletown Rancheria of Pomo Indians
H69 Pinoleville Pomo Nation
H70-H92 (see under Puget Sound Salish)
H93 Potter Valley Tribe
H94 Redwood Valley Rancheria of Pomo Indians
H95 Robinson Rancheria of Pomo Indians
H96 Habematolel Pomo of Upper Lake (Upper Lake Band of Pomo Indians of Upper Lake Rancheria)
H97 Federated Indians of Graton Rancheria
H98 Lower Lake Rancheria Koi Nation
   
  Ponca
H15 Ponca Tribe of Nebraska
H16 Ponca Tribe of Indians of Oklahoma
H17 Ponca
H18-H20 Not Used
   
  Potawatomi
H21 Citizen Potawatomi Nation, Oklahoma
H22 Forest County Potawatomi Community, Wisconsin
H23 Hannahville Potawatomi Indian Tribe, Michigan
H24 Nottawaseppi Huron Band of the Potawatomi, Michigan
H25 Pokagon Band of Potawatomi Indians
H26 Potawatomi
H27 Prairie Band of Potawatomi Nation, Kansas
H28 Wisconsin Potawatomi
H29 Match-e-be-nash-she-wish Band of Pottawatomi Indians
H30-H33 Not Used
   
  Powhatan
H34 Powhatan
H35-H37 Not Used
   
  Pueblo
H38 Pueblo of Acoma
H39 Not Used
H40 Pueblo of Cochiti
H41 Not Used
H42 Pueblo of Isleta
H43 Pueblo of Jemez
H44 Not Used
H45 Pueblo of Laguna
H46 Pueblo of Nambe
H47 Pueblo of Picuris
H48 Piro Manso Tiwa Tribe
H49 Pueblo of Pojoaque
H50 Pueblo
H51 Pueblo of San Felipe
H52 Pueblo of San Ildefonso
H53 Ohkay Owingeh, New Mexico
H54 Not Used
H55 San Juan
H56 Pueblo of Sandia
H57 Pueblo of Santa Ana
H58 Pueblo of Santa Clara
H59 Pueblo of Santo Domingo
H60 Pueblo of Taos
H61 Pueblo of Tesuque
H62 Not Used
H63 Ysleta Del Sur Pueblo of Texas
H64 Pueblo of Zia
H65 Zuni Tribe of the Zuni Reservation
H66-H69 (see under Pomo)
   
  Puget Sound Salish
H70 Marietta Band of Nooksack
H71 Duwamish
H72 Kikiallus
H73 Lower Skagit
H74 Muckleshoot Indian Tribe
H75 Nisqually Indian Tribe
H76 Nooksack Indian Tribe
H77 Not Used
H78 Puget Sound Salish
H79 Puyallup Tribe
H80 Samish Indian Tribe
H81 Sauk-Suiattle Indian Tribe
H82 Skokomish Indian Tribe of the Skokomish Indian Reservation, Washington
H83 Skykomish
H84 Snohomish
H85 Snoqualmie Tribe
H86 Squaxin Island Tribe of the Squaxin Island Reservation, Washington
H87 Steilacoom
H88 Stillaguamish
H89 The Suquamish Tribe
H90 Swinomish Indian Tribal Community
H91 Tulalip Tribes
H92 Upper Skagit Indian Tribe
H93-H98 (see under Pomo)
   
  Quapaw
H99 Quapaw Tribe of Indians, Oklahoma
I01-I99 Not Used
   
  Quinault
J01 Quinault Tribe
J02-J04 Not Used
   
  Rappahannock
J05 Rappahannock Indian Tribe
J06 Not Used
   
  Reno-Sparks
J07 Reno-Sparks Indian Colony, Nevada
J08-J13 Not Used
   
  Round Valley
J14 Round Valley Indian Tribes
J15-J18 Not Used
   
  Sac and Fox
J19 Sac and Fox Tribe of the Mississippi in Iowa
J20 Sac and Fox Nation of Missouri in Kansas and Nebraska
J21 Sac and Fox Nation, Oklahoma
J22 Sac and Fox
J23-J27 Not Used
   
  Salinan
J28 Salinan
J29-J30 Not Used
   
  Salish
J31 Salish
J32-J34 Not Used
   
  Salish and Kootenai
J35 Confederated Salish and Kootenai Tribes of the Flathead Nation
J36-J37 Not Used
   
  Saponi
J38 Saponi
   
  Schaghticoke
J39 Schaghticoke
J40-J46 Not Used
   
  Seminole
J47 Big Cypress Reservation
J48 Brighton Reservation
J49 Seminole Tribe of Florida
J50 Hollywood Reservation (Dania)
J51 Seminole Nation of Oklahoma
J52 Seminole
J53 Not Used
J54 Tampa Reservation
J55-J57 Not Used
   
  Serrano
J58 San Manuel Band of Serrano Mission Indians
J59 Serrano
J60-J61 Not Used
   
  Shasta
J62 Shasta
J63 Quartz Valley Indian Reservation
J64-J65 Not Used
   
  Shawnee
J66 Absentee Shawnee Tribe of Indians of Oklahoma
J67 Eastern Shawnee
J68 Shawnee
J69 Piqua Shawnee Tribe
J70 Shawnee Tribe, Oklahoma
J71 Shawnee Nation United Remnant Band
J72 East of the River Shawnee
J73 Not Used
   
  Shinnecock
J74 Shinnecock
J75-J77 Not Used
   
  Shoalwater Bay
J78 Shoalwater Bay Tribe of the Shoalwater Bay Reservation, Washington
J79-J80 Not Used
   
  Shoshone
J81 Duckwater Shoshone Tribe
J82 Ely Shoshone Tribe
J83 Confederated Tribes of the Goshute Reservation
J84 Not Used
J85 Shoshone
J86 Skull Valley Band of Goshute Indians of Utah
J87 Not Used
J88 Death Valley Timbi-Sha Shoshone
J89 Northwestern Band of Shoshone Nation of Utah (Washakie)
J90 Eastern Shoshone (Wind River)
J91 Yomba Shoshone Tribe of the Yomba Reservation, Nevada
J92 Not Used
   
  Te-Moak Tribes of Western Shoshone Indians of Nevada
J93 Te-Moak Tribes of Western Shoshone Indians of Nevada
J94 Battle Mountain Band
J95 Elko Band
J96 South Fork Band
J97 Wells Band
J98-J99 Not Used
   
  Paiute-Shoshone
K01 Shoshone-Paiute Tribes of the Duck Valley Reservation
K02 Paiute-Shoshone Tribe of the Fallon Reservation and Colony, Nevada
K03 Fort McDermitt Paiute and Shoshone Tribe of Nevada and Oregon
K04 Shoshone Paiute
K05 Bishop Paiute Tribe
K06 Lone Pine
K07-K09 Not Used
   
  Siletz
K10 Confederated Tribes of Siletz Indians of Oregon
K11-K15 Not Used
   
  Sioux
K16 Not Used
K17 Brule Sioux
K18 Cheyenne River Sioux Tribe of the Cheyenne River Reservation, South Dakota
K19 Crow Creek Sioux Tribe of the Crow Creek Reservation, South Dakota
K20 Dakota Sioux
K21 Flandreau Santee Sioux Tribe of South Dakota
K22-K23 Not Used
K24 Lower Brule Sioux Tribe of the Lower Brule Reservation, South Dakota
K25 Lower Sioux Indian Community in the State of Minnesota
K26 Mdewakanton Sioux
K27 Not Used
K28 Oglala Sioux Tribe of the Pine Ridge Reservation, South Dakota
K29 Not Used
K30 Pipestone Sioux
K31 Prairie Island Indian Community
K32 Shakopee Mdewakanton Sioux Community (Prior Lake)
K33 Rosebud Sioux Tribe of the Rosebud Indian Reservation, South Dakota
K34 Not Used
K35 Santee Sioux Nation, Nebraska
K36 Sioux
K37 Sisseton-Wahpeton Oyate of the Lake Traverse Reservation, South Dakota
K38 Not Used
K39 Spirit Lake Tribe
K40 Standing Rock Sioux Tribe
K41 Teton Sioux
K42 Not Used
K43 Upper Sioux Community
K44 Wahpekute Sioux
K45 Not Used
K46 Wazhaza Sioux
K47 Yankton Sioux Tribe of South Dakota
K48 Yanktonai Sioux
K49-K53 Not Used
   
  Siuslaw
K54 Siuslaw
K55-K58 Not Used
   
  Spokane
K59 Spokane Tribe
K60-K66 Not Used
   
  Stockbridge-Munsee
K67 Stockbridge-Munsee Community
K68-K76 Not Used
   
  Ak-Chin
K77 Ak-Chin Indian Community of the Maricopa Indian Reservation
   
  Tohono O'Odham
K78 Gila Bend
K79 San Xavier
K80 Sells
K81 Tohono O'Odham Nation of Arizona
K82-K86 Not Used
   
  Tolowa
K87 Tolowa
K88 Big Lagoon Rancheria
K89 Elk Valley Rancheria
A91 Smith River Rancheria
   
  Tonkawa
K90 Tonkawa Tribe of Indians of Oklahoma
K91-K93 Not Used
   
  Tygh
K94 Tygh
K95-K96 Not Used
   
  Umatilla
K97 Confederated Tribes of the Umatilla Indian Reservation
K98-K99 Not Used
   
  Umpqua
L01 Cow Creek Band of Umpqua Indians of Oregon
L02 Umpqua
L03-L05 Not Used
   
  Ute
L06 Not Used
L07 Ute Indian Tribe of the Uintah and Ouray Reservation, Utah
L08 Ute Mountain Ute Tribe
L09 Ute
L10 Southern Ute Indian Tribe of the Southern Ute Reservation
L11-L14 Not Used
   
  Wailaki
L15 Wailaki
L16-L18 Not Used
   
  Walla Walla
L19 Walla Walla
L20-L21 Not Used
   
  Wampanoag
L22 Wampanoag Tribe of Gay Head (Aquinnah)
L23 Mashpee Wampanoag Tribe
L24 Wampanoag
L25 Seaconeke Wampanoag
L26 Pocasset Wampanoag
L27 Herring Pond Wampanoag Tribe
L28 Pokanoket (Royal House of Pokanoket)
L29 Ponkapoag
L30 Chappaquiddick Tribe of the Wampanoag Indian Nation
L31 Assonet Band of the Wampanoag Nation
L32 Not Used
   
  Warm Springs
L33 Confederated Tribes of Warm Springs
   
  Wascopum
L34 Wascopum
L35-L37 Not Used
   
  Washoe
L38 Alpine
L39-L40 Not Used
L41 Washoe Tribe of Nevada and California
L42-L46 Not Used
   
  Wichita and Affiliated Tribes, Oklahoma
L47 Wichita
L48 Keechi
L49 Waco
L50 Tawakonie
L51 Not Used
   
  Wind River
L52 Wind River
L53-L54 Not Used
   
  Winnebago
L55 Not Used
L56 Winnebago Tribe of Nebraska
L57 Winnebago
L58-L65 Not Used
   
  Wintun
L66 Wintun
L67 Cachil Dehe Band of Wintun Indians of the Colusa Rancheria
L68 Cortina Indian Rancheria of Wintun Indians
L69 Rumsey Indian Rancheria of Wintun Indians
L70 Not Used
   
  Wintun-Wailaki
L71 Grindstone Indian Rancheria of Wintun-Wailaki Indians
   
  Wiyot
L72 Wiyot Tribe, California
L73 Not Used
L74 Blue Lake Rancheria
L75-L78 Not Used
   
  Yakama
L79 Confederated Tribes and Bands of the Yakama Nation
L80-L84 Not Used
   
  Yakama Cowlitz
L85 Yakama Cowlitz
L86-L90 Not Used
   
  Yaqui
L91 Not Used
L92 Pascua Yaqui Tribe of Arizona
L93 Yaqui
L94-L99 Not Used
   
  Yavapai Apache
M01 Yavapai Apache Nation of the Camp Verde Indian Reservation
M02-M06 Not Used
   
  Yokuts
M07 Picayune Rancheria of Chukchansi Indians
M08 Tachi
M09 Tule River Indian Tribe
M10 Yokuts
M11 Table Mountain Rancheria
M12-M15 Not Used
   
  Yuchi
M16 Yuchi
M17 Tla
M18 Tla Wilano
M19 Ani-stohini/Unami
M20-M21 Not Used
   
  Yuman
M22 Cocopah Tribe of Arizona
M23 Havasupai Tribe of the Havasupai Reservation
M24 Hualapai Indian Tribe of the Hualapai Indian Reservation
M25 Maricopa
M26 Fort Mojave Indian Tribe of Arizona, California, and Nevada
M27 Quechan Tribe of the Fort Yuma Indian Reservation
M28 Yavapai-Prescott Tribe of the Yavapai Reservation
M29-M33 Not Used
   
  Yurok
M34 Resighini Rancheria
M35 Yurok Tribe
M36-M38 Not Used
   
M39 Multiple AMERICAN INDIAN and ALASKA NATIVE responses
M40 Multiple AMERICAN INDIAN responses
   
  Tribe Not Specified
M41 American Indian
M42 Tribal responses, not elsewhere classified
M43 Not Used
 
 
                              ALASKA NATIVE
  Alaska Native Not Specified
M44 Alaska Indian
M45-M46 Not Used
M47 Alaska Native
M48-M51 Not Used
   
  Alaskan Athabascan
M52 Ahtna, Inc Corporation
M53 Alaskan Athabascan
M54 Alatna Village
M55 Alexander
M56 Allakaket Village
M57 Alanvik
M58 Anvik Village
M59 Arctic Village
M60 Beaver Village
M61 Birch Creek Tribe
M62 Native Village of Cantwell
M63 Chalkyitsik Village
M64 Chickaloon Native Village
M65 Cheesh-Na Tribe (Chistochina)
M66 Native Village of Chitina
M67 Circle Native Community
M68 Cook Inlet
M69 Not Used
M70 Copper River
M71 Village of Dot Lake
M72 Doyon
M73 Native Village of Eagle
M74 Eklutna Native Village
M75 Evansville Village (Bettles Field)
M76 Native Village of Fort Yukon
M77 Native Village of Gakona
M78 Galena Village (Louden Village)
M79 Organized Village of Grayling (Holikachuk)
M80 Gulkana Village
M81 Healy Lake Village
M82 Holy Cross Village
M83 Hughes Village
M84 Huslia Village
M85 Village of Iliamna
M86 Village of Kaltag
M87 Native Village of Kluti Kaah (Copper Center)
M88 Knik Tribe
M89 Koyukuk Native Village
M90 Lake Minchumina
M91 Lime Village
M92 McGrath Native Village
M93 Manley Village Council (Manley Hot Springs)
M94 Mentasta Traditional Council
M95 Native Village of Minto
M96 Nenana Native Association
M97 Nikolai Village
M98 Ninilchik Village Traditional Council
M99 Nondalton Village
N01 Northway Village
N02 Nulato Village
N03 Pedro Bay Village
N04 Rampart Village
N05 Native Village of Ruby
N06 Village of Salamatoff
N07 Seldovia Village Tribe
N08 Slana
N09 Shageluk Native Village
N10 Native Village of Stevens
N11 Village of Stony River
N12 Takotna Village
N13 Native Village of Tanacross
N14 Not Used
N15 Native Village of Tanana
N16 Tanana Chiefs
N17 Native Village of Tazlina
N18 Telida Village
N19 Native Village of Tetlin
N20 Tok
N21 Native Village of Tyonek
N22 Village of Venetie
N23 Wiseman
N24 Kenaitze Indian Tribe
N25-N27 Not Used
   
  Tlingit-Haida
N28 Angoon Community Association
N29 Central Council of the Tlingit and Haida Indian Tribes
N30 Chilkat Indian Village (Klukwan)
N31 Chilkoot Indian Association (Haines)
N32 Craig Community Association
N33 Douglas Indian Association
N34 Haida
N35 Hoonah Indian Association
N36 Hydaburg Cooperative Association
N37 Organized Village of Kake
N38 Organized Village of Kasaan
N39 Not Used
N40 Ketchikan Indian Corporation
N41 Klawock Cooperative Association
N42 Not Used
N43 Pelican
N44 Petersburg Indian Association
N45 Organized Village of Saxman
N46 Sitka Tribe of Alaska
N47 Tenakee Springs
N48 Tlingit
N49 Wrangell Cooperative Association
N50 Yakutat Tlingit Tribe
N51-N55 Not Used
N56-N58 (see under Tsimshian)
N59 Not Used
N60 Sealaska Corporation (Southeast Alaska)
N61-N64 Not Used
N65 Skagway Village
N66 Not Used
   
  Tsimshian
N56 Metlakatla Indian Community, Annette Island Reserve
N57 Tsimshian
N58 Not Used
   
  Inupiat
N67 American Eskimo
N68 Eskimo
N69 Greenland Eskimo
N70-N74 Not Used
N75 Inuit
N76-N78 Not Used
N79 Native Village of Ambler
N80 Not Used
N81 Village of Anaktuvuk Pass
N82 Inupiat Community of the Arctic Slope
N83 Arctic Slope Corporation
N84 Atqasuk Village (Atkasook)
N85 Native Village of Barrow Inupiat Traditional Government
N86 Bering Straits Inupiat
N87 Native Village of Brevig Mission
N88 Native Village of Buckland
N89 Chinik Eskimo Community (Golovin)
N90 Native Village of Council
N91 Native Village of Deering
N92 Native Village of Elim
N93 Not Used
N94 Native Village of Diomede (Inalik)
N95 Not Used
N96 Inupiat (Inupiaq)
N97 Kaktovik Village (Barter Island)
N98 Kawerak
N99 Native Village of Kiana
O01-O99 Not Used
P01 Native Village of Kivalina
P02 Native Village of Kobuk
P03 Native Village of Kotzebue
P04 Native Village of Koyuk
P05-P06 Not Used
P07 Nana Inupiat
P08 Native Village of Noatak
P09 Nome Eskimo Community
P10 Noorvik Native Community
P11 Native Village of Nuiqsut (Nooiksut)
P12 Native Village of Point Hope
P13 Native Village of Point Lay
P14 Native Village of Selawik
P15 Native Village of Shaktoolik
P16 Native Village of Shishmaref
P17 Native Village of Shungnak
P18 Village of Solomon
P19 Native Village of Teller
P20 Native Village of Unalakleet
P21 Village of Wainwright
P22 Native Village of Wales
P23 Native Village of White Mountain
P24 Not Used
P25 Native Village of Mary's Igloo
P26 King Island Native Community
P27-P29 Not Used
P30-P32 (see under Yup'ik)
P33-P35 Not Used
P36 Chevak Native Village
P37 Native Village of Mekoryuk
   
  Yup'ik
P30 Native Village of Gambell
P31 Native Village of Savoonga
P32 Siberian Yupik
P33-P37 (see under Inupiat)
P38 Akiachak Native Community
P39 Akiak Native Community
P40 Village of Alakanuk
P41 Native Village of Aleknagik
P42 Yupiit of Andreafski
P43 Village of Aniak
P44 Village of Atmautluak
P45 Orutsararmiut Native Village (Bethel)
P46 Village of Bill Moore's Slough
P47 Bristol Bay
P48 Calista
P49 Village of Chefornak
P50 Native Village of Hamilton
P51 Native Village of Chuathbaluk
P52 Village of Clark's Point
P53 Village of Crooked Creek
P54 Curyung Tribal Council (Native Village of Dillingham)
P55 Native Village of Eek
P56 Native Village of Ekuk
P57 Ekwok Village
P58 Emmonak Village
P59 Native Village of Goodnews Bay
P60 Native Village of Hooper Bay (Naparagamiut)
P61 Iqurmuit Traditional Council
P62 Village of Kalskag
P63 Native Village of Kasigluk
P64 Native Village of Kipnuk
P65 New Koliganek Village Council
P66 Native Village of Kongiganak
P67 Village of Kotlik
P68 Organized Village of Kwethluk
P69 Native Village of Kwigillingok
P70 Levelock Village
P71 Village of Lower Kalskag
P72 Manokotak Village
P73 Native Village of Marshall (Fortuna Ledge)
P74 Village of Ohogamiut
P75 Asa'carsarmiut Tribe
P76 Naknek Native Village
P77 Native Village of Napaimute
P78 Native Village of Napakiak
P79 Native Village of Napaskiak
P80 Newhalen Village
P81 New Stuyahok Village
P82 Newtok Village
P83 Native Village of Nightmute
P84 Native Village of Nunapitchuk
P85 Oscarville Traditional Village
P86 Pilot Station Traditional Village
P87 Native Village of Pitka's Point
P88 Platinum Traditional Village
P89 Portage Creek Village (Ohgsenakale)
P90 Native Village of Kwinhagak
P91 Village of Red Devil
P92 Native Village of Saint Michael
P93 Native Village of Scammon Bay
P94 Native Village of Nunam Iqua (Sheldon's Point)
P95 Village of Sleetmute
P96 Stebbins Community Association
P97 Traditional Village of Togiak
P98 Nunakauyarmiut Tribe (Toksook Bay)
P99 Tuluksak Native Community
Q01-Q99 Not Used
R01 Native Village of Tuntutuliak
R02 Native Village of Tununak
R03 Twin Hills Village
R04 Yup'ik (Yup'ik Eskimo)
R05 Not Used
R06 Native Village of Georgetown
R07 Algaaciq Native Village (St Mary's)
R08 Umkumiute Native Village
R09 Chuloonawick Native Village
R10 Not Used
   
  Aleut
R11 Aleut
R12-R15 Not Used
R16 Alutiiq
R17 Native Village of Afognak
R18-R22 Not Used
R23 Native Village of Tatitlek
R24 Ugashik Village
R25-R27 Not Used
R28 Bristol Bay Aleut
R29 Chignik Bay Tribal Council (Native Village of Chignik)
R30 Chignik Lake Village
R31 Egegik Village
R32 Igiugig Village
R33 Ivanoff Bay Village
R34 King Salmon Tribe
R35 Kokhanok Village
R36 Native Village of Perryville
R37 Native Village of Pilot Point
R38 Native Village of Port Heiden
R39-R42 Not Used
R43 Native Village of Chanega (Chenega)
R44 Chugach Aleut
R45 Chugach Corporation
R46 Native Village of Nanwalek (English Bay)
R47 Native Village of Port Graham
R48-R50 Not Used
R51 Native Village of Eyak (Cordova)
R52-R54 Not Used
R55 Native Village of Akhiok
R56 Agdaagux Tribe of King Cove
R57 Native Village of Karluk
R58 Native Village of Kanatak
R59 Kodiak
R60 Koniag Aleut
R61 Native Village of Larsen Bay
R62 Village of Old Harbor
R63 Native Village of Ouzinkie
   
  Aleut
R64 Native Village of Port Lions
R65 Lesnoi Village (Woody Island)
R66 Sun'aq Tribe of Kodiak
R67 Sugpiaq
R68-R74 Not Used
R75 Native Village of Akutan
R76 Aleut Corporation
R77-R78 Not Used
R79 Native Village of Atka
R80 Native Village of Belkofski
R81 Native Village of Chignik Lagoon
R82 King Cove
R83 Native Village of False Pass
R84 Native Village of Nelson Lagoon
R85 Native Village of Nikolski
R86 Pauloff Harbor Village
R87 Qagan Tayagungin Tribe of Sand Point Village
R88 Qawalangin Tribe of Unalaska
R89 Saint George Island
R90 Saint Paul Island
R91 Not Used
R92 South Naknek Village
R93 Unangan (Unalaska)
R94 Not Used
R95 Native Village of Unga
R96 Kaguyak Village
R97-R98 Not Used
R99 Multiple ALASKA NATIVE responses
   
S01-S99 Not Used
 
                               CANADIAN AND LATIN AMERICAN INDIAN
 
  Canadian and French American Indian
T01 Canadian Indian
T02 French Canadian/French American Indian
T03 Abenaki Canadian
T04 Acadia Band
T05 Ache Dene Koe
T06 Ahousaht
T07 Alderville First Nation
T08 Alexandria Band
T09 Algonquins of Barriere Lake
T10 Batchewana First Nation
T11 Beardys and Okemasis Band
T12 Beausoleil
T13 Beecher Bay
T14 Beothuk
T15 Bella Coola (Nuxalk Nation)
T16 Big Cove
T17 Big Grassy
T18 Bigstone Cree Nation
T19 Bonaparte Band
T20 Boston Bar First Nation
T21 Bridge River
T22 Brokenhead Ojibway Nation
T23 Buffalo Point Band
T24 Caldwell
T25 Campbell River Band
T26 Cape Mudge Band
T27 Carcross/Tagish First Nation
T28 Caribou
T29 Carrier Nation
T30 Carry the Kettle Band
T31 Cheam Band
T32 Chemainus First Nation
T33 Chilcotin Nation
T34 Chippewa/Ojibwe Canadian
T35 Chippewa of Sarnia
T36 Chippewa of the Thames
T37 Clayoquot
T38 Cold Lake First Nations
T39 Coldwater Band
T40 Comox Band
T41 Coquitlam Band
T42 Cote First Nation
T43 Couchiching First Nation
T44 Cowessess Band
T45 Cowichan
T46 Cree Canadian
T47 Cross Lake First Nation
T48 Curve Lake Band
T49 Dene Canadian
T50 Dene Band Nwt (Nw Terr)
T51 Ditidaht Band
T52 Dogrib
T53 Eagle Lake Band
T54 Eastern Cree
T55 Ebb and Flow Band
T56 English River First Nation
T57 Eskasoni
T58 Esquimalt
T59 Fisher River
T60 Five Nations
T61 Fort Alexander Band
T62 Garden River Nation
T63 Gibson Band
T64 Gitksan
T65 Gitlakdamix Band
T66 Grassy Narrows First Nation
T67 Gull Bay Band
T68 Gwichya Gwich'in
T69 Heiltsuk Band
T70 Hesquiaht Band
T71 Hiawatha First Nation
T72 Hope Band (Chawathill Nation)
T73 Huron
T74 Huron of Lorretteville
T75 Innu (Montagnais)
T76 Interior Salish
T77 James Bay Cree
T78 James Smith Cree Nation
T79 Kahkewistahaw First Nation
T80 Kamloops Band
T81 Kanaka Bar
T82 Kanesatake Band
T83 Kaska Dena
T84 Keeseekoose Band
T85 Kincolith Band
T86 Kingsclear Band
T87 Kitamaat
T88 Kitigan Zibi Anishinabeg
T89 Klahoose First Nation
T90 Kwakiutl
T91 Kyuquot Band
T92 Lakahahmen Band
T93 Lake Manitoba Band
T94 Lake St Martin Band
T95 Lennox Island Band
T96 Liard River First Nation
T97 Lillooet
T98 Little Shuswap Band
T99 Long Plain First Nation
U01 Lower Nicola Indian Band
U02 Malahat First Nation
U03 Matachewan Band
U04 Mcleod Lake
U05 Metis
U06 Millbrook First Nation
U07 Mississaugas of the Credit
U08 Mohawk Bay of Quinte
U09 Mohawk Canadian
U10 Mohawk Kahnawake
U11 Mohican Canadian
U12 Musqueam Band
U13 Namgis First Nation (Nimpkish)
U14 Nanaimo (Snuneymuxw)
U15 Nanoose First Nation
U16 Naskapi
U17 Nation Huronne Wendat
U18 Nipissing First Nation
U19 North Thompson Band (Simpcw First Nation)
U20 N'Quatqua (Anderson Lake)
U21 Nuu-chah-nulth (Nootka)
U22 Odanak
U23 Ohiaht Band
U24 Oneida Nation of the Thames
U25 Opaskwayak Cree Nation
U26 Osoyoos Band
U27 Pacheedaht First Nation
U28 Pauquachin
U29 Peepeekisis
U30 Peguis
U31 Penelakut
U32 Penticton
U33 Pine Creek
U34 Plains Cree
U35 Rainy River First Nations
U36 Red Earth Band
U37 Restigouche (Listugaj First Nation)
U38 Roseau River
U39 Saddle Lake
U40 Sakimay First Nations
U41 Sandy Bay Band
U42 Sarcee (Sarci)
U43 Saugeen
U44 Saulteau First Nations
U45 Saulteaux
U46 Seabird Island
U47 Sechelt
U48 Seine River First Nation
U49 Serpent River
U50 Seton Lake
U51 Shoal Lake Cree Nation
U52 Shuswap
U53 Similkameen
U54 Siksika Canadian
U55 Six Nation Canadian
U56 Six Nations of the Grand River
U57 Skawahlook First Nation
U58 Skeetchestn Indian Band
U59 Skookum Chuck Band
U60 Skowkale
U61 Skuppah
U62 Skwah First Nation
U63 Skway First Nation
U64 Songhees First Nation
U65 Soowahlie First Nation
U66 Spuzzum First Nation
U67 Squamish Nation
U68 Stanjikoming First Nation
U69 Sto:lo Nation
U70 Stone
U71 Sucker Creek First Nation
U72 Swampy Cree
U73 Tahltan
U74 Taku River Tlingit
U75 Tete De Boule (Attikamek)
U76 Thompson
U77 Tobacco Plains Band
U78 Tobique First Nation
U79 Toquaht
U80 Tsartlip
U81 Tsawout First Nation
U82 Tseycum
U83 Uchucklesaht
U84 Ucluelet First Nation
U85 Vuntut Gwitchin First Nation
U86 Wabauskang First Nation
U87 Walpole Island
U88 Wasauksing First Nation
U89 Waywayseecappo First Nation
U90 West Bay Band
U91 White Bear Band
U92 Whitefish Lake Band
U93 Wikwemikong
U94 Wolf Lake Band
U95 Woodland Cree First Nation
U96 Woodstock First Nation
U97 Xaxli'p First Nation (Fountain Band)
U98 Canadian Indian, not elsewhere classified
U99-V23 Not Used
   
  Central American Indian
V24 Central American Indian
V25 Cakchiquel
V26 Carib
V27 Choco
V28 Garifuna
V29 Guaymi
V30 Kanjobal
V31 Kekchi
V32 Kuna Indian
V33 Lenca
V34 Maya Central American
V35 Miskito
V36 Pipil
V37 Quiche
V38 Rama
V39 Sumo
V40 Belize Indian
V41 Costa Rica Indian
V42 Dominican Indian
V43 El Salvador Indian
V44 Guatemala Indian
V45 Honduras Indian
V46 Nicaragua Indian
V47 Panama Indian
V48 Puerto Rican Indian
V49-V83 Not Used
   
  Mexican American Indian
V84 Mexican American Indian
V85 Amuzgo
V86 Auraca
V87 Aztec
V88 Chatino
V89 Chinantec
V90 Chocho
V91 Concho
V92 Cora
V93 Couhimi
V94 Cuicatec
V95 Huastec
V96 Huave
V97 Huichol
V98 Ixacatec
V99 Lacandon
W01 Lagunero
W02 Maya
W03 Mazahua
W04 Mazatec
W05 Mixe
W06 Mixtec
W07 Nahuatl
W08 Olmec
W09 Opata
W10 Otomi
W11 Popoluca
W12 Seri
W13 Tarahumara (Raramuri)
W14 Tarasco (Purepecha)
W15 Tepehua
W16 Tequistlatec
W17 Tlapanec
W18 Tojolabal
W19 Toltec
W20 Triqui (Trique)
W21 Tzeltal
W22 Tzotzil
W23 Yucatan
W24 Zacateco
W25 Zapotec
W26 Zoque
W27 Mexican American Indian, not elsewhere classified
W28-W66 Not Used
   
  South American Indian
W67 South American Indian
W68 Ache Indian
W69 Amazon Indian
W70 Andean Indian
W71 Mapuche (Araucanian)
W72 Arawak
W73 Aymara
W74 Canela
W75 Guarani
W76 Inca
W77 Maya South American
W78 Quechua
W79 Quichua
W80 Taino
W81 Tehuelche
W82 Tupi
W83 Zaporo
W84 Argentinean Indian
W85 Bolivian Indian
W86 Brazilian Indian
W87 Chilean Indian
W88 Colombian Indian
W89 Ecuadorian Indian
W90 Guyanese South American Indian
W91 Paraguayan Indian
W92 Peruvian Indian
W93 Not Used
W94 Uruguayan Indian
W95 Venezuelan Indian
W96 South American Indian, not elsewhere classified
W97-X24 Not Used
   
  Spanish American Indian
X25 Spanish American Indian
X26-Z99 Not Used
 
 
400-499 ASIAN
   
400 Asian Indian (Checkbox)
401 Asian Indian
402 Bangladeshi
403 Bhutanese
404 Burmese
405 Cambodian
406-409 Not Used
   
410 Chinese (Checkbox)
411 Chinese
412 Taiwanese
413-419 Not Used
420 Filipino (Checkbox)
421 Filipino
422 Hmong
423 Indonesian
424-429 Not Used
   
430 Japanese (Checkbox)
431 Japanese
432-439 Not Used
   
440 Korean (Checkbox)
441 Korean
442 Laotian
443 Malaysian
444 Okinawan
445 Pakistani
446 Sri Lankan
447 Thai
448-449 Not Used
   
450 Vietnamese (Checkbox)
451 Vietnamese
452-459 Not Used
460 Other Asian (Checkbox)
461 Not Used
462 Asian
463 Asiatic
464 Not Used
465 Mongolian
466 Oriental
467 Whello
468 Yellow
469 Indo-Chinese
470 Iwo Jiman
471 Maldivian
472 Nepalese
473 Singaporean
474-479 Not Used
480 Multiple ASIAN responses
481-499 Not Used
 
 
500-599 NATIVE HAWAIIAN AND OTHER PACIFIC ISLANDER
   
  Polynesian
500 Native Hawaiian (Checkbox)
501 Native Hawaiian
502 Hawaiian
503 Part Hawaiian
504-509 Not Used
510 Samoan (Checkbox)
511 Samoan
512 Tahitian
513 Tongan
514 Polynesian
515 Tokelauan
516-519 Not Used
   
  Micronesian
520 Guamanian or Chamorro (Checkbox)
521 Guamanian
522 Chamorro
523-529 Not Used
530 (see under Other Pacific Islander)
531 Mariana Islander
532 Marshallese
533 Palauan
534 Carolinian
535 Kosraean
536 Micronesian
537 Pohnpeian
538 Saipanese
539 I-Kiribati
540 Chuukese
541 Yapese
   
  Melanesian
542 Fijian
543 Melanesian
544 Papua New Guinean
545 Solomon Islander
546 Ni-Vanuatu (New Hebrides Islander)
   
  Other Pacific Islander
530 Other Pacific Islander (Checkbox)
547 Pacific Islander
548-549 Not Used
550 Multiple NATIVE HAWAIIAN and OTHER PACIFIC ISLANDER responses
551-599 Not Used
 
 
600-999 SOME OTHER RACE
   
600 Some Other Race (Checkbox)
601 Argentinean
602 Bolivian
603 Californio
604 Central American
605 Chicano
606 Chilean
607 Colombian
608 Costa Rican
609 Cuban
610 Ecuadorian
611 Salvadoran
612 Guatemalan
613 Hispanic
614 Honduran
615 Latin American
616 Mestizo
617 Mexican
618 Nicaraguan
619 Panamanian
620 Paraguayan
621 Peruvian
622 Puerto Rican
623 Morena
624 South American
625 Spanish
626 Spanish-American
627 Sudamericano
628 Uruguayan
629 Venezuelan
630 Spaniard
631 Tejano
632 Cayman Islander
633-639 Not Used
640 Dominican/Dominican Republic
641 Not Used
642 Belizean
643 Bermudan
644 Aruba Islander
645 Not Used
646 Guyanese
647 Surinamer
648 Sudanese
649 Amerasian
650 Eurasian
651 Brazilian
652 Brown
653 Bushwacker
654 Not Used
655 Cape Verdean
656 Chocolate
657 Coe Clan
658 Coffee
659 Cosmopolitan
660 Issues
661 Jackson White
662 Melungeon
663 Mixed
664 Ramp
665 Wesort
666 Mulatto
667 Moor
668 Biracial
669 Creole
670 Indian
671 Turk
672 Half-Breed
673 Rainbow
674 Octoroon
675 Quadroon
676 Multiracial
677 Interracial
678 Multiethnic
679 Multinational
680-689 Not Used
690 Multiple SOME OTHER RACE responses
691-698 Not Used
699 Other race, not elsewhere classified
700-999 Not Used


2008-2012 Subject Definitions
General Information
Contact List: To obtain additional information on these and other American Community Survey (ACS) subjects, see the list of Census 2000/2010 Contacts on the Internet at http://www.census.gov/contacts/www/c-census2000.html.

Scope: These definitions apply to the data collected in both the United States and Puerto Rico. The text specifically notes any differences. References about comparability to the previous ACS years refer only to the ACS in the United States. Beginning in 2006, the population in group quarters is included in the data tabulations.

Historical census comparability: For additional information about the data in previous decennial censuses, see http://www.census.gov/prod/www/decennial.html.

Weighting Methodology: The weighting methodology in the 2006 ACS was modified in order to ensure consistent estimates of occupied housing units, households, and householders. For more information on the 2006 weighting methodology changes, see "User Notes" on the ACS website (http://www.census.gov/acs). There were no significant changes to the 2007 or 2008 weighting methodology. Beginning in 2009, the weighting methodology has changed to include the use of controls for total population for incorporated places and minor civil divisions.

For subject definitions from previous years, visit http://www.census.gov/acs.


Living Quarters
Living quarters are classified as either housing units or group quarters. Living quarters are usually found in structures intended for residential use, but also may be found in structures intended for nonresidential use as well as in places such as tents, vans, and emergency and transitional shelters.

Housing Unit
A housing unit may be a house, an apartment, a mobile home, a group of rooms or a single room that is occupied (or, if vacant, intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other individuals in the building and which have direct access from outside the building or through a common hall. For vacant units, the criteria of separateness and direct access are applied to the intended occupants whenever possible. If that information cannot be obtained, the criteria are applied to the previous occupants.

Both occupied and vacant housing units are included in the housing unit inventory. Boats, recreational vehicles (RVs), vans, tents, railroad cars, and the like are included only if they are occupied as someone's current place of residence. Vacant mobile homes are included provided they are intended for occupancy on the site where they stand. Vacant mobile homes on dealers' sales lots, at the factory, or in storage yards are excluded from the housing inventory. Also excluded from the housing inventory are quarters being used entirely for nonresidential purposes, such as a store or an office, or quarters used for the storage of business supplies or inventory, machinery, or agricultural products.

Occupied Housing Unit
A housing unit is classified as occupied if it is the current place of residence of the person or group of people living in it at the time of interview, or if the occupants are only temporarily absent from the residence for two months or less, that is, away on vacation or a business trip. If all the people staying in the unit at the time of the interview are staying there for two months or less, the unit is considered to be temporarily occupied and classified as "vacant." The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living quarters. The living quarters occupied by staff personnel within any group quarters are separate housing units if they satisfy the housing unit criteria of separateness and direct access; otherwise, they are considered group quarters.

Occupied rooms or suites of rooms in hotels, motels, and similar places are classified as housing units only when occupied by permanent residents, that is, people who consider the hotel as their current place of residence or have no current place of residence elsewhere. If any of the occupants in rooming or boarding houses, congregate housing, or continuing care facilities live separately from others in the building and have direct access, their quarters are classified as separate housing units.

Vacant Housing Unit
A housing unit is vacant if no one is living in it at the time of interview. Units occupied at the time of interview entirely by persons who are staying two months or less and who have a more permanent residence elsewhere are considered to be temporarily occupied, and are classified as "vacant."

New units not yet occupied are classified as vacant housing units if construction has reached a point where all exterior windows and doors are installed and final usable floors are in place. Vacant units are excluded from the housing inventory if they are open to the elements, that is, the roof, walls, windows, and/or doors no longer protect the interior from the elements. Also, excluded are vacant units with a sign that they are condemned or they are to be demolished.

Group Quarters
Group Quarters (GQs) are places where people live or stay, in a group living arrangement that is owned or managed by an entity or organization providing housing and/or services for the residents. These services may include custodial or medical care, as well as other types of assistance, and residency is commonly restricted to those receiving these services. People living in GQs usually are not related to each other. GQs include such places as college residence halls, residential treatment centers, skilled nursing facilities, group homes, military barracks, correctional facilities, workers' dormitories, and facilities for people experiencing homelessness. GQs are defined according to the housing and/or services provided to residents, and are identified by Census GQ type codes.

In January 2006, the American Community Survey (ACS) was expanded to include the population living in GQ facilities. The ACS GQ sample encompasses 12 independent samples; like the housing unit (HU) sample, a new GQ sample is introduced each month. The GQ data collection lasts only 6 weeks and does not include a formal nonresponse follow- up operation. The GQ data collection operation is conducted in two phases. First, U.S. Census Bureau Field Representatives (FRs) conduct interviews with the GQ facility contact person or administrator of the selected GQ (GQ level), and second, the FR conducts interviews with a sample of individuals from the facility (person level).

The GQ-level data collection instrument is an automated Group Quarters Facility Questionnaire (GQFQ). Information collected by the FR using the GQFQ during the GQ- level interview is used to determine or verify the type of facility, population size, and the sample of individuals to be interviewed. FRs conduct GQ-level data collection at approximately 20,000 individual GQ facilities each year.

A list of the GQ facilities (and their respective type codes) that is in scope for the 2012 ACS can be found in the 2012 Code List on the ACS website (http://www.census.gov/acs).

Question/Concept History - Though the American Community Survey (ACS) was expanded to include the population living in GQ facilities in 2006, the ACS began field testing early. The pretest in 2001 prevented the ACS from going into 2006 without determining whether or not the new processes, type codes, and procedures would produce the desired outcome for the ACS GQ data collection operation.

In 2001, the ACS GQ operational staff and other ACS staff implemented a number of changes in the GQ operation, the greatest of which was developing an automated Group Quarters Facility Questionnaire (GQFQ). The staff developed the GQFQ based on the decennial Other Living Quarters (OLQ) questionnaire used in the 2004 Census test. However, in order to make that questionnaire script fit with the ACS operation, the developers made some modifications, such as dropping the listing component, and adding the ability to capture multiple GQ types within the special place or GQ sampled.

Along with the introduction of an automated GQFQ, the ACS made the decision to use the revised GQ definitions planned for 2010 Census, even though the definitions of GQ types were still evolving. The pretest used a draft version of the GQ definitions that existed at the end of November 2004. Since these definitions will continue to evolve over the next several years, the ACS needed a GQFQ that could easily adopt future revisions to the definitions. Thus, the developers designed a flexible GQFQ. It was through this flexibility that group quarter types have been able to be added or dropped (e.g. YMCA/YWCA and hostels).

Comparability - The total group quarters population in the ACS may not be comparable with 2010 Census because there are some 2010 Census GQ types that were out of scope in the ACS such as domestic violence shelters, soup kitchens, regularly scheduled mobile food vans, targeted non-sheltered outdoor locations, crews of maritime vessels and living quarters for victims of natural disasters. The exclusion of these GQ types from the ACS may result in a small bias in some ACS estimates to the extent that the excluded population is different from the included population. Furthermore, only a sample of GQ facilities throughout the United States and Puerto Rico are selected for the ACS. ACS controls the GQ sample at the state level only. Therefore, for lower levels of geography, particularly when there are relatively few GQs in a geographic area, the ACS estimate of the GQ population may vary from the estimate from 2010 Census.

When comparing the 2012 ACS data with 2008 ACS, data the data should be compared with caution at the National and State levels. It should not be compared below the State level because the weighting for the group quarters (GQ) population is not controlled below the state level. Because of this users may observe greater fluctuations in year-to-year ACS estimates of the GQ population at sub-state levels than at state levels. The causes of these fluctuations typically are the result of either GQs that have closed or where the current population of the GQ is significantly different than the expected population as reflected on the sampling frame. Substantial changes in the ACS GQ estimates can impact ACS estimates of total population characteristics for areas where either the GQ population is a substantial proportion of the total population or where the GQ population may have very different characteristics than the total population as a whole. Users can assess the impact that year-to- year changes in sub-state GQ total population estimates have on the changes in total ACS population estimates by accessing Table B26001 on American Fact Finder. Users should also use their local knowledge to help determine whether the year-to-year change in the ACS estimate represents a real change in the GQ population or may be the result of the lack of adequate population controls for sub-state areas.

When comparing ACS GQ data across the years that group quarters data have been collected, it must be noted that beginning in 2008 military transient quarters, YMCA / YWCA and hostels were no longer in scope. These data were collected in 2006 and 2007.

A complete list and definitions of the GQs that have been included in the ACS can be found in the 2012 Code List on the ACS website (http://www.census.gov/acs).

Housing Variables
Acreage (Cuerda)
The data on acreage were obtained from Housing Question 4 in the 2012 American Community Survey. This question was asked at occupied and vacant one-family houses and mobile homes. The data for vacant units were obtained by asking a neighbor, real estate agent, building manager, or anyone else who had knowledge of the vacant unit in question.
This question determines a range of acres (cuerdas) on which the house or mobile home is located. A major purpose for this question, in conjunction with Housing Question 5 on agricultural sales, is to identify farm units. In previous American Community Surveys and in the Census 2000, this question was used to determine single-family homes on 10 or more acres (cuerdas). The land may consist of more than one tract or plot. These tracts or plots are usually adjoining; however, they may be separated by a road, creek, another piece of land, etc.
In the American Community Surveys prior to 2004 and in Census 2000, acreage was one of the variables used to determine specified owner- and renter-occupied housing units.

Question/Concept History - The 1996-1998 question asked, "Is this house or mobile home on less than 1 acre, 1 to less than 10 acres, or 10 or more acres." Since 1999, the question wording was changed to ask, "How many acres is this house or mobile home on?" and the second response category was modified to "1 to 9.9 acres."

Comparability - Data on acreage in the 2012 American Community Survey can be compared to previous ACS and Census 2000 acreage data.

Agricultural Sales
Data on the sales of agricultural crops were obtained from Housing Question 5 in the 2012 American Community Survey. The question was asked at occupied one-family houses and mobile homes located on lots of 1 or more acres. Data for this question exclude units on lots of less than 1 acre, units located in structures containing two or more units, and all vacant units. This question refers to the total amount (before taxes and expenses) received in the 12 months prior to the interview, from the sale of crops, vegetables, fruits, nuts, livestock and livestock products, and nursery and forest products, produced on "this property." Respondents new to a unit were to estimate total agricultural sales from the 12 months prior to the interview even if some portion of the sales had been made by previous occupants of the unit.

This question is used mainly to classify housing units as farm or nonfarm residences, not to provide detailed information on the sale of agricultural products. Detailed information on the sale of agricultural products is provided by the Census of Agriculture, which is conducted by the U.S. Department of Agriculture/National Agricultural Statistics Service (see http://www.agcensus.usda.gov/).

Question/Concept History - On the 1996-1998 American Community Survey questionnaires, there were just two response categories to indicate whether or not the amount of sales was over $1,000. Since 1999, the question has included a series of response categories for the amount of the agricultural sales.

Comparability - Data on agricultural sales in the 2012 American Community Survey can be compared to previous ACS and Census 2000 agricultural sales data.

Bedrooms
The data on bedrooms were obtained from Housing Question 7b in the 2012 American Community Survey. The question was asked at both occupied and vacant housing units. The number of bedrooms is the count of rooms designed to be used as bedrooms, that is, the number of rooms that would be listed as bedrooms if the house, apartment, or mobile home were on the market for sale or for rent. Included are all rooms intended to be used as bedrooms even if they currently are being used for some other purpose. A housing unit consisting of only one room is classified, by definition, as having no bedroom.

Bedrooms provide the basis for estimating the amount of living and sleeping spaces within a housing unit. These data allow officials to evaluate the adequacy of the housing stock to shelter the population, and to determine any housing deficiencies in neighborhoods. The data also allow officials to track the changing physical characteristics of the housing inventory over time.

Question/Concept History - The 1996-1998 American Community Survey question provided a response category for "None" and space for the respondent to enter a number of bedrooms. From 1999-2007, the question provided pre-coded response categories from "No bedroom" to "5 or more bedrooms." Starting in 2008, the question became the second part of a two-part question that linked the number of "rooms" and number of "bedrooms" questions together. In addition, the wording of the question was changed to ask, "How many of these rooms are bedrooms?" Additional changes introduced in 2008 included removing the pre- coded response categories and adding a write-in box for the respondent to enter the number of bedrooms, providing the rule to use for defining a "bedroom" as an instruction, and providing an additional instruction addressing efficiency and studio apartments - "If this is an efficiency/studio apartment, print '0'."

Limitation of the Data - The Census Bureau tested the changes introduced to the 2008 version of the bedrooms question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Rooms and Bedrooms" on the ACS website (http://www.census.gov/acs).

Comparability - Caution should be used when comparing American Community Survey data on bedrooms from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the bedrooms question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in "No bedroom" responses and as a decrease in "1 bedroom" to "3 bedrooms" responses.

Business on Property
The data for business on property were obtained from Housing Question 6 in the 2012 American Community Survey. The question was asked at occupied and vacant one-family houses and mobile homes. A business must be easily recognizable from the outside. It usually will have a separate outside entrance and have the appearance of a business, such as a grocery store, restaurant, or barbershop. It may be either attached to the house or mobile home or be located elsewhere on the property. Those housing units in which a room is used for business or professional purposes and have no recognizable alterations to the outside are not considered to have a business. Medical offices are considered businesses for tabulation purposes.
In American Community Surveys prior to 2004 and in Census 2000, business on property was one of the variables used to determine specified owner- and renter-occupied housing units.
Business on property provides information on whether certain housing units should be excluded from statistics on rent, value, and shelter costs. The data provide a means to allow comparisons to be made to earlier census data by identifying information for comparable select groups of housing units without a business or medical office on the property.

Question/Concept History - Since 1999, the 1996-1998 ACS questions were changed to add parentheses to the question wording: "Is there a business (such as a store or barber shop) or a medical office on this property?"

Comparability - Data on business on property in the 2012 American Community Survey can be compared to previous ACS and Census 2000 business on property data.

Condominium Status and Fee
The data on condominium housing units were obtained from Housing Question 13 in the 2012 American Community Survey. The question was asked at occupied housing units.

Condominium Status
Condominium is a type of ownership that enables a person to own an apartment or house in a development of similarly owned units and to hold a common or joint ownership in some or all of the common areas and facilities such as land, roof, hallways, entrances, elevators, swimming pool, etc. Condominiums may be single-family houses as well as units in apartment buildings. A unit does not need to be occupied by the owner to be counted as a condominium.

Condominium Fee
A condominium fee normally is charged monthly to the owners of the individual condominium units by the condominium owners' association to cover operating, maintenance, administrative, and improvement costs of the common property (grounds, halls, lobby, parking areas, laundry rooms, swimming pool, etc.). The costs for utilities and/or fuels may be included in the condominium fee if the units do not have separate meters.

Data on condominium fees may include real estate taxes and/or insurance payments for the common property, but do not include real estate taxes or fire, hazard, and flood insurance reported in Housing Questions 17 and 18 (in the 2012 American Community Survey) for the individual unit.

Amounts reported were the regular monthly payment, even if paid by someone outside the household or remain unpaid. Costs were estimated as closely as possible when exact costs were not known.

The data from this question were added to payments for mortgages (both first, second, home equity loans, and other junior mortgages); real estate taxes; fire hazard, and flood insurance payments; and utilities and fuels to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for condominium owners. These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.

By listing the condominium status and fee separately on the questionnaire, the data also serve to improving the accuracy of estimating monthly housing costs for mortgaged owners.

Question/Concept History - Since 1996, the American Community Survey included the question on condominium status with one that asked for condominium fees. The words "or mobile home," and an instruction for renters to enter the amount of the condominium fee only if the fee was in addition to rent, were added starting in 1999.

Comparability - Data on condominium status and fee in the 2012 American Community Survey can be compared to previous ACS and Census 2000 condominium status and fee data.

Contract Rent
The data on contract rent (also referred to as "rent asked" for vacant units) were obtained from Housing Question 15a in the 2012 American Community Survey. The question was asked at occupied housing units that were for rent, vacant housing units that were for rent, and vacant units rented but not occupied at the time of interview.

Housing units that are renter occupied without payment of rent are shown separately as "No rent paid." The unit may be owned by friends or relatives who live elsewhere and who allow occupancy without charge. Rent-free houses or apartments may be provided to compensate caretakers, ministers, tenant farmers, sharecroppers, or others.

Contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.

If the contract rent includes rent for a business unit or for living quarters occupied by another household, only that part of the rent estimated to be for the respondent's unit was included. Excluded was any rent paid for additional units or for business premises.
If a renter pays rent to the owner of a condominium or cooperative, and the condominium fee or cooperative carrying charge also is paid by the renter to the owner, the condominium fee or carrying charge was included as rent.

If a renter receives payments from lodgers or roomers who are listed as members of the household, the rent without deduction for any payments received from the lodgers or roomers, was to be reported. The respondent was to report the rent agreed to or contracted for even if paid by someone else such as friends or relatives living elsewhere, a church or welfare agency, or the government through subsidies or vouchers.

Contract rent provides information on the monthly housing cost expenses for renters. When the data is used in conjunction with utility costs and income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance to agencies in determining policies on fair rent.

Median and Quartile Contract Rent
The median divides the rent distribution into two equal parts: one-half of the cases falling below the median contract rent and one-half above the median. Quartiles divide the rent distribution into four equal parts. Median and quartile contract rent are computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) In computing median and quartile contract rent, units reported as "No rent paid" are excluded. Median and quartile rent calculations are rounded to the nearest whole dollar. Upper and lower quartiles can be used to note large rent differences among various geographic areas. (For more information on medians and quartiles, see "Derived Measures.")

Aggregate Contract Rent
Aggregate contract rent is calculated by adding all of the contract rents for occupied housing units in an area. Aggregate contract rent is rounded to the nearest hundred dollars. This explanation is comparable to the description used for Aggregate Gross Rent. (For more information, see "Aggregate" under "Derived Measures.")

Aggregate Rent Asked
Aggregate rent asked is calculated by adding all of the rents for vacant-for-rent housing units in an area. Aggregate rent asked is subject to rounding, which means that all cells in a matrix are rounded to the nearest hundred dollars. (For more information, see "Aggregate" under "Derived Measures.")

Question/Concept History

Since 1996, the American Community Survey questionnaires provided a space for the respondent to enter a dollar amount. The words "or mobile home"
were added to the question starting in 1999 to be more inclusive of the structure type. Since 2004, contract rent has been shown for all renter-occupied housing units. In previous years (1996-2003), it was shown only for specified renter-occupied housing units.

Comparability

Data on contract rent in the 2012 American Community Survey should not be compared to Census 2000 contract rent data. For Census 2000, tables were not released for total renter-occupied units. The universe in Census 2000 was "specified renter-occupied housing units" whereas the universe in the ACS is "renter occupied housing units," thus comparisons cannot be made between these two data sets.

Food Stamp/Supplemental Nutrition Assistance Program Benefits (SNAP)
The data on Food Stamp benefits were obtained from Housing Question 12 in the 2012 American Community Survey. The Food Stamp Act of 1977 defines this federally-funded program as one intended to "permit low-income households to obtain a more nutritious diet" (from Title XIII of Public Law 95-113, The Food Stamp Act of 1977, declaration of policy). Food purchasing power is increased by providing eligible households with coupons or cards that can be used to purchase food. The Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA) administers the Food Stamp Program through state and local welfare offices. The Food Stamp Program is the major national income support program to which all low-income and low-resource households, regardless of household characteristics, are eligible.

On October 1, 2008, the Federal Food Stamp program was renamed SNAP (Supplemental Nutrition Assistance Program).

Respondents were asked if one or more of the current members received food stamps or a food stamp benefit card during the past 12 months. Respondents were also asked to include benefits from the Supplemental Nutrition Assistance Program (SNAP) in order to incorporate the program name change.

Question/Concept History - The 1996-1998 American Community Survey asked for a 12- month amount for the value of the food stamps following the Yes response category. For the 1999-2002 ACS, the words "Food Stamps" were capitalized in the question following the Yes response category, and the instruction "Past 12 months' value - Dollars" was added. Since 2003, the words "received during the past 12 months" were added to the question following the Yes response category. Beginning in 2008, the value of food stamps received was no longer collected; the wording of the question was changed from "At anytime during the past 12 months" to "In the past 12 months," and the term '"food stamp benefit card' was added.
Adding the text "food stamps benefit card" to the question text and removing the dollar amount portion of the question resulted in a statistically significant increase in the recipiency rate for food stamps because of a decrease in item nonresponse rate.

Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Many types of GQ populations have food stamp distributions that are very different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the food stamp distribution. This is particularly true for areas with a substantial GQ population.

The Census Bureau tested the changes introduced to the 2008 version of the Food Stamp benefits question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Receipt Food Stamps" on the ACS website (http://www.census.gov/acs).

Comparability - The Food Stamp/SNAP question is not asked in Census 2000. Because of the wording change on the 2008 ACS questionnaire, you cannot compare data before and after 2008.

Gross Rent
The data on gross rent were obtained from answers to Housing Questions 11a-d and 15a in the 2012 American Community Survey. Gross rent is the contract rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter (or paid for the renter by someone else). Gross rent is intended to eliminate differentials that result from varying practices with respect to the inclusion of utilities and fuels as part of the rental payment. The estimated costs of water and sewer, and fuels are reported on a 12-month basis but are converted to monthly figures for the tabulations. Renter units occupied without payment of rent are shown separately as "No rent paid" in the tabulations.

Gross rent provides information on the monthly housing cost expenses for renters. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance to agencies in determining policies on fair rent.

Adjusting Gross Rent for Inflation
To inflate gross rent amounts from previous years, the dollar values are inflated to the latest year's dollar values by multiplying by a factor equal to the average annual Consumer Price Index (CPI-U-RS) factor for the current year, divided by the average annual CPI-U-RS factor for the earlier/earliest year.

Median Gross Rent
Median gross rent divides the gross rent distribution into two equal parts: one-half of the cases falling below the median gross rent and one-half above the median. Median gross rent is computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) Median gross rent is rounded to the nearest whole dollar. (For more information on medians, see "Derived Measures.")

Aggregate Gross Rent
Aggregate gross rent is calculated by adding together all the gross rents for all specified housing units in an area. Aggregate gross rent is rounded to the nearest hundred dollars. (For more information, see "Aggregate" under "Derived Measures.")

Question/Concept History

Since 1996, the American Community Survey questions have remained the same.

Comparability

Data on gross rent in the 2012 American Community Survey should not be compared to Census 2000 gross rent data. For Census 2000, tables were not released for total renter-occupied units. The universe in Census 2000 was "specified renter-occupied housing units" whereas the universe in the ACS is "renter occupied housing units," thus comparisons cannot be made between these two data sets.

Gross Rent as a Percentage of Household Income
Gross rent as a percentage of household income is a computed ratio of monthly gross rent to monthly household income (total household income divided by 12). The ratio is computed separately for each unit and is rounded to the nearest tenth. Units for which no rent is paid and units occupied by households that reported no income or a net loss comprise the category, "Not computed."

Gross rent as a percentage of household income provides information on the monthly housing cost expenses for renters. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance to agencies in determining policies on fair rent.

Median Gross Rent as a Percentage of Household Income
This measure divides the gross rent as a percentage of household income distribution into two equal parts: one-half of the cases falling below the median gross rent as a percentage of household income and one- half above the median. Median gross rent as a percentage of household income is computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) Median gross rent as a percentage of household income is rounded to the nearest tenth. (For more information on medians, see "Derived Measures.")

Comparability

Data on gross rent as a percentage of household income in the 2012 American Community Survey should not be compared to Census 2000 gross rent as a percentage of household income data. For Census 2000, tables were not released for total renter-occupied units. The universe in Census 2000 was "specified renter-occupied housing units" whereas the universe in the ACS is "renter occupied housing units," thus comparisons cannot be made between these two data sets.

Homeowner Vacancy Rate
See Vacancy Status.

House Heating Fuel
The data on house heating fuel were obtained from Housing Question 10 in the 2012 American Community Survey. The question was asked at occupied housing units. The data show the type of fuel used most to heat the house, apartment, or mobile home.

House heating fuel provides information on energy supply and consumption. These data are used by planners to identify the types of fuel used in certain areas and the consequences this usage may have on the area. The data also serve to aid in forecasting the need for future energy needs and power facilities such as generating plants, long distance pipelines for oil or natural gas, and long distance transmission lines for electricity.

House heating fuel is categorized on the ACS questionnaire as follows:

Utility Gas - This category includes gas piped through underground pipes from a central system to serve the neighborhood.

Bottled, Tank, or LP Gas - This category includes liquid propane gas stored in bottles or tanks that are refilled or exchanged when empty.

Electricity - This category includes electricity that is generally supplied by means of above or underground electric power lines.

Fuel Oil, Kerosene, etc. - This category includes fuel oil, kerosene, gasoline, alcohol, and other combustible liquids.

coal or coke - This category includes coal or coke that is usually distributed by truck.

Wood - This category includes purchased wood, wood cut by household members on their property or elsewhere, driftwood, sawmill or construction scraps, or the like.

Solar Energy - This category includes heat provided by sunlight that is collected, stored, and actively distributed to most of the rooms.

Other Fuel - This category includes all other fuels not specified elsewhere.

No Fuel used - This category includes units that do not use any fuel or that do not have heating equipment.

Question/Concept History - Since 1996, the American Community Survey questions have remained the same.

Comparability - Data on house heating fuel in the 2012 American Community Survey can be compared to previous ACS and Census 2000 house heating fuel data.

Household Size
This question is based on the count of people in occupied housing units. All people occupying the housing unit are counted, including the householder, occupants related to the householder, and lodgers, roomers, boarders, and so forth.

Average Household Size of Occupied Unit
A measure obtained by dividing the number of people living in occupied housing units by the total number of occupied housing units. This measure is rounded to the nearest hundredth.

Average Household Size of Owner-occupied Unit
A measure obtained by dividing the number of people living in owner-occupied housing units by the total number of owner- occupied housing units. This measure is rounded to the nearest hundredth.

Average Household Size of Renter-occupied Unit
A measure obtained by dividing the number of people living in renter-occupied housing units by the total number of renter- occupied housing units. This measure is rounded to the nearest hundredth.

Comparability

Data on household size in the 2012 American Community Survey can be compared to previous ACS and Census 2000 household size data.

Housing Units
See Living Quarters.

Insurance for Fire, Hazard, and Flood
The data on fire, hazard, and flood insurance were obtained from Housing Question 18 in the 2012 American Community Survey. The question was asked of owner-occupied units. The statistics for this question refer to the annual premium for fire, hazard, and flood insurance on the property (land and buildings), that is, policies that protect the property and its contents against loss due to damage by fire, lightning, winds, hail, flood, explosion, and so on.

Liability policies are included only if they are paid with the fire, hazard, and flood insurance premiums and the amounts for fire, hazard, and flood cannot be separated. Premiums are reported even if they have not been paid or are paid by someone outside the household. When premiums are paid on other than a yearly basis, the premiums are converted to a yearly basis.

The payment for fire, hazard, and flood insurance is added to payments for real estate taxes, utilities, fuels, and mortgages (both first, second, home equity loans, and other junior mortgages) to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income." These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.

A separate question (19d in the 2012 American Community Survey) determines whether insurance premiums are included in the mortgage payment to the lender(s). This makes it possible to avoid counting these premiums twice in the computations.

Median Fire, Hazard, and Flood Insurance
Median fire, hazard, and flood insurance divides the fire, hazard, and flood insurance distribution into two equal parts: one-half of the cases falling below the median fire, hazard, and flood insurance and one-half above the median. Median fire, hazard, and flood insurance is computed on the basis of a standard distribution (see the "Standard Distributions" section under Appendix A.) Median fire, hazard, and flood insurance is rounded to the nearest whole dollar. (For more information on medians, see "Derived Measures.")

Question/Concept History

The American Community Survey questions have been the same since 1996.

Comparability

Data on fire, hazard, and flood insurance in the 2012 American Community Survey can be compared to previous ACS and Census 2000 fire, hazard, and flood insurance data.

Kitchen Facilities
Data on kitchen facilities were obtained from Housing Question 8d-f in the 2012 American Community Survey. The question was asked at both occupied and vacant housing units. A unit has complete kitchen facilities when it has all three of the following facilities: (d) a sink with a faucet, (e) a stove or range, and (f) a refrigerator. All kitchen facilities must be located in the house, apartment, or mobile home, but they need not be in the same room. A housing unit having only a microwave or portable heating equipment such as a hot plate or camping stove should not be considered as having complete kitchen facilities. An icebox is not considered to be a refrigerator.

Kitchen facilities provide an indication of living standards and assess the quality of household facilities within the housing inventory. These data provide assistance in determining areas that are eligible for programs and funding, such as Meals on Wheels. The data also serve to aid in the development of policies based on fair market rent, and to identify areas in need of rehabilitation loans or grants.

Question/Concept History

The 1996-1998 American Community Survey questions asked whether the house or apartment had complete kitchen facilities, requiring that the three facilities all be in the same unit. In 1999, "mobile home" was added to the question, along with the capitalization of the word "COMPLETE" for emphasis. Starting in 2008, the structure of the question changed and combined kitchen facilities with plumbing facilities and telephone service availability into one question to ask, "Does this house, apartment, or mobile home have-" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. Also in 2008, the component "sink with piped water" was changed to "sink with a faucet."

Comparability

Caution should be used when comparing American Community Survey data on kitchen facilities from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the kitchen facilities question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in housing units "lacking complete kitchen facilities."

Meals Included in Rent
The data on meals included in the rent were obtained from Housing Question 15b in the 2012 American Community Survey. The question was asked of occupied housing units that were rented and vacant housing units that were for rent at the time of enumeration. These data only include rental units which meals are included in the rent, or if occupants contract for either their meals or a meal plan in order to live in the unit. Renters in continuing care or life facilities are included in this category if their contracts cover meal services.

The meals included in rent allows for a measurement on the amount of congregate housing within the housing inventory. Congregate housing is considered to be housing units where the rent includes meals and other services.

Question/Concept History

Since 1996, the American Community Survey questions have been the same. Starting in 2004, meals included in rent is shown for all renter-occupied housing units. In previous years (1996-2003), it was shown only for specified renter- occupied housing units.

Comparability

Data on meals included in rent in the 2012 American Community Survey can be compared to previous ACS and Census 2000 meals included in rent data.

Mobile Home Costs
The data on mobile home costs were obtained from Housing Question 21 in the 2012 American Community Survey. The question was asked at owner-occupied mobile homes.
These data include the total yearly costs for personal property taxes, land or site rent, registration fees, and license fees on all owner-occupied mobile homes. The instructions are to exclude real estate taxes already reported in Question 17 in the 2012 American Community Survey.

Costs are estimated as closely as possible when exact costs are not known. Amounts are the total for an entire 12-month billing period, even if they are paid by someone outside the household or remain unpaid.

The data from this question are added to payments for mortgages; real estate taxes; fire, hazard, and flood insurance payments; utilities; and fuels to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for mobile home owners. These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.

Question/Concept History

The 1996-1998 American Community Survey questions were the same. Between 1999 and 2002, the question had a lead-in question on whether the respondent had an installment loan or a contract on the mobile home. The question then asked for total costs including any installment loan.

Comparability

Data on mobile home costs in the 2012 American Community Survey can be compared to previous ACS and Census 2000 mobile home costs data.

Monthly Housing Costs
The data for monthly housing costs are developed from a distribution of "Selected Monthly Owner Costs" for owner-occupied units and "Gross Rent" for renter-occupied units. The owner-occupied categories are further separated into those with a mortgage and those without a mortgage. See the sections on "Selected Monthly Owner Costs" and "Gross Rent" for more details on what characteristics are included in each measure and how these data are comparable to previous ACS and Census 2000 data.

Monthly housing costs provide information on the cost of monthly housing expenses for owners and renters. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

Median Monthly Housing Costs
This measure divides the monthly housing costs distribution into two equal parts: one-half of the cases falling below the median monthly housing costs and one-half above the median. Medians are shown separately for units "with a mortgage" and for units "not mortgaged." Median monthly housing costs are computed on the basis of a standard distribution. (See the "Standard Distributions" section under Appendix A.) Median monthly housing costs are rounded to the nearest whole dollar.

Monthly Housing Costs as a Percentage of Household Income
The data for monthly housing costs as a percentage of household income are developed from a distribution of "Selected Monthly Owner Costs as a Percentage of Household Income" for owner-occupied and "Gross Rent as a Percentage of Household Income" for renter-occupied units. The owner-occupied categories are further separated into those with a mortgage and those without a mortgage. See sections on "Selected Monthly Owner Costs as a Percentage of Household Income" and "Gross Rent as a Percentage of Household Income" for more details on what characteristics are included in each measure and how these data are comparable to previous ACS and Census 2000 data.

Monthly housing costs as a percentage of household income provide information on the cost of monthly housing expenses for owners and renters. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

Mortgage Payment
The data on mortgage payment were obtained from Housing Question 19b in the 2012 American Community Survey. The question was asked at owner-occupied units that have a mortgage, deed of trust, or similar debt; or contract to purchase. The question provides the regular monthly amount required to be paid to the lender for the first mortgage (deed of trust, contract to purchase, or similar debt) on the property. Amounts are included even if the payments are delinquent or paid by someone else. The amounts reported are included in the computation of "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for units with a mortgage.

The amounts reported include everything paid to the lender including principal and interest payments, real estate taxes, fire, hazard, and flood insurance payments, and mortgage insurance premiums. Separate questions determine whether real estate taxes and fire, hazard, and flood insurance payments are included in the mortgage payment to the lender. This makes it possible to avoid counting these components twice in the computation of "Selected Monthly Owner Costs."
Mortgage payment provides information on the monthly housing cost expenses for owners with a mortgage. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs aimed to meet the needs of people at different economic levels.

Question/Concept History

Since 1996, the American Community Survey questions have been the same.

Comparability

Data on mortgage payment in the 2012 American Community Survey can be compared to previous ACS and Census 2000 mortgage payment data. For Census 2000, tables for both total owner-occupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets.

Mortgage Status
The data on mortgage status were obtained from Housing Questions 19a and 20a in the 2012 American Community Survey. The questions were asked at owner-occupied units. "Mortgage" refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust; trust deeds; contracts to purchase; land contracts; junior mortgages; and home equity loans.

A mortgage is considered a first mortgage if it has prior claim over any other mortgage or if it is the only mortgage on the property. All other mortgages (second, third, etc.) are considered junior mortgages. A home equity loan is generally a junior mortgage. If no first mortgage is reported, but a junior mortgage or home equity loan is reported, then the loan is considered a first mortgage.

In most data products, the tabulations for "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" usually are shown separately for units "with a mortgage" and for units "not mortgaged." The category "not mortgaged" is comprised of housing units owned free and clear of debt.

Mortgage status provides information on the cost of home ownership. When the data is used in conjunction with mortgage payment data, the information determines shelter costs for living quarters. These data can be used in the development of housing programs aimed to meet the needs of people at different economic levels.

Question/Concept History

Since 1996, the American Community Survey for mortgage status questions have been the same.

Comparability

Data on mortgage status in the 2012 American Community Survey can be compared to previous ACS and Census 2000 mortgage status data. For Census 2000, tables for both total owner-occupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets.

Occupants Per Room
Occupants per room is obtained by dividing the reported number of current residents in each occupied housing unit by the number of rooms in the unit. The figures show the number of occupied units having the specified ratio of current residents per room. Occupants per room is rounded to the nearest hundredth.
This data is the basis for estimating the amount of living and sleeping spaces within a housing unit. The data also serve to aid in planning for future services and infrastructure, such as home energy assistance programs and the development of waste treatment facilities.

Comparability

Caution should be used when comparing American Community Survey data on occupants per room from the years 2008 and after with both pre-2008 data. Changes made to the rooms question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable in a 2006 content test with the revised question showing an increase in "1 room" responses, decrease in "2 rooms" to "6 rooms" responses, and increases in "7 rooms" and "9 or more" room responses, with an overall increase in the median number of rooms reported using the revised question.

Data on occupants per room in the American Community Survey should be compared with great caution to Census 2000 data due to: 1) differences in residence rules and the absence of population controls used to adjust for undercoverage in the reported number of current residents in the ACS used in this measure and 2) differences in the reported number of rooms due to changes in the rooms question between the 2007 and 2008 ACS.

Occupied Housing Units
See Living Quarters.

Owner-Occupied Units
See Tenure.

Plumbing Facilities
The data on plumbing facilities were obtained from Housing Question 8 a, b, and c in the 2012 American Community Survey. The question was asked at both occupied and vacant housing units. Complete plumbing facilities include: (a) hot and cold running water, (b) a flush toilet, and (c) a bathtub or shower. All three facilities must be located inside the house, apartment, or mobile home, but not necessarily in the same room. Housing units are classified as lacking complete plumbing facilities when any of the three facilities is not present.

Plumbing facilities provide an indication of living standards and assess the quality of household facilities within the housing inventory. These data provide assistance in the assessment of water resources and to serve as an aid to identify possible areas of ground water contamination. The data also are used to forecast the need for additional water and sewage facilities, aid in the development of policies based on fair market rent, and to identify areas in need of rehabilitation loans or grants.

Question/Concept History

The 1996-2007 American Community Survey questions were stand-alone questions that asked the respondent to answer either "Yes, has all three facilities" or "No" to the question of whether the housing unit had complete plumbing facilities, requiring that the facilities all be in the same unit. Starting in 2008, the structure of the question changed and combined plumbing facilities with kitchen facilities and telephone service availability into one question to ask, "Does this house, apartment, or mobile home have -" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. An additional change introduced in 2008 included changing the description of the component "hot and cold piped water" to "hot and cold running water."

Comparability

Caution should be used when comparing American Community Survey data on plumbing facilities from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the plumbing facilities question between 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in housing units "lacking complete plumbing facilities."

Data tables for Puerto Rico were not shown. Research indicated that the questions on plumbing facilities that were introduced in 2008 in the stateside American Community Survey and the Puerto Rico Community Survey may not have been appropriate for Puerto Rico.

Population in Occupied Housing Units
The data shown for population in occupied units is the total population minus any people living in group quarters. All people occupying the housing unit are counted, including the householder, occupants related to the householder, and lodgers, roomers, boarders, and so forth.
Population in occupied housing units provides information on the population within the housing inventory. The data allow the identification of population patterns within areas to assist in developing housing programs. These data also serve to aid officials in tracking the changing population characteristics of the housing inventory over time.

Comparability

Data on the population in occupied housing units in the 2012 American Community Survey can be compared to previous ACS and Census 2000 population data on the population in occupied housing units.

Poverty Status of Households
The data on poverty status of households were derived from answers to the income questions. Since poverty is defined at the family level and not the household level, the poverty status of the household is determined by the poverty status of the householder. Households are classified as poor when the total income of the householder's family is below the appropriate poverty threshold. (For nonfamily householders, their own income is compared with the appropriate threshold.) The income of people living in the household who are unrelated to the householder is not considered when determining the poverty status of a household, nor does their presence affect the family size in determining the appropriate threshold. The poverty thresholds vary depending on three criteria: size of family, number of related children, and, for 1- and 2-person families, age of householder. See the table "The 2012 Poverty Factors" in Appendix A. (For more information, see "Poverty Status" and "Income" under "Population Variables.")

Real Estate Taxes
The data on real estate taxes were obtained from Housing Question 17 in the 2012 American Community Survey. The question was asked at owner-occupied units. The statistics from this question refer to the total amount of all real estate taxes on the entire property (land and buildings) payable to all taxing jurisdictions, including special assessments, school taxes, county taxes, and so forth.

Real estate taxes include state, local, and all other real estate taxes even if delinquent, unpaid, or paid by someone who is not a member of the household. However, taxes due from prior years are not included. If taxes are paid on other than a yearly basis, the payments are converted to a yearly basis.
The payment for real estate taxes is added to payments for fire, hazard, and flood insurance; utilities and fuels; and mortgages (both first and second mortgages, home equity loans, and other junior mortgages) to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income." These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.
A separate question (Question 19c in the 2008 American Community Survey) determines whether real estate taxes are included in the mortgage payment to the lender(s). This makes it possible to avoid counting taxes twice in the computations.

Question/Concept History

Since 1996, the American Community Survey questions have been the same.

Comparability

Data on real estate taxes in the 2012 American Community Survey should not be compared to Census 2000 real estate taxes data. The universe in Census 2000 was "specified owner-occupied housing units" whereas the universe in the ACS is "owner occupied housing units," thus comparisons cannot be made between these two data sets.

Rent Asked
See Contract Rent.

Rental Vacancy Rate
See Vacancy Status.

Renter-Occupied Housing Units
See Tenure.

The data on rooms were obtained from Housing Question 7a in the 2012 American Community Survey. The question was asked at both occupied and vacant housing units. The statistics on rooms are in terms of the number of housing units with a specified number of rooms. The intent of this question is to count the number of whole rooms used for living purposes.

For each unit, rooms include living rooms, dining rooms, kitchens, bedrooms, finished recreation rooms, enclosed porches suitable for year-round use, and lodger's rooms. Excluded are strip or pullman kitchens, bathrooms, open porches, balconies, halls or foyers, half-rooms, utility rooms, unfinished attics or basements, or other unfinished space used for storage. A partially divided room is a separate room only if there is a partition from floor to ceiling, but not if the partition consists solely of shelves or cabinets.

Rooms provide the basis for estimating the amount of living and sleeping spaces within a housing unit. These data allow officials to plan and allocate funding for additional housing to relieve crowded housing conditions. The data also serve to aid in planning for future services and infrastructure, such as home energy assistance programs and the development of waste treatment facilities.

Median Rooms
This measure divides the room distribution into two equal parts: one-half of the cases falling below the median number of rooms and one-half above the median. In computing median rooms, the whole number is used as the midpoint of the interval; thus, the category "3 rooms" is treated as an interval ranging from 2.5 to 3.5 rooms. Median rooms is rounded to the nearest tenth. (For more information on medians, see the discussion under "Derived Measures.")

Aggregate Rooms
Aggregate rooms is calculated by adding all of the rooms for housing units in an area. (For more information on aggregates, see "Derived Measures.")

Question/Concept History

The 1996-1998 American Community Survey question provided a space for a write-in entry on the number of rooms. From 1999-2007 the question provided response categories from "1 room" to "9 or more rooms." Starting in 2008, the response categories were removed and a write-in box was added for the respondent to enter the number of rooms. Additional changes introduced in 2008 included adding the word "separate" to the question stem, adding an instruction that defines a "room," adding an inclusion instruction to include bedrooms and kitchens in the count of rooms, and changing the current exclusion instruction by removing the word "half-room" and adding the phrase "unfinished basements."

Limitation of the Data

The Census Bureau tested the changes introduced to the 2008 version of the rooms question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Rooms and Bedrooms" on the ACS website (http://www.census.gov/acs).

Comparability

Caution should be used when comparing American Community Survey data on rooms from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the rooms question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in "1 room" response and as a decrease in "2 rooms" to "6 rooms" responses.

Second or Junior Mortgage Payments or Home Equity Loan
The data on second mortgages or home equity loan payments were obtained from Housing Questions 20a and 20b in the 2012 American Community Survey. The questions were asked at owner-occupied units. Question 20a asks whether a second mortgage or a home equity loan exists on the property. Question 20b provides the regular monthly amount required to be paid to the lender on all second and junior mortgages and home equity loans. Amounts are included even if the payments are delinquent or paid by someone else. The amounts reported are included in the computation of "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for units with a mortgage.

All mortgages other than first mortgages (for example, second, third, etc.) are classified as "junior" mortgages. A second mortgage is a junior mortgage that gives the lender a claim against the property that is second to the claim of the holder of the first mortgage. Any other junior mortgage(s) would be subordinate to the second mortgage. A home equity loan is a line of credit available to the borrower that is secured by real estate. It may be placed on a property that already has a first or second mortgage, or it may be placed on a property that is owned free and clear.

If the respondents answered that no first mortgage existed, but a second mortgage or a home equity loan did, a computer edit assigned the unit a first mortgage and made the first mortgage monthly payment the amount reported in the second mortgage. The second mortgage/home equity loan data were then made "No" in Question 20a and blank in Question 20b.

Second mortgage or home equity loan data provide information on the monthly housing cost expenses for owners. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs aimed to meet the needs of people at different economic levels.

By listing the second mortgage or home equity loan question separately on the questionnaire from other housing cost questions, the data also serve to improving the accuracy of estimating monthly housing costs for mortgaged owners.

Question/Concept History

Since 1996, the American Community Survey questions remained the same.

Comparability

Data on second mortgages or home equity loans in the 2012 American Community Survey can be compared to previous ACS and Census 2000 second mortgages or home equity loans data.

Selected Conditions
The variable "Selected Conditions" is defined for owner- and renter-occupied housing units as having at least one of the following conditions:

1) lacking complete plumbing facilities,

2) lacking complete kitchen facilities,

3) with 1.01 or more occupants per room,

4) selected monthly owner costs as a percentage of household income greater than 30 percent, and

5) gross rent as a percentage of household income greater than 30 percent.

Selected conditions provide information in assessing the quality of the housing inventory and its occupants. The data is used to easily identify those homes in which the quality of living and housing can be considered substandard.

Comparability

Data on selected conditions in the 2012 American Community Survey can be compared to previous ACS and Census 2000 selected conditions data.

Selected Monthly Owner Costs
The data on selected monthly owner costs were obtained from Housing Questions 11 and Questions 17 through 21 in the 2012 American Community Survey. The data were obtained for owner-occupied units. Selected monthly owner costs are the sum of payments for mortgages, deeds of trust, contracts to purchase, or similar debts on the property (including payments for the first mortgage, second mortgages, home equity loans, and other junior mortgages); real estate taxes; fire, hazard, and flood insurance on the property; utilities (electricity, gas, and water and sewer); and fuels (oil, coal, kerosene, wood, etc.). It also includes, where appropriate, the monthly condominium fee for condominiums (Question 13) and mobile home costs (Question 21) (installment loan payments, personal property taxes, site rent, registration fees, and license fees). Selected monthly owner costs were tabulated for all owner-occupied units, and usually are shown separately for units "with a mortgage" and for units "not mortgaged."

Selected monthly owner costs provide information on the monthly housing cost expenses for owners. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

Adjusting Selected Monthly Owner Costs for Inflation
To inflate selected monthly owner costs from previous years, the dollar values are inflated to the latest year's dollar values by multiplying by a factor equal to the average annual Consumer Price Index (CPI-U- RS) factor for the current year, divided by the average annual CPI-U-RS factor for the earlier/earliest year.

Median Selected Monthly Owner Costs
This measure divides the selected monthly owner costs distribution into two equal parts: one-half of the cases falling below the median selected monthly owner costs and one-half above the median. Medians are shown separately for units "with a mortgage" and for units "not mortgaged." Median selected monthly owner costs are computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) Median selected monthly owner costs are rounded to the nearest whole dollar.

Question/Concept History

Since 1996, the American Community Survey questions have been the same. The American Community Survey collected the monthly cost of electricity and gas, and the 12-month cost of water and sewer. Since 2004, selected monthly owner costs has been shown for all owner-occupied housing units. In previous years (1996-2003), the question was shown only for specified owner-occupied housing units.

Comparability

Caution should be used when comparing selected monthly owner costs data between the American Community Survey and Census 2000. For Census 2000, tables for both total owner-occupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets. Additionally, for Census 2000 tables with full distributions were released for total owner-occupied housing units but medians were not shown.

Selected Monthly Owner Costs as a Percentage of Household Income
The information on selected monthly owner costs as a percentage of household income is the computed ratio of selected monthly owner costs to monthly household income. The ratio was computed separately for each unit and rounded to the nearest whole percentage. The data are tabulated only for owner-occupied units.
Separate distributions are often shown for units "with a mortgage" and for units "not mortgaged." Units occupied by households reporting no income or a net loss are included in the "not computed" category. (For more information, see the discussion under "Selected Monthly Owner Costs.")
Selected monthly owner costs as a percentage of household income provide information on the monthly housing cost expenses for owners. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

Median Selected Monthly Owner Costs as a Percentage of Household Income
This measure divides the selected monthly owner costs as a percentage of household income distribution into two equal parts: one-half of the cases falling below the median selected monthly owner costs as a percentage of household income and one-half above the median. Median selected monthly owner costs as a percentage of household income is computed on the basis of a standard distribution. (See the "Standard Distributions" section under Appendix A.) Median selected monthly owner costs as a percentage of household income is rounded to the nearest tenth. (For more information on medians, see "Derived Measures.")

Comparability

Caution should be used when comparing selected monthly owner costs as a percentage of household income data between the American Community Survey and Census 2000. For Census 2000, tables for both total owner-occupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets. Additionally, for Census 2000 tables with full distributions were released for total owner-occupied housing units but medians were not shown.

Specified Owner-Occupied Units
Specified owner-occupied units include only 1-family houses on less than 10 acres (cuerdas) without a business or medical office on the property. The data for "specified units" exclude mobile homes, houses with a business or medical office, houses on 10 or more acres (cuerdas), and housing units in multiunit buildings.
Specified owner-occupied unit information is used to maintain a comparable universe between the American Community Survey and earlier census data. Financial housing characteristics in earlier census data were based on a specified owner-occupied unit, however the ACS does not provide information solely for this universe. Therefore, the characteristics for a specified owner-occupied unit are maintained within the PUMS file to ensure comparisons can be made between the two data sets.

Question/Concept History

Prior to 1990, much of the owner-occupied housing inventory was comprised of single-family homes, either detached or attached. Therefore, earlier census data provided financial housing characteristics for the specified owner-occupied unit universe. However, the housing market began to change during the 1990's as an increasing number of units in multiunit structures were constructed and sold as condominiums, as well as the increase of mobile homes as an option for lower-income owners to purchase a home. As a result of these changes, the ACS abandoned the concept of the specified owner- occupied universe to ensure housing data was provided for all owner-occupied units.

Comparability

The ACS only publishes financial housing characteristics for all units. The ACS PUMS file will provide the individual characteristics of a specified owner-occupied unit to allow comparisons to be made between the ACS and earlier census data. Census 2000 data provide financial housing characteristics for both all owner-occupied units and the more restricted universe of specified owner-occupied units.

Specified Renter-Occupied Units
Specified renter-occupied units are renter-occupied units that exclude 1-family houses on 10 or more acres (cuerdas).
Specified renter-occupied unit information is used to maintain a comparable universe between the American Community Survey and earlier census data. Financial housing characteristics in earlier census data were based on a specified renter-occupied unit, however the ACS does not provide information solely for this universe. Therefore, the characteristics for a specified renter-occupied unit are maintained within the PUMS file to ensure comparisons can be made between the two data sets.

Comparability

The ACS only publishes financial housing characteristics for total renter- occupied units; whereas for Census 2000, tables were only released for specified renter- occupied units. Therefore, comparisons between these two data sets cannot be made, unless the characteristics of a specified renter-occupied are used to construct the same universe within the ACS PUMS file.

Telephone Service Available
The data on telephones were obtained from Housing Question 8g in the 2012 American Community Survey. The question was asked at occupied housing units.
The question asked whether telephone service was available in the house, apartment, or mobile home. A telephone must be in working order and service available in the house, apartment, or mobile home that allows the respondent to both make and receive calls. Households whose service has been discontinued for nonpayment or other reasons are not counted as having telephone service available.

The availability of telephone service provides information on the isolation of households. These data help assess the level of communication access amongst elderly and low-income households. The data also serve to aid in the development of emergency telephone, medical, or crime prevention services.

Question/Concept History

For the 1996-1998 American Community Survey, the question asked whether there was a telephone in the house or apartment. A telephone must be inside the house or apartment for the unit to be classified as having a telephone. Units where the respondent used a telephone located inside the building, but not in the respondent's living quarters, were classified as having no telephone. In 1999, the words "or mobile home" were added question to be more inclusive of the structure type. In 2004, instructions that accompanied the ACS mail questionnaire advised respondents that if the household members used cell phones to answer that the house, apartment, or mobile home had telephone service. Starting in 2008, the structure of the question changed and combined telephone service availability with plumbing facilities and kitchen facilities into one question to ask, "Does this house, apartment, or mobile home have -" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. In 2008 the instruction "Include cell phones" was added.

Limitation of the Data

The Census Bureau tested the changes introduced to the 2008 version of the telephone service available question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008; see "2006 ACS Content Test Evaluation Report Covering Facilities" on the ACS website (http://www.census.gov/acs).

Comparability

Caution should be used when comparing American Community Survey data on telephone service availability from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the telephone service availability question between the 2007 and 2008 ACS involving the structure of the question as well as the introduction of an instruction to include cell phones resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in the number of respondents answering "Yes" to the question.

Tenure
The data for tenure were obtained from Housing Question 14 in the 2012 American Community Survey. The question was asked at occupied housing units. Occupied housing units are classified as either owner-occupied or renter-occupied.

Tenure provides a measurement of home ownership, which has served as an indicator of the nation's economy for decades. These data are used to aid in the distribution of funds for programs such as those involving mortgage insurance, rental housing, and national defense housing. Data on tenure allows planners to evaluate the overall viability of housing markets and to assess the stability of neighborhoods. The data also serve in understanding the characteristics of owner-occupied and renter-occupied units to aid builders, mortgage lenders, planning officials, government agencies, etc., in the planning of housing programs and services.

Owner-Occupied
A housing unit is owner-occupied if the owner or co-owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person 1 on the questionnaire. The unit is "Owned by you or someone in this household with a mortgage or loan" if it is being purchased with a mortgage or some other debt arrangement such as a deed of trust, trust deed, contract to purchase, land contract, or purchase agreement. The unit also is considered owned with a mortgage if it is built on leased land and there is a mortgage on the unit. Mobile homes occupied by owners with installment loan balances also are included in this category.

A housing unit is "Owned by you or someone in this household free and clear (without a mortgage or loan)" if there is no mortgage or other similar debt on the house, apartment, or mobile home including units built on leased land if the unit is owned outright without a mortgage.

Renter-Occupied
All occupied housing units which are not owner-occupied, whether they are rented or occupied without payment of rent, are classified as renter-occupied. "No rent paid" units are separately identified in the rent tabulations. Such units are generally provided free by friends or relatives or in exchange for services such as resident manager, caretaker, minister, or tenant farmer. Housing units on military bases also are classified in the "No rent paid" category. "Rented" includes units in continuing care, sometimes called life care arrangements. These arrangements usually involve a contract between one or more individuals and a health services provider guaranteeing the individual shelter, usually a house or apartment, and services, such as meals or transportation to shopping or recreation. (For more information, see "Meals Included in Rent.")

Question/Concept History

From 1996-2007 the American Community Survey questions were the same. Starting in 2008, the instruction ""Mark (X) ONE box." was added following the question, and the instruction "Include home equity loans." was added following the response category "Owned by you or someone in this household with a mortgage or loan?" Additional changes introduced in 2008 included revising the wording of two of the response categories from "Rented for cash rent?" to "Rented?" and "Occupied without payment of cash rent?" to "Occupied without payment of rent?"

Comparability

Data on tenure in the 2012 American Community Survey can be compared to previous ACS and Census 2000 tenure data.

Units in Structure
The data on units in structure (also referred to as "type of structure") were obtained from Housing Question 1 in the 2012 American Community Survey. The question was asked at occupied and vacant housing units. A structure is a separate building that either has open spaces on all sides or is separated from other structures by dividing walls that extend from ground to roof. In determining the number of units in a structure, all housing units, both occupied and vacant, are counted. Stores and office space are excluded. The data are presented for the number of housing units in structures of specified type and size, not for the number of residential buildings.

The units in structure provides information on the housing inventory by subdividing the inventory into one-family homes, apartments, and mobile homes. When the data is used in conjunction with tenure, year structure built, and income, units in structure serves as the basic identifier of housing used in many federal programs. The data also serve to aid in the planning of roads, hospitals, utility lines, schools, playgrounds, shopping centers, emergency preparedness plans, and energy consumption and supplies.

Mobile Home
Both occupied and vacant mobile homes to which no permanent rooms have been added are counted in this category. Mobile homes used only for business purposes or for extra sleeping space and mobile homes for sale on a dealer's lot, at the factory, or in storage are not counted in the housing inventory.

1-Unit, Detached
This is a 1-unit structure detached from any other house, that is, with open space on all four sides. Such structures are considered detached even if they have an adjoining shed or garage. A one-family house that contains a business is considered detached as long as the building has open space on all four sides. Mobile homes to which one or more permanent rooms have been added or built also are included.

1-Unit, Attached
This is a 1-unit structure that has one or more walls extending from ground to roof separating it from adjoining structures. In row houses (sometimes called townhouses), double houses, or houses attached to nonresidential structures, each house is a separate, attached structure if the dividing or common wall goes from ground to roof.

2 or More Apartments
These are units in structures containing 2 or more housing units, further categorized as units in structures with "2, 3 or 4," "5 to 9, 10 to 19," "20 to 49, and 50 or more apartments."

Boat, RV, Van, Etc.
This category is for any living quarters occupied as a housing unit that does not fit the previous categories. Examples that fit this category are houseboats, railroad cars, campers, and vans. Recreational vehicles, boats, vans, tents, railroad cars, and the like are included only if they are occupied as someone's current place of residence.

Question/Concept History
The 1996-1998 American Community Survey question provided the response category, "a mobile home or trailer." Starting in 1999, the ACS response category dropped "or trailer" to read as "a mobile home."

Comparability

Data on units in structure in the 2012 American Community Survey can be compared to previous ACS and Census 2000 units in structure data.

Utilities
The data on utility costs were obtained from Housing Questions 11a through 11d in the 2012 American Community Survey. The questions were asked of occupied housing units. The questions about electricity and gas asked for the monthly costs, and the questions about water/sewer and other fuels (oil, coal, wood, kerosene, etc.) asked for the yearly costs.

Costs are recorded if paid by or billed to occupants, a welfare agency, relatives, or friends. Costs that are paid by landlords, included in the rent payment, or included in condominium or cooperative fees are excluded.

The cost of utilities provides information on the cost of either home ownership or renting. When the data is used as part of monthly housing costs and in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance in forecasting future utility services and energy supplies.

Question/Concept History

The American Community Survey questions ask for monthly costs for electricity and gas, and yearly costs for water/sewer and other fuels. Since 1999, the words "or mobile home" were added to each question, and Question 11b, which asked "Last month, what was the cost of gas for this house, apartment, or mobile home?" had an additional response category, "included in electricity payment entered above."

Limitation of the Data

Research has shown that respondents tended to overstate their expenses for electricity and gas when compared to utility company records. There is some evidence that this overstatement is reduced when yearly costs are asked rather than monthly costs. Caution should be exercised in using these data for direct analysis because costs are not reported for certain kinds of units such as renter-occupied units with all utilities included in the rent and owner-occupied condominium units with utilities included in the condominium fee.

Comparability

Data on utility costs in the 2012 American Community Survey can be compared to previous ACS and Census 2000 utility costs data.

Vacancy Status
The data on vacancy status were obtained only for a sample of cases in the computer-assisted personal interview (known as "CAPI") follow-up by field representatives. Data on vacancy status were obtained at the time of the personal visit. Vacancy status and other characteristics of vacant units were determined by field representatives obtaining information from landlords, owners, neighbors, rental agents, and others.

Vacancy status has long been used as a basic indicator of the housing market and provides information on the stability and quality of housing for certain areas. The data is used to assess the demand for housing, to identify housing turnover within areas, and to better understand the population within the housing market over time. These data also serve to aid in the development of housing programs to meet the needs of persons at different economic levels.

Vacant units are subdivided according to their housing market classification as follows:

For Rent - These are vacant units offered "for rent," and vacant units offered either "for rent" or "for sale."

Rented, Not Occupied - These are vacant units rented but not yet occupied, including units where money has been paid or agreed upon, but the renter has not yet moved in.

For Sale Only - These are vacant units being offered "for sale only," including units in cooperatives and condominium projects if the individual units are offered "for sale only." If units are offered either "for rent" or "for sale" they are included in the "for rent" classification.

Sold, Not Occupied - These are vacant units sold but not yet occupied, including units that have been sold recently, but the new owner has not yet moved in.

For Seasonal, Recreational, or Occasional Use - These are vacant units used or intended for use only in certain seasons or for weekends or other occasional use throughout the year. Seasonal units include those used for summer or winter sports or recreation, such as beach cottages and hunting cabins. Seasonal units also may include quarters for such workers as herders and loggers. Interval ownership units, sometimes called shared-ownership or timesharing condominiums, also are included here.

For Migrant Workers - These include vacant units intended for occupancy by migratory workers employed in farm work during the crop season. (Work in a cannery, a freezer plant, or a food-processing plant is not farm work.)

Other Vacant - If a vacant unit does not fall into any of the categories specified above, it is classified as "Other vacant." For example, this category includes units held for occupancy by a caretaker or janitor, and units held for personal reasons of the owner.

Homeowner Vacancy Rate - The homeowner vacancy rate is the proportion of the homeowner inventory that is vacant "for sale." It is computed by dividing the number of vacant units "for sale only" by the sum of the owner-occupied units, vacant units that are "for sale only," and vacant units that have been sold but not yet occupied, and then multiplying by 100. This measure is rounded to the nearest tenth.

Rental Vacancy Rate - The rental vacancy rate is the proportion of the rental inventory that is vacant "for rent." It is computed by dividing the number of vacant units "for rent" by the sum of the renter-occupied units, vacant units that are "for rent," and vacant units that have been rented but not yet occupied, and then multiplying by 100. This measure is rounded to the nearest tenth.

Available Housing Vacancy Rate - The proportion of the housing inventory that is vacant- for-sale only and vacant-for-rent. It is computed by dividing the sum of vacant-for-sale only housing units and vacant-for-rent housing units, by the sum of occupied units, vacant-for-sale only housing units, vacant-sold-not occupied housing units, vacant-for-rent housing units, and vacant-rented-not-occupied housing units, and then multiplying by 100. This measure is rounded to the nearest tenth.

Question/Concept History - The 1996-2004 American Community Survey and Census 2000 used a single vacancy status category for units that were either "Rented or sold, not occupied." Since the 2005 ACS, there have been two separate categories, "Rented, not occupied" and "Sold, not occupied." This change created consistency among the ACS, the Housing Vacancy Survey, and the 2010 Census vacancy status response options. The revised categories were incorporated in the calculations of the rental vacancy rate and the homeowner vacancy rate.

Comparability - Caution should be used when comparing vacancy status data between the American Community Survey and Census 2000. The tabulation category "Rented or sold, not occupied" in Census 2000 is separated into the two categories "Rented, not occupied" and "Sold, not occupied" in the ACS.

Vacant - Current Residence Elsewhere
A housing unit occupied at the time of interview entirely by people who will be there for 2 months or less.In Computer-Assisted Telephone Interviews (CATI) and Computer-Assisted Personal Interviews (CAPI), the data for current residence elsewhere were obtained after creating the roster of people staying at the sample unit and after asking the current residence questions. Temporarily occupied units are sample units occupied at the time of interview entirely by people who will be there for 2 months or less. At sample units where all the people are staying less than 2 months, the respondent is asked a subset of the questions from the housing section, including the question on vacancy status.

The current residence concept is unique to the American Community Survey. By using the current residence to decide for whom to collect survey information, the ACS can provide a more accurate description of an area's social and economic characteristics. Most surveys, as well as the decennial census, use the concept of usual residence. Usual residence is defined as the place where a person lives and sleeps most of the time. The census defines everyone as having only one usual residence.

Comparability

Caution should be used when comparing vacant-current residence elsewhere data between the American Community Survey and Census 2000.

Vacant Housing Units
See Living Quarters.

The data on value (also referred to as "price asked" for vacant units) were obtained from Housing Question 16 in the 2012 American Community Survey. The question was asked at housing units that were owned, being bought, vacant for sale, or sold not occupied at the time of the survey. Value is the respondent's estimate of how much the property (house and lot, mobile home and lot, or condominium unit) would sell for if it were for sale. If the house or mobile home was owned or being bought, but the land on which it sits was not, the respondent was asked to estimate the combined value of the house or mobile home and the land. For vacant units, value was the price asked for the property. Value was tabulated separately for all owner-occupied and vacant-for-sale housing units, as well as owner- occupied and vacant-for-sale mobile homes.

The value of a home provides information on neighborhood quality, housing affordability, and wealth. These data provide socioeconomic information not captured by household income and comparative information on the state of local housing markets. The data also serve to aid in the development of housing programs designed to meet the housing needs of persons at different economic levels.

Median and Quartile Value
The median divides the value distribution into two equal parts: one-half of the cases falling below the median value of the property (house and lot, mobile home and lot, or condominium unit) and one-half above the median. Quartiles divide the value distribution into four equal parts. Median and quartile value are computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.)

Median and quartile value calculations are rounded to the nearest hundred dollars. Upper and lower quartiles can be used to note large value differences among various geographic areas. (For more information on medians and quartiles, see "Derived Measures.")

Aggregate Value
Aggregate value is calculated by adding all of the value estimates for owner occupied housing units in an area. Aggregate value is rounded to the nearest hundred dollars. (For more information on aggregates, see "Derived Measures.")

Question/Concept History

The 1996-1998 American Community Survey question provided a space for the respondent to enter a dollar amount. From 1999-2007 the question provided 19 pre-coded response categories from "Less than $10,000" to "$250,000 or more - Specify." Starting in 2004, value was shown for all owner-occupied housing units, unlike from1996-2003 in which value was shown only for specified owner-occupied housing units. Changes introduced in 2008 were removing the pre-coded response categories and adding a write-in box for the respondent to enter the property value amount in dollars, and revising the wording of the question to ask, "About how much do you think this house and lot, apartment, or mobile home (and lot, if owned) would sell for if it were for sale?"

Limitation of the Data

The Census Bureau tested the changes introduced to the 2008 version of the value question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Property Value" on the ACS website (http://www.census.gov/acs).

Comparability

Caution should be used when comparing American Community Survey data on value from the years 2008 and after with pre-2008 ACS data. Changes made to the value question between the 2007 and 2008 ACS involving the response option may have resulted in an inconsistency in the value distribution for some areas. In 2007 and previous years, the ACS value question included categorical response options with a write-in for values over $250,000. Beginning in 2008, the response option became solely a write-in.

Caution should also be used when comparing value data from the ACS produced in 2008 or later with Census 2000 value data. The 2008 or later ACS provides solely a write-in response option while Census 2000 collected data in categories. Additionally, Census 2000 tables on value were released for both total owner-occupied housing units and specified owner-occupied housing units, thus comparisons can be made only when comparing the same universes between the two data sets.

Vehicles Available
The data on vehicles available were obtained from Housing Question 9 in the 2012 American Community Survey. The question was asked at occupied housing units. These data show the number of passenger cars, vans, and pickup or panel trucks of one-ton capacity or less kept at home and available for the use of household members. Vehicles rented or leased for one month or more, company vehicles, and police and government vehicles are included if kept at home and used for non-business purposes. Dismantled or immobile vehicles are excluded. Vehicles kept at home but used only for business purposes also are excluded.

The availability of vehicles provides information for numerous transportation programs. When the data is used in conjunction with place-of-work and journey-to-work data, the information can provide insight into vehicle travel and aid in forecasting future travel and its effect on transportation systems. The data also serve to aid in the development of emergency and evacuation planning, special transportation services, and forecasting future energy consumption and needs.

Question/Concept History

The 1996-1998 American Community Survey question provided a space for the respondent to enter the number of vehicles. Since 1999, the American Community Survey question provided seven pre-coded response categories ranging from "None" to "6 or more."

Comparability

Data on vehicle availability in the 2012 American Community Survey can be compared to previous ACS and Census 2000 vehicle availability data.

Year Householder Moved into Unit
The data on year householder moved into unit were obtained from answers to Housing Question 3 in the 2012 American Community Survey, which was asked at occupied housing units. These data refer to the year of the latest move by the householder. If the householder moved back into a housing unit he or she previously occupied, the year of the latest move was reported. If the householder moved from one apartment to another within the same building, the year the householder moved into the present apartment was reported. The intent is to establish the year the present occupancy by the householder began. The year that the householder moved in is not necessarily the same year other members of the household moved in, although in the great majority of cases an entire household moves at the same time.

The year the householder moved into the unit provides information on the specific period of time when mobility occurs, especially for recent movers. These data help to measure neighborhood stability and to identify transient communities. The data also is used to assess the amount of displacement caused by floods and other natural disasters, and as an aid to evaluate the changes in service requirements.

Median Year Householder Moved into Unit
Median year householder moved into unit divides the distribution into two equal parts: one-half of the cases falling below the median year householder moved into unit and one-half above the median. Median year householder moved into unit is computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) Median year householder moved into unit is rounded to the nearest calendar year. (For more information on medians, see "Derived Measures.")

Question/Concept History

Since 1996, the question provided two write-in spaces for the respondent to enter month and year the householder (person 1) moved into the house, apartment, or mobile home.

Comparability

Data on year householder moved into unit in the 2012American Community Survey can be compared to previous ACS and Census 2000 year householder moved into unit data.

Year Structure Built
The data on year structure built were obtained from Housing Question 2 in the 2012 American Community Survey. The question was asked at both occupied and vacant housing units. Year structure built refers to when the building was first constructed, not when it was remodeled, added to, or converted. Housing units under construction are included as vacant housing if they meet the housing unit definition, that is, all exterior windows, doors, and final usable floors are in place. For mobile homes, houseboats, RVs, etc., the manufacturer's model year was assumed to be the year built. The data relate to the number of units built during the specified periods that were still in existence at the time of interview.

The year the structure was built provides information on the age of housing units. These data help identify new housing construction and measures the disappearance of old housing from the inventory, when used in combination with data from previous years. The data also serve to aid in the development of formulas to determine substandard housing and provide assistance in forecasting future services, such as energy consumption and fire protection.

Median Year Structure Built
Median year structure built divides the distribution into two equal parts: one-half of the cases falling below the median year structure built and one-half above the median. Median year structure built is computed on the basis of a standard distribution. (See the "Standard Distributions" section in Appendix A.) The median is rounded to the nearest calendar year. Median age of housing can be obtained by subtracting median year structure built from survey year. For example, if the median year structure built is 1969, the median age of housing in that area is 43 years (2012 minus 1969). (For more information on medians, see "Derived Measures.")

Question/Concept History

The 1996-1998 American Community Survey question provided a write-in space for the respondent to enter a year the structure was built. From 1999-2007 the question provided 9 pre-coded response categories, which showed ranges of years, and from 2003-2007 the response categories were updated to provide detail for recently built structures. Starting in 2008, the response category "2000 or later" and the instruction "Specify yeaf with a write-in box replaced the two categories "2000 to 2004" and "2005 or later."

Limitation of the Data

Data on year structure built are more susceptible to errors of response and non-reporting than data for many other questions because respondents must rely on their memory or on estimates by people who have lived in the neighborhood a long time.

Comparability

Data on year structure built in the 2012 American Community Survey can be compared to previous ACS and Census 2000 year structure built data.

Population Variables
Ability to Speak English
Respondent's Ability to Speak English
Respondents who reported speaking a language other than English (question 14a in the 2012 American Community Survey) were asked to indicate their English-speaking ability (question 14c in the 2012 American Community Survey) based on one of the following categories: "Very well," "Well," "Not well," or "Not at all." Those who answered "Well," "Not well," or "Not at all" are sometimes referred as "Less than 'very well.'" Respondents were not instructed on how to interpret the response categories in this question.

Households in which no one 14 and over speaks English only or speaks a language other than English at home and speaks English "very well"
This variable identifies households that may need English language assistance. This arises when no one 14 and over meets either of two conditions

(1) they speak English at home or

(2) even though they speak another language, they also report that they speak English "very well."

After data are collected for each person in the household, this variable checks if all people 14 years old and older speak a language other than English. If so, the variable checks the English-speaking ability responses to see if all people 14 years old and older speak English "Less than 'very well.'" If all household members 14 and over speak a language other than English and speak English "Less than 'very well,'" the household is considered part of this group that may be in need of English language assistance. All members of a household were identified in this group, including members under 14 years old who may have spoken only English.
Government agencies use information on language spoken at home for their programs that serve the needs of the foreign-born and specifically those who have difficulty with English. Under the Voting Rights Act, language is needed to meet statutory requirements for making voting materials available in minority languages. The Census Bureau is directed, using data about language spoken at home and the ability to speak English, to identify minority groups that speak a language other than English and to assess their English-speaking ability. The U.S. Department of Education uses these data to prepare a report to Congress on the social and economic status of children served by different local school districts.

Government agencies use information on language spoken at home for their programs that serve the needs of the foreign-born and specifically those who have difficulty with English. Under the Voting Rights Act, language is needed to meet statutory requirements for making voting materials available in minority languages. The Census Bureau is directed, using data about language spoken at home and the ability to speak English, to identify minority groups that speak a language other than English and to assess their English-speaking ability. The U.S. Department of Education uses these data to prepare a report to Congress on the social and economic status of children served by different local school districts. State and local agencies concerned with aging develop health care and other services tailored to the language and cultural diversity of the elderly under the Older Americans Act.

Question/Concept History

The English Language Ability question has been the same since the beginning of ACS. "Households in which no one 14 and over speaks English only or speaks a language other than English and speaks English 'very well'" has been calculated the same way in all years of ACS data collection, but has sometimes been termed "Linguistic Isolation."

Limitation of the Data

Ideally, the data on ability to speak English represented a person's perception of their own English-speaking ability. However, because one household member usually completes American Community Survey questionnaires, the responses may have represented the perception of another household member.

Comparability

All years of ACS language data are comparable to each other. They are also comparable to Census data from 1980, 1990 and 2000. Though the term "Linguistic Isolation" is no longer used, data under this heading may still be compared.

The data on age were derived from answers to Question 4 in the 2012 American Community Survey. The age classification is based on the age of the person in complete years at the time of interview. Both age and date of birth are used in combination to calculate the most accurate age at the time of the interview. Respondents are asked to give an age in whole, completed years as of interview date as well as the month, day and year of birth. People are not to round an age up if the person is close to having a birthday, and to estimate an age if the exact age is not known. An additional instruction on babies also asks respondents to print "0" for babies less than one year old. Inconsistently reported and missing values are assigned or imputed based on the values of other variables for that person, from other people in the household, or from people in other households ("hot deck" imputation).

Age is asked for all persons in a household or group quarters. On the mailout/mailback paper questionnaire for households, both age and date of birth are asked for persons listed as person numbers 1-5 on the form. Only age (in years) is initially asked for persons listed as 6-12 on the mailout/mailback paper questionnaire. If a respondent indicates that there are more than 5 people living in the household, then the household is eligible for Failed Edit Follow-up (FEFU). During FEFU operations, telephone center staffers call respondents to obtain missing data. This includes asking date of birth for any person in the household missing date of birth information. In Computer Assisted Telephone Interviews (CATI) and Computer Assisted Personal Interview (CAPI) instruments both age and date of birth is asked for all persons. In 2006, the ACS began collecting data in group quarters (GQs). This included asking both age and date of birth for persons living in a group quarters. For additional data collection methodology, please see http://www.census.gov/acs.

Data on age are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. Age data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Age is central for any number of federal programs that target funds or services to children, working-age adults, women of childbearing age, or the older population. The U.S. Department of Education uses census age data in its formula for allotment to states. The U.S. Department of Veterans Affairs uses age to develop its mandated state projections on the need for hospitals, nursing homes, cemeteries, domiciliary services, and other benefits for veterans. For more information on the use of age data in Federal programs, please see http://www.census.gov/acs.

Median Age
The median age is the age that divides the population into two equal-size groups. Half of the population is older than the median age and half is younger. Median age is based on a standard distribution of the population by single years of age and is shown to the nearest tenth of a year. (See the sections on "Standard Distributions" and "Medians" under "Derived Measures.")

Age Dependency Ratio
The age dependency ratio is derived by dividing the combined under 18 years and 65 years and over populations by the 18-to-64 population and multiplying by 100.

Old-Age Dependency Ratio
The old-age dependency ratio is derived by dividing the population 65 years and over by the 18-to-64 population and multiplying by 100.

Child Dependency Ratio
The child dependency ratio is derived by dividing the population under 18 years by the 18-to-64 population, and multiplying by 100.

Question/Concept History

The 1996-2002 American Community Survey question asked for month, day, and year of birth before age. Since 2003, the American Community Survey question asked for age, followed by month, day, and year of birth. In 2008, an additional instruction was provided with the age and date of birth question on the American Community Survey questionnaire to report babies as age 0 when the child was less than 1 year old. The addition of this instruction occurred after 2005 National Census Test results indicated increased accuracy of age reporting for babies less than one year old.

Limitation of the Data

Beginning in 2006, the population living in group quarters (GQ) was included in the American Community Survey population universe. Some types of group quarters have populations with age distributions that are very different from that of the household population. The inclusion of the GQ population could therefore have a noticeable impact on the age distribution for a given geographic area. This is particularly true for areas with a substantial GQ population. For example, in areas with large colleges and universities, the percent of individuals 18-24 would increase due to the inclusion of GQs in the American Community Survey universe.

Comparability

Caution should be taken when comparing population in age groups across time. The entire population continually ages into older age groups over time, and babies fill in the youngest age group. Therefore, the population of a certain age is made up of a completely different group of people in one time period than in another (e.g. one age group in 2000 versus same age group in 2012). Since populations occasionally experience booms/increases and busts/decreases in births, deaths, or migration (for example, the postwar Baby Boom from 1946-1964), one should not necessarily expect that the population in an age group in one year should be similar in size or proportion to the population in the same age group in a different period in time. For example, Baby Boomers were age 36 to 54 in Census 2000 while they were age 47 to 65 in the 2012 ACS. The age structure and distribution would therefore shift in those age groups to reflect the change in people occupying those age- specific groups over time.

Data users should also be aware of methodology differences that may exist between different data sources if they are comparing American Community Survey age data to data sources, such as Population Estimates or Decennial Census data. For example, the American Community Survey data are that of a respondent-based survey and subject to various quality measures, such as sampling and nonsampling error, response rates and item allocation error. This differs in design and methodology from other data sources, such as Population Estimates, which is not a survey and involves computational methodology to derive intercensal estimates of the population. While ACS estimates are controlled to Population Estimates for age at the nation, state and county levels of geography as part of the ACS weighting procedure, variation may exist in the age structure of a population at lower levels of geography when comparing different time periods or comparing across time due to the absence of controls below the county geography level. For more information on American Community Survey data accuracy and weighting procedures, please see http://www.census.gov/acs.

It should also be noted that although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns, and estimates of housing units for states and counties (http://factfinder2.census.gov).

Ancestry
Ancestry refers to a person's ethnic origin, heritage, descent, or "roots," which may reflect their place of birth or that of previous generations of their family. Some ethnic identities, such as "Egyptian" or "Polish" can be traced to geographic areas outside the United States, while other ethnicities such as "Pennsylvania German" or "Cajun" evolved in the United States.

The intent of the ancestry question was not to measure the degree of attachment the respondent had to a particular ethnicity, but simply to establish that the respondent had a connection to and self-identified with a particular ethnic group. For example, a response of "Irish" might reflect total involvement in an Irish community or only a memory of ancestors several generations removed from the individual.

The data on ancestry were derived from answers to Question 13 in the 2012 American Community Survey. The question was based on self-identification; the data on ancestry represent self-classification by people according to the ancestry group(s) with which they most closely identify.

The Census Bureau coded the responses into a numeric representation of over 1,000 categories. To do so, responses initially were processed through an automated coding system; then, those that were not automatically assigned a code were coded by individuals trained in coding ancestry responses. The code list reflects the results of the Census Bureau's own research and consultations with many ethnic experts. Many decisions were made to determine the classification of responses. These decisions affected the grouping of the tabulated data. For example, the "Indonesian" category includes the responses of "Indonesian," "Celebesian," "Moluccan," and a number of other responses.

The ancestry question allowed respondents to report one or more ancestry groups. Generally, only the first two responses reported were coded. If a response was in terms of a dual ancestry, for example, "Irish English," the person was assigned two codes, in this case one for Irish and another for English. However, in certain cases, multiple responses such as "French Canadian," "Scotch-Irish," "Greek Cypriot," and "Black Dutch" were assigned a single code reflecting their status as unique groups. If a person reported one of these unique groups in addition to another group, for example, "Scotch-Irish English," resulting in three terms, that person received one code for the unique group (Scotch-Irish) and another one for the remaining group (English). If a person reported "English Irish French," only English and Irish were coded. If there were more than two ancestries listed and one of the ancestries was a part of another, such as "German Bavarian Hawaiian," the responses were coded using the more detailed groups (Bavarian and Hawaiian).

The Census Bureau accepted "American" as a unique ethnicity if it was given alone or with one other ancestry. There were some groups such as "American Indian," "Mexican American," and "African American" that were coded and identified separately.

The ancestry question is asked for every person in the American Community Survey, regardless of age, place of birth, Hispanic origin, or race.
Ancestry identifies the ethnic origins of the population, and Federal agencies regard this information as essential for fulfilling many important needs. Ancestry is required to enforce provisions under the Civil Rights Act, which prohibits discrimination based upon race, sex, religion, and national origin. More generally, these data are needed to measure the social and economic characteristics of ethnic groups and to tailor services to accommodate cultural differences. The Department of Labor draws samples for surveys that provide employment statistics and other related information for ethnic groups using ancestry.

The ACS data on ancestry are released annually on the Census Bureau's Internet site (http://www.census.gov). The Detailed Tables (B04001-B04006) contain estimates of over 100 different ancestry groups for the nation, states, and many other geographic areas, while the Special Population Profiles contain characteristics of different ancestry groups.

In all tabulations, when respondents provided an unclassifiable ethnic identity (for example, "multi-national," "adopted," or "I have no idea"), the answer was included in "Unclassified or not reported."

The tabulations on ancestry show two types of data- one where estimates represent the number of people, and the other where estimates represent the number of responses. If you want to know how many people reported an ancestry, use the estimates based on people. If you want to know how many reports there were of a certain ancestry, use the estimates based on reports. The difference between the two types of data presentations represents the fact that people can provide more than one ancestry, and therefore can be counted twice in the same ancestry category. Examples are provided below.

The following are the types of estimates shown:

Estimates Based on People
People Reporting Single Ancestry
Includes all people who reported only one ethnic group such as "German." Also included in this category are people with only a multiple- term response such as "Scotch-Irish" who are assigned a single code because they represent one distinct group. For example, in this type of table, the count for German would be interpreted as "The number of people who reported that German was their only ancestry."

People Reporting Multiple Ancestries
Includes all people who reported more than one group, such as "German" and "Irish" and were assigned two ancestry codes. The German line on this table would be interpreted as "The number of people who responded that German was part of their multiple ancestry."

People Reporting Ancestry
Includes all people who reported each ancestry, regardless of whether it was their first or second ancestry, or part of a single or multiple response. This estimate is the sum of the two estimates above (for Single and Multiple ancestry). People can be listed twice in this table. For example, if someone reports their ancestry as "German and Danish," they will be listed once in German and once in Danish, and therefore the sum of the rows would not equal the total population. Interpret the German line of this table as "The total number of people who reported they had German ancestry."

Estimates Based on Responses
First Ancestry Reported
Includes the first response of all people who reported at least one codeable entry. For example, in this type of table, the count for German would include all those who reported only German and those who reported German first and then some other group. The German line of this table could be interpreted as, "The number of times German was listed as the first, or only, ancestry."

Second Ancestry Reported
Includes the second response of all people who reported a multiple ancestry. Thus, the count for German in this category includes all people who reported German as the second response, regardless of the first response provided. The German line in this table is interpreted as, "The number of times German was listed as a second ancestry."

Total Ancestries Reported
Includes the total number of ancestries reported and coded. If a person reported a multiple ancestry such as "German Danish," that response was counted twice in the tabulations--once in the German category and again in the Danish category. Also, if a person reported two different types of German ancestry, such as "Bavarian Hamburger," they would be counted twice in the German category on this type of table. Thus, each line of this table represents the number of reports for that ancestry type, not the number of people (although sometimes that number is the same). Likewise, the sum of the estimates in each of the rows in this type of presentation is not the total population but the total of all responses. The German line in this table is interpreted as "The number of times a German ancestry was reported."

Question/Concept History

The question on ancestry has been asked on the American Community Survey since 1996. The question wording has never changed, although placement of the question changed slightly. Also, the examples listed below the write-in lines changed in 1999, but have remained the same since then.

The question on ancestry was first asked in the 1980 Census. It replaced the question on parental place of birth, in order to include ancestral heritage for people whose families have been in the U.S. for more than two generations. The question also was asked in the 1990 Census and Census 2000.

From 1996 to 1999, the ACS editing system used answers to the race and place of birth questions to clarify ancestry responses of "Indian," where possible. In 2000 and subsequent years, the editing was expanded to aid interpretation of two-word ancestries, such as "Black Irish."

Limitation of the Data

Although some experts consider religious affiliation a component of ethnic identity, the ancestry question was not designed to collect any information concerning religion. The Census Bureau is prohibited from collecting information on religion. Thus, if a religion was given as an answer to the ancestry question, it was coded as an "Other" response.

Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations may have ancestry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the ancestry distribution. This is particularly true for areas with a substantial GQ population.

Comparability

The data are comparable to Census 2000, as long as some caution is used. Response rates to the ancestry question are generally higher for ACS than for Census, and data are never generated for missing ancestry responses, therefore some ancestry groups are reported more heavily in ACS than in Census 2000.

In 2010, there were two major changes to the coding rules. If up to two ancestries were listed, both were coded, even if one was the specific of the other or if one was American. Also, race groups and Hispanic groups were coded with the same priority as non-race andnon-Hispanic groups. For example, "Haitian Black French" would previously have been coded Haitian and French, but now would be coded Haitian and Black.

See the 2012 Code List on the ACS website (http://www.census.gov) for Ancestry Code List.

Children Ever Born
For the 1996-1998 American Community Survey, the data on fertility (also referred to as "children ever born") was asked of all women 15 years old and over regardless of marital status. Stillbirths, stepchildren, and adopted children were excluded from the number of children ever born. Ever-married women were instructed to include all children born to them before and during their most recent marriage, children no longer living, and children living away from home, as well as children who were still living in the home. Never-married women were instructed to include all children born to them. The question on children ever born was asked to measure lifetime fertility experience of women up to the survey date.

Data were most frequently presented in terms of the aggregate number of children ever born to women in the specified category and in terms of the rate per 1,000 women.

Beginning in 1999, American Community Survey data on fertility were derived from questions that asked if the person had given birth in the past 12 months. See the section on "Fertility" for more information.

Question/Concept History

The 1996-1998 American Community Survey used a write-in space for the number and a response category for "None." No question addressed "children ever born" after 1998.

Limitation of the Data

The data available for 1996-1998 are only available for a limited number of geographies.

Comparability

The data on children ever born are comparable to data from the 1990 Census and prior censuses. The data are also comparable to the June supplement to the Current Population Survey.

Citizenship Status (U.S. Citizenship Status)
The data on citizenship status were derived from answers to Question 8 in the 2012 American Community Survey. This question was asked about Persons 1 through 5 in the ACS.

Respondents were asked to select one of five categories:

(1) born in the United States,

(2) born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas,

(3) born abroad of U.S. citizen parent or parents,

(4) U.S. citizen by naturalization, or

(5) not a U.S citizen. Respondents indicating they are a U.S. citizen by naturalization are also asked to print their year of naturalization.

People born in American Samoa, although not explicitly listed, are included in the second response category.

For the Puerto Rico Community Survey, respondents were asked to select one of five categories: (1) born in Puerto Rico, (2) born in a U.S. state, District of Columbia, Guam, the U.S. Virgin Islands, or Northern Marianas, (3) born abroad of U.S. citizen parent or parents, (4) U.S. citizen by naturalization, or (5) not a U.S. citizen. Respondents indicating they are a U.S. citizen by naturalization are also asked to print their year of naturalization. People born in American Samoa, although not explicitly listed, are included in the second response category.


When no information on citizenship status was reported for a person, information for other household members, if available, was used to assign a citizenship status to the respondent. All cases of nonresponse that were not assigned a citizenship status based on information from other household members were allocated the citizenship status of another person with similar characteristics who provided complete information. In cases of conflicting responses, place of birth information is used to edit citizenship status. For example, if a respondent states he or she was born in Puerto Rico but was not a U.S. citizen, the edits use the response to the place of birth question to change the respondent's status to "U.S. citizen at birth."

U.S. Citizen
Respondents who indicated that they were born in the United States, Puerto Rico, a U.S. Island Area (such as Guam), or abroad of American (U.S. citizen) parent or parents are considered U.S. citizens at birth. Foreign-born people who indicated that they were U.S. citizens through naturalization also are considered U.S. citizens.

Not a U.S. Citizen
Respondents who indicated that they were not U.S. citizens at the time of the survey.

Native
The native population includes anyone who was a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were born in the United States, Puerto Rico, a U.S. Island Area (such as Guam), or abroad of American (U.S. citizen) parent or parents.

Foreign born
The foreign-born population includes anyone who was not a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were a U.S. citizen by naturalization or not a U.S. citizen.

The American Community Survey questionnaires do not ask about immigration status. The population surveyed includes all people who indicated that the United States was their usual place of residence on the survey date. The foreign-born population includes naturalized U.S. citizens, lawful permanent residents (i.e. immigrants), temporary migrants (e.g., foreign students), humanitarian migrants (e.g., refugees), and unauthorized migrants (i.e. people illegally present in the United States).

The responses to this question are used to determine the U.S. citizen and non-U.S. citizen populations as well as to determine the native and foreign-born populations.

Question/Concept History

In the 1996-1998 American Community Survey, the third response category was "Yes, born abroad of American parent(s)." However, since 1999 in
the American Community Survey and since the 2005 Puerto Rico Community Survey, the response category was "Yes, born abroad of American parent or parents." In 2008, respondents who indicated that they were a U.S. citizen by naturalization were also asked to print their year of naturalization. Also in 2008, modifications in wording were made to both the third response category (changed from "Yes, born abroad of American parent or parents" to "Yes, born abroad of U.S. citizen parent or parents") and the fifth response category (changed from "No, not a citizen of the United States" to "No, not a U.S. citizen").

Limitation of the Data

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have citizenship status distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the citizenship status distribution. This is particularly true for areas with substantial GQ populations.

Comparability

Citizenship can be compared both across ACS years and to Census 2000 data.

Class of Worker
Class of worker categorizes people according to the type of ownership of the employing organization. Class of worker data were derived from answers to question 41 in the 2012 American Community Survey. Question 41 provides respondents with 8 class of worker categories from which they are to select one. These categories are:

  1. An employee of a private, for-profit company or business, or of an individual, for wages, salary, or commissions.
  2. An employee of a private, not-for-profit, tax-exempt, or charitable organization.
  3. A local government employee (city, county, etc.).
  4. A state government employee.
  5. A Federal government employee.
  6. Self-employed in own not incorporated business, professional practice, or farm.
  7. Self-employed in own incorporated business, professional practice, or farm.
  8. Working without pay in a family business or farm.
These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

The class of worker categories are defined as follows:

Private wage and salary workers
Includes people who worked for wages, salary, commission, tips, pay-in-kind, or piece rates for a private, for-profit employer or a private not-for-profit, tax-exempt or charitable organization. Self-employed people whose business was incorporated are included with private wage and salary workers because they are paid employees of their own companies.

ACS tabulations present data separately for these subcategories: "Employee of private company workers," "Private not-for-profit wage and salary workers," and "Self-employed in own incorporated business workers."

Government workers
Includes people who were employees of any local, state, or Federal governmental unit, regardless of the activity of the particular agency. For ACS tabulations, the data are presented separately for the three levels of government.

Employees of Indian tribal governments, foreign governments, the United Nations, or other formal international organizations controlled by governments were classified as "Federal government workers."

The government categories include all government workers, though government workers may work in different industries. For example, people who work in a public elementary school or city owned bus line are coded as local government class of workers.

Self-employed in own not incorporated business workers
Includes people who worked for profit or fees in their own unincorporated business, profession, or trade, or who operated a farm.

Unpaid family workers
Includes people who worked without pay in a business or on a farm operated by a relative.

Editing Procedures
A computer edit and allocation process excludes all responses that should not be included in the universe and evaluates the consistency of the remaining responses. Class of worker responses are checked for consistency with the industry and occupation data provided for that respondent. Occasionally respondents do not report a response for class of worker, industry, or occupation. Certain types of incomplete entries are corrected using the Alphabetical Index of Industries and Occupations (http://www.census.gov/people/io/methodology/indexes.html). If one or more of the three codes (occupation, industry, or class of worker) is blank after the edit, a code is assigned from a donor respondent who is a "similar" person based on questions such as age, sex, educational attainment, income, employment status, and weeks worked. If all of the labor force and income data are blank, all of these economic questions are assigned from a "similar" person who had provided all the necessary data.

These data are used to formulate policy and programs for employment and career development and training. Companies use these data to decide where to locate new plants, stores, or offices.

Question/Concept History

Class of worker data have been collected during decennial censuses since 1910. Starting with the 2010 Census, class of worker data will no longer be collected during the decennial census. Long form data collection has transitioned to the American Community Survey. The American Community Survey began collecting data on class of worker in 1996. The questions on class of worker were designed to be consistent with the 1990 Census questions on class of worker. The 1996-1998 ACS class of worker question had an additional response category for "Active duty U.S. Armed Forces member." People who marked this category were tabulated as Federal government workers. A check box was added to the employer name questionnaire item in 1999. This check box is to be marked by anyone "now on active duty in the Armed Forces..." This information is used by the industry and occupation coders to assist in assigning proper industry codes for active duty military.

Limitation of the Data

Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have class of worker distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the class of worker distribution in some geographic areas with a substantial GQ population.

Data on occupation, industry, and class of worker are collected for the respondent's current primary job or the most recent job for those who are not employed but have worked in the last 5 years. Other labor force questions, such as questions on earnings or work hours, may have different reference periods and may not limit the response to the primary job. Although the prevalence of multiple jobs is low, data on some labor force items may not exactly correspond to the reported occupation, industry, or class of worker of a respondent.

Comparability

Class of worker categories have remained consistent since the implementation of the American Community Survey in 1996. The 1996-1998 ACS class of worker question had an additional response category for "Active duty U.S. Armed Forces member" in order to assist industry and occupation coders in assigning proper industry codes for active duty military. People who selected this category were tabulated as Federal government workers. Active duty U.S. Armed Forces have been coded as Federal government workers from 1996 to 2011.

See also, Industry and Occupation.

Disability Status
Under the conceptual framework of disability described by the Institute of Medicine (IOM) and the International Classification of Functioning, Disability, and Health (ICF), disability is defined as the product of interactions among individuals' bodies; their physical, emotional, and mental health; and the physical and social environment in which they live, work, or play. Disability exists where this interaction results in limitations of activities and restrictions to full participation at school, at work, at home, or in the community. For example, disability may exist where a person is limited in their ability to work due to job discrimination against persons with specific health conditions; or, disability may exist where a child has difficulty learning because the school cannot accommodate the child's deafness.
Furthermore, disability is a dynamic concept that changes over time as one's health improves or declines, as technology advances, and as social structures adapt. As such, disability is a continuum in which the degree of difficulty may also increase or decrease. Because disability exists along a continuum, various cut-offs are used to allow for a simpler understanding of the concept, the most common of which is the dichotomous "With a disability"/"no disability" differential.

Measuring this complex concept of disability with a short set of six questions is difficult. Because of the multitude of possible functional limitations that may present as disabilities, and in the absence of information on external factors that influence disability, surveys like the ACS are limited to capturing difficulty with only selected activities. As such, people identified by the ACS as having a disability are, in fact, those who exhibit difficulty with specific functions and may, in the absence of accommodation, have a disability. While this definition is different from the one described by the IOM and ICF conceptual frameworks, it relates to the programmatic definitions used in most Federal and state legislation.

In an attempt to capture a variety of characteristics that encompass the definition of disability, the ACS identifies serious difficulty with four basic areas of functioning - hearing, vision, cognition, and ambulation. These functional limitations are supplemented by questions about difficulties with selected activities from the Katz Activities of Daily Living (ADL) and Lawton Instrumental Activities of Daily Living (IADL) scales, namely difficulty bathing and dressing, and difficulty performing errands such as shopping. Overall, the ACS attempts to capture six aspects of disability, which can be used together to create an overall disability measure, or independently to identify populations with specific disability types.

Information on disability is used by a number of federal agencies to distribute funds and develop programs for people with disabilities. For example, data about the size, distribution, and needs of the population with a disability are essential for developing disability employment policy. For the Americans with Disabilities Act, data about functional limitations are important to ensure that comparable public transportation services are available for all segments of the population. Federal grants are awarded, under the Older Americans Act, based on the number of elderly people with physical and mental disabilities.

Question/Concept History

In the 2012 American Community Survey, disability concepts were asked in questions 17 through 19. Question 17 had two subparts and was asked of all persons regardless of age. Question 18 had three subparts and was asked of people age 5 years and older. Question 19 was asked of people age 15 years and older.

Hearing difficulty
was derived from question 17a, which asked respondents if they were "deaf or ... [had] serious difficulty hearing." Vision difficulty was derived from question 17b, which asked respondents if they were "blind or ... [had] serious difficulty seeing even when wearing glasses." Prior to the 2008 ACS, hearing and vision difficulty were asked in a single question under the label "Sensory disability."

Cognitive difficulty
was derived from question 18a, which asked respondents if due to physical, mental, or emotional condition, they had "serious difficulty concentrating, remembering, or making decisions." Prior to the 2008 ACS, the question on cognitive functioning asked about difficulty "learning, remembering, or concentrating" under the label "Mental disability."

Ambulatory difficulty
was derived from question 18b, which asked respondents if they had "serious difficulty walking or climbing stairs." Prior to 2008, the ACS asked if respondents had "a condition that substantially limits one or more basic physical activities such as walking, climbing stairs, reaching, lifting, or carrying." This measure was labeled "Physical difficulty" in ACS data products.

Self-care difficulty
was derived from question 18c, which asked respondents if they had "difficulty dressing or bathing." Difficulty with these activities are two of six specific Activities of Daily Living (ADLs) often used by health care providers to assess patients' self- care needs. Prior to the 2008 ACS, the question on self-care limitations asked about difficulty "dressing, bathing, or getting around inside the home," under the label "Self-care disability."

Independent living difficulty
was derived from question 19, which asked respondents if due to a physical, mental, or emotional condition, they had difficulty "doing errands alone such as visiting a doctor's office or shopping." Difficulty with this activity is one of several Instrumental Activities of Daily Living (IADL) used by health care providers in making care decisions. Prior to the 2008 ACS, a similar measure on difficulty "going outside the home alone to shop or visit a doctor's office" was asked under the label "Go-outside-home disability."

Disability status is determined from the answers from these six types of difficulty. For children under 5 years old, hearing and vision difficulty are used to determine disability status. For children between the ages of 5 and 14, disability status is determined from hearing, vision, cognitive, ambulatory, and self-care difficulties. For people aged 15 years and older, they are considered to have a disability if they have difficulty with any one of the six difficulty types.

Limitation of the Data

The universe for most disability data tabulations is the civilian noninstitutionalized population. Some types of GQ populations have disability distributions that are different from the household population. The inclusion of the noninstitutionalized GQ population could therefore have a noticeable impact on the disability distribution. This is particularly true for areas with a substantial noninstitutionalized GQ population. For a discussion of the effect of group quarters data has on estimates of disability status, see "Disability Status and the Characteristics of People in Group Quarters: A Brief Analysis of Disability Prevalence among the Civilian Noninstitutionalized and Total Populations in the American Community Survey" (http://www.census.gov/people/disability/files/GQdisability.pdf).

Comparability

Beginning in 2008, questions on disability represent a conceptual and empirical break from earlier years of the ACS. Hence, the Census Bureau does not recommend any comparisons of 2012 disability data to 2007 and earlier ACS disability data. Research suggests that combining the new separate measures of hearing and vision difficulty to generate a sensory difficulty measure does not create a comparable estimate to the old Sensory disability estimates in prior ACS products. Likewise, the cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty measures are based on different sets of activities and different question wordings from similar measures in ACS questionnaires prior to 2008 and thus should not be compared. Because the overall measure of disability status beginning in 2008 is based on different measures of difficulty, these estimates should also not be compared to prior years. For additional information on the differences between the ACS disability questions beginning in 2008 and prior ACS disability questions, see "Review of Changes to the Measurement of Disability in the 2008 American Community Survey" (http://www.census.gov/people/disability/files/2008ACS_disability.pdf).

The 2012 disability estimates should also not be compared with disability estimates from Census 2000 for reasons similar to the ones made above. ACS disability estimates should also not be compared with more detailed measures of disability from sources such as the National Health Interview Survey and the Survey of Income and Program Participation.

The 2012 ACS disability estimates are comparable with the ACS disability estimates from 2008, 2009, 2010, and 2011.

Educational Attainment
Educational attainment data are needed for use in assessing the socioeconomic condition of the U.S. population. Government agencies also require these data for funding allocations and program planning and implementation. These data are needed to determine the extent of illiteracy rates of citizens in language minorities in order to meet statutory requirements under the Voting Rights Act. Based on data about educational attainment, school districts are allocated funds to provide classes in basic skills to adults who have not completed high school.

Data on educational attainment were derived from answers to Question 11 on the 2012 American Community Survey, which was asked of all respondents. Educational attainment data are tabulated for people 18 years old and over. Respondents are classified according to the highest degree or the highest level of school completed. The question included instructions for persons currently enrolled in school to report the level of the previous grade attended or the highest degree received.

The educational attainment question included a response category that allowed people to report completing the 12th grade without receiving a high school diploma. Respondents who received a regular high school diploma and did not attend college were instructed to report "Regular high school diploma." Respondents who received the equivalent of a high school diploma (for example, passed the test of General Educational Development (G.E.D.)), and did not attend college, were instructed to report "GED or alternative credential." "Some college" is in two categories: "Some college credit, but less than 1 year of college credit" and "1 or more years of college credit, no degree." The category "Associate's degree" included people whose highest degree is an associate's degree, which generally requires 2 years of college level work and is either in an occupational program that prepares them for a specific occupation, or an academic program primarily in the arts and sciences. The course work may or may not be transferable to a bachelor's degree. Master's degrees include the traditional MA and MS degrees and field-specific degrees, such as MSW, MEd, MBA, MLS, and MEng. Instructions included in the respondent instruction guide for mailout/mailback respondents only provided the following examples of professional school degrees: medicine, dentistry, chiropractic, optometry, osteopathic medicine, pharmacy, podiatry, veterinary medicine, law, and theology. The order in which degrees were listed suggested that doctorate degrees were "higher" than professional school degrees, which were "higher" than master's degrees. If more than one box was filled, the response was edited to the highest level or degree reported.

The instructions further specified that schooling completed in foreign or ungraded school systems should be reported as the equivalent level of schooling in the regular American system. The instructions specified that certificates or diplomas for training in specific trades or from vocational, technical or business schools were not to be reported. Honorary degrees awarded for a respondent's accomplishments were not to be reported.

High School Graduate or Higher
This category includes people whose highest degree was a high school diploma or its equivalent, people who attended college but did not receive a degree, and people who received an associate's, bachelor's, master's, or professional or doctorate degree. People who reported completing the 12th grade but not receiving a diploma are not included.

Not Enrolled, Not High School Graduate
This category includes people of compulsory school attendance age or above who were not enrolled in school and were not high school graduates. These people may be referred to as "high school dropouts." There is no restriction on when they "dropped out" of school; therefore, they may have dropped out before high school and never attended high school.

Question/Concept History

Since 1999, the American Community Survey question does not have the response category for "Vocational, technical, or business school degree" that the 1996-1998 American Community Surveys question had. Starting in 1999, the American Community Survey question had two categories for some college: "Some college credit, but less than 1 year" and "1 or more years of college, no degree." The 1996-1998 American Community Survey question had one category: "Some college but no degree."

In the 1996-1998 American Community Survey, the educational attainment question was used to estimate level of enrollment. Since 1999, a question regarding grade of enrollment was included.

The 1999-2007 American Community Survey attainment question grouped grade categories below high school into the following three categories: "Nursery school to 4th grade," "5th grade or 6th grade," and "7th grade or 8 grade." The 1996-1998 American Community Survey question allowed a write-in for highest grade completed for grades 1-11 in addition to "Nursery or preschool" and "Kindergarten."

Beginning in 2008, the American Community Survey attainment question was changed to the following categories for levels up to "Grade 12, no diploma," "Nursery school," "Kindergarten," "Grade 1 through grade 11," and "12th grade, no diploma." The survey question allowed a write-in for the highest grade completed for grades 1-11. In addition, the category that was previously "High school graduate (including GED)" was broken into two categories: "Regular high school diploma" and "GED or alternative credential." The term "credit" for the two some college categories was emphasized. The phrase "beyond a bachelor's degree" was added to the professional degree category.

Limitation of the Data

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have educational attainment distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the educational attainment distribution. This is particularly true for areas with a substantial GQ population.

The Census Bureau tested the changes introduced to the 2008 version of the educational attainment question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Educational Attainment" on the ACS website (http://www.census.gov/acs).

Comparability

New questions were added to the 2008 ACS Computer-Assisted Telephone Interview (CATI) and Computer-Assisted Personal Interview (CAPI) instruments. Respondents who received a high school diploma, GED or equivalent were also asked if they had completed any college credit. Therefore, data users may notice a decrease in the number of high school graduates relative to previous years because those people are now being captured in the "Some college credit, but less than 1 year of college credit" or "1 or more years of college credit, no degree" categories. For more information, see the report titled Report P.2.b: "Evaluation Report Covering Educational Attainment" on the ACS website (http://www.census.gov/acs).

Data about educational attainment are also collected from the decennial Census and from the Current Population Survey (CPS). ACS data is generally comparable to data from the Census. For more information about the comparability of ACS and CPS data, please see the Educational Attainment Fact Sheet and the Comparison Report from the CPS Educational Attainment page on the ACS website (http://www.census.gov/acs).

Employment Status
The data on employment status were derived from Questions 29 and 35 to 37 in the 2012 American Community Survey. (In the 1999-2002 American Community Survey, data were derived from Questions 22 and 28 to 30; in the 1996-1998 American Community Survey, data were derived from Questions 21 and 28 to 30.) The questions were asked of all people 15 years old and over. The series of questions on employment status was designed to identify, in this sequence: (1) people who worked at any time during the reference week; (2) people on temporary layoff who were available for work; (3) people who did not work during the reference week but who had jobs or businesses from which they were temporarily absent (excluding layoff); (4) people who did not work during the reference week, but who were looking for work during the last four weeks and were available for work during the reference week; and (5) people not in the labor force. (For more information, see the discussion under "Reference Week.")

The employment status data shown in American Community Survey tabulations relate to people 16 years old and over.

Employment status is key to understanding work and unemployment patterns and the availability of workers. Based on labor market areas and unemployment levels, the U.S. Department of Labor identifies service delivery areas and determines amounts to be allocated to each for job training. The impact of immigration on the economy and job markets is determined partially by labor force data, and this information is included in required reports to Congress. The Office of Management and Budget, under the Paperwork Reduction Act, uses data about employed workers as part of the criteria for defining metropolitan areas. The Bureau of Economic Analysis uses this information, in conjunction with other data, to develop its state per capita income estimates used in the allocation formulas and eligibility criteria for many federal programs such as Medicaid.

Employed
This category includes all civilians 16 years old and over who either (1) were "at work," that is, those who did any work at all during the reference week as paid employees, worked in their own business or profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm or in a family business; or (2) were "with a job but not at work," that is, those who did not work during the reference week but had jobs or businesses from which they were temporarily absent due to illness, bad weather, industrial dispute, vacation, or other personal reasons. Excluded from the employed are people whose only activity consisted of work around the house or unpaid volunteer work for religious, charitable, and similar organizations; also excluded are all institutionalized people and people on active duty in the United States Armed Forces.

Civilian Employed
This term is defined exactly the same as the term "employed" above.

Unemployed
All civilians 16 years old and over are classified as unemployed if they (1) were neither "at work" nor "with a job but not at work" during the reference week, and (2) were actively looking for work during the last 4 weeks, and (3) were available to start a job. Also included as unemployed are civilians who did not work at all during the reference week, were waiting to be called back to a job from which they had been laid off, and were available for work except for temporary illness. Examples of job seeking activities are:

  • Registering at a public or private employment office
  • Meeting with prospective employers
  • Investigating possibilities for starting a professional practice or opening a business
  • Placing or answering advertisements
  • Writing letters of application
  • Being on a union or professional register


Civilian Labor Force
Consists of people classified as employed or unemployed in accordance with the criteria described above.

Unemployment Rate
The unemployment rate represents the number of unemployed people as a percentage of the civilian labor force. For example, if the civilian labor force equals 100 people and 7 people are unemployed, then the unemployment rate would be 7 percent.

Labor Force
All people classified in the civilian labor force plus members of the U.S. Armed Forces (people on active duty with the United States Army, Air Force, Navy, Marine Corps, or Coast Guard).

Labor Force Participation Rate
The labor force participation rate represents the proportion of the population that is in the labor force. For example, if there are 100 people in the population 16 years and over, and 64 of them are in the labor force, then the labor force participation rate for the population 16 years and over would be 64 percent.

Not in Labor Force
All people 16 years old and over who are not classified as members of the labor force. This category consists mainly of students, homemakers, retired workers, seasonal workers interviewed in an off season who were not looking for work, institutionalized people, and people doing only incidental unpaid family work (less than 15 hours during the reference week).

Worker
This term appears in connection with several subjects: employment status, journey-to-work questions, class of worker, weeks worked in the past 12 months, and number of workers in family in the past 12 months. The meaning varies and, therefore, should be determined in each case by referring to the definition of the subject in which it appears. When used in the concepts "workers in family" and "full-time, year-round workers," the term "worker" relates to the meaning of work defined for the "work experience" subject.

Question/Concept History -

Worked Last Week (Question 29 in the 2012 American Community Survey): From 1999-2007, an italicized instruction was added to the question to help respondents determine what to count as work. Starting in 2008, the instruction was removed and the question wasseparated into two parts in an effort to give respondents - particularly people with irregular kinds of work arrangements - two opportunities to grasp and respond to the correct intent of the question.

On Layoff (Question 35a in the 2012 American Community Survey): Starting in 1999, the "Yes, on temporary layoff from most recent job" and "Yes, permanently laid off from most recent job" response categories were condensed into a single "Yes" category. An additional question (Q35b) was added to determine the temporary/permanent layoff distinction.

Temporarily Absent (Question 35b in the 2012 American Community Survey): Starting in 2008, the temporarily absent question included a revised list of examples of work absences.

Recalled to Work (Question 35c in the 2012 American Community Survey): This question was added in the 1999 American Community Survey to determine if a respondent who reported being on layoff from a job had been informed that he or she would be recalled to work within 6 months or been given a date to return to work.

Looking for Work (Question 36 in the 2012 American Community Survey): Starting in 2008, the actively looking for work question was modified to emphasize 'active' job- searching activities.

Available to Work (Question 37 in the 2012 American Community Survey): Starting in 1999, the "Yes, if a job had been offered" and "Yes, if recalled from layoff' response categories were condensed into one category, "Yes, could have gone to work."

Limitation of the Data

The data may understate the number of employed people because people who have irregular, casual, or unstructured jobs sometimes report themselves as not working. The number of employed people "at work" is probably overstated in the data (and conversely, the number of employed "with a job, but not at work" is understated) since some people on vacation or sick leave erroneously reported themselves as working. This problem has no effect on the total number of employed people. The reference week for the employment data is not the same for all people. Since people can change their employment status from one week to another, the lack of a uniform reference week may mean that the employment data do not reflect the reality of the employment situation of any given week. (For more information, see the discussion under "Reference Week.")

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations have employment status distributions that are different from the household population. All institutionalized people are placed in the "not in labor force category." The inclusion of the GQ population could therefore have a noticeable impact on the employment status distribution. This is particularly true for areas with a substantial GQ population. For example, in areas having a large state prison population, the employment rate would be expected to decrease because the base of the percentage, which now includes the population in correctional institutions, is larger.

The Census Bureau tested the changes introduced to the 2008 version of the employment status questions in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for these questions as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Employment Status" on the ACS website (http://www.census.gov/acs).

Along with the 2008 ACS release, the Census Bureau produced a research note comparing 2007 and 2008 ACS employment estimates to 2007 and 2008 Current Population Survey (CPS)/Local Area Unemployment Statistics (LAUS) estimates. The research note shows that the changes to the employment status series of questions in the 2008 ACS will make ACS labor force data more consistent with benchmark data from the CPS and LAUS program. For more information, see "Changes to the American Community Survey between 2007 and 2008 and the Effects on the Estimates of Employment and Unemployment" (http://www.census.gov/hhes/www/laborfor/researchnote092209.html).

Comparability

Since employment data from the American Community Survey are obtained from respondents in households, they differ from statistics based on reports from individual business establishments, farm enterprises, and certain government programs. People employed at more than one job are counted only once in the American Community Survey and are classified according to the job at which they worked the greatest number of hours during the reference week. In statistics based on reports from business and farm establishments, people who work for more than one establishment may be counted more than once. Moreover, some tabulations may exclude private household workers, unpaid family workers, and self-employed people, but may include workers less than 16 years of age.
An additional difference in the data arises from the fact that people who had a job but were not at work are included with the employed in the American Community Survey statistics, whereas many of these people are likely to be excluded from employment figures based on establishment payroll reports. Furthermore, the employment status data in tabulations include people on the basis of place of residence regardless of where they work, whereas establishment data report people at their place of work regardless of where they live. This latter consideration is particularly significant when comparing data for workers who commute between areas.

For several reasons, the unemployment figures of the Census Bureau are not comparable with published figures on unemployment compensation claims. For example, figures on unemployment compensation claims exclude people who have exhausted their benefit rights, new workers who have not earned rights to unemployment insurance, and people losing jobs not covered by unemployment insurance systems (including some workers in agriculture, domestic services, and religious organizations, and self-employed and unpaid family workers). In addition, the qualifications for drawing unemployment compensation differ from the definition of unemployment used by the Census Bureau. People working only a few hours during the week and people with a job but not at work are sometimes eligible for unemployment compensation but are classified as "Employed" in the American Community Survey. Differences in the geographical distribution of unemployment data arise because the place where claims are filed may not necessarily be the same as the place of residence of the unemployed worker.
For guidance on differences in employment and unemployment estimates from different sources, go to (http://www.census.gov/hhes/www/laborfor/laborguidance082504.html.

Families
See Household Type and Relationship.

Fertility
The data on fertility were derived from Question 17 in 1999-2002, Question 18 in 2003-2007, question 23 in 2008, and question 24 since 2009 in the American Community Survey. The question asked if the person had given birth in the past 12 months, and was asked of all women 15 to 50 years old regardless of marital status. From this question, we are able to determine geographies with high numbers of women with births and the characteristics of these women, such as age and marital status. When fertility was not reported, it was imputed according to the woman's age and marital status and the possibility there was an infant in the household.

Data are most frequently presented in terms of the aggregate number of women who had a birth in the past 12 months in the specified category, and in terms of the rate per 1,000 women.

Total Fertility Rate
This measure estimates the number of children a group of 1,000 women would have by the end of their childbearing years if they all experienced the same age-specific birth rates between ages 15-50 in a given year. This rate is used for comparisons among different population groups-for example, women in different geographical areas--as the rate accounts for differences in the age distribution in those areas.

Question/Concept History

The 1996-1998 American Community Survey collected data on "children ever born." (See the section on "Children Ever Born" for more information.) In 1999, the American Community Survey began collecting data on children born in the last 12 months.

Limitation of the Data

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have fertility distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the fertility distribution. This is particularly true for areas with a substantial GQ population.

Comparability

The data on fertility can be compared to previous ACS years, to data from the National Center for Health Statistics (NCHS), and to similar data collected in the Current Population Survey (CPS) before that question changed in 2012. Keep in mind there are differences among these that can lead to differences in estimates. For instance, the NCHS collects administrative records while the ACS and CPS estimates are based on survey data. Also, all of these surveys have slightly different ways of determining the reference period, but generally show births occurring over a period of 12 months.

Field of Degree
Field of degree data are used by the National Science Foundation to study the characteristics of the population with science and engineering degrees and occupations.

Data on field of bachelor's degree were derived from answers to Question 12 in the 2012 American Community Survey. This question was asked only to person with a bachelor's degree or higher. Eligible respondents were asked to list the specific major(s) of any bachelor's degree received. This question does not ask for the field of any other type of degree earned (such as master's or doctorate).

An automated computer system coded write-in responses to Question 12 into 192 areas. Clerical coding categorized any write-in responses that could not be autocoded by the computer. Respondents listing multiple fields were assigned a code for each field, with a maximum of 10 fields per respondent.
The majors were further classified into a category scheme detailed in Field of Degree Classification table in Appendix A.

Question/Concept History

The field of degree question first appeared in the 2009 ACS. The inclusion of a field of degree question on the ACS was proposed to provide field of degree data annually for small levels of geography and to assist in building a sampling frame for the National Science Foundation's (NSF) National Survey of College Graduates (NSCG).

Comparability

Tables based on 2010-2012 ACS data are not completely comparable to tables based on 2009 ACS data due to slight changes in the field of degree coding and classifications. More information can be found at http://www.census.gov/hhes/socdemo/education/data/acs/index.html.

This data may be roughly comparable to the National Survey of College Graduates and the National Survey of Recent College Graduates, although the sampling frame and survey instruments differ between the surveys. Field of degree data was also collected in the Survey of Income and Program Participation (SIPP) from1984 to 2004. However, these data would not be comparable to ACS due to differences in data collection period, methodology and collection methods. For example, the SIPP only collects data for respondents who are 15 years and older and does not include group quarters.

Foreign-Born Population
The foreign-born population includes anyone who was not a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were a U.S. citizen by naturalization or not a U.S. citizen. See Citizenship Status.

Foster Children
See Household Type and Relationship.

Grade in Which Enrolled
See School Enrollment and Type of School.

Grandparents as Caregivers
Data on grandparents as caregivers were derived from Questions 25a through 25c in the 2012 American Community Survey. Data are collected on whether a grandchild lives with a grandparent in the household, whether the grandparent has responsibility for the basic needs of the grandchild, and the duration of that responsibility.

Existence of a Grandparent Living with a Grandchild in the Household
This was determined by a "Yes" answer to the question, "Does this person have any of his/her own grandchildren under the age of 18 living in this house or apartment?" This question was asked of people 15 years of age and over. Because of the low numbers of persons under 30 years old living with their grandchildren, data were only tabulated for people 30 and over.

Responsibility for Basic Needs
This question determines if the grandparent is financially responsible for food, shelter, clothing, day care, etc., for any or all grandchildren living in the household. In selected tabulations, grandparent responsibility is further classified by presence of parent (of the grandchild).

Duration of Responsibility
The answer refers to the grandchild for whom the grandparent has been responsible for the longest period of time. Duration categories ranged from less than 6 months to 5 or more years.

Question/Concept History

This set of questions was added to the American Community Survey in 1999 to comply with legislation passed in the 104th Congress requiring that the decennial census program obtain information about grandparents who have primary responsibility for the care of their grandchildren.
The response categories for length of time caring for grandchildren were modified slightly between the 1999 and 2000 American Community Survey questionnaires to match the 2000 decennial census questionnaire. The question has remained unchanged since then.
Limitation of the Data - Before 2006, ACS grandparents data had a universe of people in households (which was the same as that in Census 2000). Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations may have grandparents as caregivers distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the grandparents as caregivers distribution. This is particularly true for areas with a substantial GQ population.

Comparability

The data on grandparents as caregivers can be compared to previous ACS years and Census 2000 (with the potential limitation noted above about areas with a substantial GQ population).

Group Quarters (GQ)
See Living Quarters.

Health Insurance Coverage
In 2012, data on health insurance coverage were derived from answers to Question 16 in the American Community Survey, which was asked of all respondents. Respondents were instructed to report their current coverage and to mark "yes" or "no" for each of the eight types listed (labeled as parts 16a to 16h).

  1. Insurance through a current or former employer or union (of this person or another family member)
  2. Insurance purchased directly from an insurance company (by this person or another family member)
  3. Medicare, for people 65 and older, or people with certain disabilities
  4. Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability
  5. TRICARE or other military health care
  6. VA (including those who have ever used or enrolled for VA health care)
  7. Indian Health Service
  8. Any other type of health insurance or health coverage plan
Respondents who answered "yes" to question 16h were asked to provide their other type of coverage type in a write-in field.

Health insurance coverage in the ACS and other Census Bureau surveys define coverage to include plans and programs that provide comprehensive health coverage. Plans that provide insurance for specific conditions or situations such as cancer and long-term care policies are not considered coverage. Likewise, other types of insurance like dental, vision, life, and disability insurance are not considered health insurance coverage.

In defining types of coverage, write-in responses were reclassified into one of the first seven types of coverage or determined not to be a coverage type. Write-in responses that referenced the coverage of a family member were edited to assign coverage based on responses from other family members. As a result, only the first seven types of health coverage are included in the microdata file.

An eligibility edit was applied to give Medicaid, Medicare, and TRICARE coverage to individuals based on program eligibility rules. TRICARE or other military health care was given to active-duty military personnel and their spouses and children. Medicaid or other means-tested public coverage was given to foster children, certain individuals receiving Supplementary Security Income or Public Assistance, and the spouses and children of certain Medicaid beneficiaries. Medicare coverage was given to people 65 and older who received Social Security or Medicaid benefits.

People were considered insured if they reported at least one "yes" to Questions 16a to 16f. People who had no reported health coverage, or those whose only health coverage was Indian Health Service, were considered uninsured. For reporting purposes, the Census Bureau broadly classifies health insurance coverage as private health insurance or public coverage. Private health insurance is a plan provided through an employer or union, a plan purchased by an individual from a private company, or TRICARE or other military health care. Respondents reporting a "yes" to the types listed in parts a, b, or e were considered to have private health insurance. Public health coverage includes the federal programs Medicare, Medicaid, and VA Health Care (provided through the Department of Veterans Affairs); the Children's Health Insurance Program (CHIP); and individual state health plans. Respondents reporting a "yes" to the types listed in c, d, or f were considered to have public coverage. The types of health insurance are not mutually exclusive; people may be covered by more than one at the same time.
The U.S. Department of Health and Human Services, as well as other federal agencies, use data on health insurance coverage to more accurately distribute resources and better understand state and local health insurance needs.

Question/Concept History

The ACS began asking questions about health insurance coverage in 2008. Because 2008 was the first year of collection, the Census Bureau limited the number and type of data products to simple age breakdowns of overall, private, and public coverage status. The evaluation of the 2008 data suggested that the data were of good quality, so the Census Bureau expanded the data products to include estimates of the specific types of coverage along with estimates about social, economic, and demographic details for people with and without health insurance.

For the 2008 data released September 2009, there was no eligibility edit applied. The eligibility edit that was developed for the 2009 was applied to the 2008 data during spring 2010. New estimates of health insurance coverage with this data are available (http://www.census.gov/hhes/www/hlthins/hlthins.html).

Limitation of the Data

The universe for most health insurance coverage estimates is the civilian noninstitutionalized population, which excludes active-duty military personnel and the population living in correctional facilities and nursing homes. Some noninstitutionalized GQ populations have health insurance coverage distributions that are different from the household population (e.g., the prevalence of private health insurance among residents of college dormitories is higher than the household population). The proportion of the universe that is in the noninstitutionalized GQ populations could therefore have a noticeable impact on estimates of the health insurance coverage. Institutionalized GQ populations may also have health insurance coverage distributions that are different from the civilian noninstitutionalized population, the distributions in the published tables may differ slightly from how they would look if the total population were represented.

Comparability

Health insurance coverage was added to the 2008 ACS and so no equivalent measure is available from previous ACS surveys or Census 2000. Because of the addition of the eligibility edit to 2009 ACS health insurance, data users should be careful as to which 2008 ACS estimates they use to make comparisons. National, state, county and place-level 2008 1-year data incorporating the eligibility edit are available
(http://www.census.gov/hhes/www/hlthins/data/acs/2008/re-run.html); they are comparable to the 2009 estimates in American Fact Finder. Please see
http://www.census.gov/hhes/www/hlthins/publications/coverage_edits_final.pdf for more information on the logical coverage (eligibility) edits.

Because coverage in the ACS references an individual's current status, caution should be taken when making comparisons to other surveys which may define coverage as "at any time in the last year" or "throughout the past year." A discussion of how the ACS health insurance estimates relate to other survey health insurance estimates can be found in A Preliminary Evaluation of Health Insurance Coverage in the 2008 American Community Survey (http://www.census.gov/hhes/www/hlthins/data/acs/2008/2008ACS_healthins.pdf).

Hispanic or Latino Origin
The data on the Hispanic or Latino population were derived from answers to a question that was asked of all people. The terms "Hispanic," "Latino," and "Spanish" are used interchangeably. Some respondents identify with all three terms while others may identify with only one of these three specific terms. Hispanics or Latinos who identify with the terms "Hispanic," "Latino," or "Spanish" are those who classify themselves in one of the specific Hispanic, Latino, or Spanish categories listed on the questionnaire ("Mexican," "Puerto Rican," or "Cuban") as well as those who indicate that they are "another Hispanic, Latino, or Spanish origin." People who do not identify with one of the specific origins listed on the questionnaire but indicate that they are "another Hispanic, Latino, or Spanish origin" are those whose origins are from Spain, the Spanish-speaking countries of Central or South America, or the Dominican Republic. Up to two write-in responses to the "another Hispanic, Latino, or Spanish origin" category are coded.

Origin can be viewed as the heritage, nationality group, lineage, or country of birth of the person or the person's parents or ancestors before their arrival in the United States. People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

Hispanic origin is used in numerous programs and is vital in making policy decisions. These data are needed to determine compliance with provisions of antidiscrimination in employment and minority recruitment legislation. Under the Voting Rights Act, data about Hispanic origin are essential to ensure enforcement of bilingual election rules. Hispanic origin classifications used by the Census Bureau and other federal agencies meet the requirements of standards issued by the Office of Management and Budget in 1997 (Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity). These standards set forth guidance for statistical collection and reporting on race and ethnicity used by all federal agencies.

Some tabulations are shown by the origin of the householder. In all cases where the origin of households, families, or occupied housing units is classified as Hispanic, Latino, or Spanish, the origin of the householder is used. (For more information, see the discussion of householder under "Household Type and Relationship.")

Coding of Hispanic Origin Write-in Responses
There were two types of coding operations: (1) automated coding where a write-in response was automatically coded if it matched a write-in response already contained in a database known as the "master file," and (2) expert coding, which took place when a write-in response did not match an entry already on the master file, and was sent to expert coders familiar with the subject matter. During the coding process, subject-matter specialists reviewed and coded written entries from the "Yes, another Hispanic, Latino or Spanish origin" write-in response category on the Hispanic origin question.

Editing of Hispanic Origin Responses
If an individual did not provide a Hispanic origin response, their origin was allocated using specific rules of precedence of household relationship. For example, if origin was missing for a natural-born child in the household, then either the origin of the householder, another natural-born child, or spouse of the householder was allocated. If Hispanic origin was not reported for anyone in the household and origin could not be obtained from a response to the race question, then the Hispanic origin of a householder in a previously processed household with the same race was allocated. Surnames (Spanish and Non-Spanish) were used to assist in allocating an origin or race.

Question/Concept History

Beginning in 1996, the American Community Survey question was worded "Is this person Spanish/Hispanic/Latino?" In 2008, the question wording changed to "Is this person of Hispanic, Latino, or Spanish origin?" From 1999 to 2007, the Hispanic origin question provided an instruction, "Mark (X) the "No" box if not Spanish/Hispanic/Latino." The 2008 question, as well as the 1996 to 1998 questions, did not have this instruction. In addition, in 2008, the "Yes, another Hispanic, Latino, or Spanish" category provided examples of six Hispanic origin groups (Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on).

Limitation of the Data

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have Hispanic or Latino origin distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the Hispanic or Latino origin distribution. This is particularly true for areas with a substantial GQ population.

Comparability

The ACS question on Hispanic origin was revised in 2008 to make it consistent with the 2010 Census Hispanic origin question. The reporting of specific Hispanic groups (e.g., Colombian, Dominican, Spaniard, etc.) increased at the national level. The change in estimates for 2012 may be due to demographic changes, as well as factors including questionnaire changes, differences in ACS population controls, and methodological differences in the population estimates. Caution should be used when comparing 2012 estimates to estimates from previous years. The 2012 Hispanic origin question is different from the Census 2000 question on Hispanic origin, therefore comparisons should be made with caution. More information about the changes in the estimates is available (http://www.census.gov/population/hispanic/files/acs08researchnote.pdf).

See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Hispanic Origin Code List.

Household
See Household Type and Relationship.

Household Type and Relationship
The data on relationship to householder were derived from answers to Question 2 in the 2012 American Community Survey, relationship to the householder, which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs, such as families in poverty.

The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multigenerational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.

Household
A household includes all the people who occupy a housing unit. (People not living in households are classified as living in group quarters.) A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other people in the building and which have direct access from the outside of the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living arrangements.

Average Household Size
A measure obtained by dividing the number of people in households by the number of households. In cases where people in households are cross- classified by race or Hispanic origin, people in the household are classified by the race or Hispanic origin of the householder rather than the race or Hispanic origin of each individual. Average household size is rounded to the nearest hundredth.

Relationship to Householder
Householder
One person in each household is designated as the householder. In most cases, this is the person or one of the people in whose name the home is owned, being bought, or rented and who is listed on line one of the survey questionnaire. If there is no such person in the household, any adult household member 15 years old and over could be designated as the householder.

Households are classified by type according to the sex of the householder and the presence of relatives. Two types of householders are distinguished: a family householder and a non- family householder. A family householder is a householder living with one or more individuals related to him or her by birth, marriage, or adoption. The householder and all people in the household related to him or her are family members. A nonfamily householder is a householder living alone or with non-relatives only.

Spouse
Includes a person married to and living with a householder who is of the opposite sex of the householder. The category "husband or wife" includes people in formal marriages, as well as people in common-law marriages. In tabulations, unless otherwise specified, "Spouse" does not include same-sex married couples even if the marriage was performed in a state issuing marriage certificates for same-sex couples.

Includes a son or daughter by birth, a stepchild, or adopted child of the householder, regardless of the child's age or marital status. The category excludes sons-in-law, daughters-in-law, and foster children.

  • Biological son or daughter
- The son or daughter of the householder by birth.
  • Adopted son or daughter - The son or daughter of the householder by legal adoption. If a stepson or stepdaughter has been legally adopted by the householder, the child is then classified as an adopted child.
  • Stepson or stepdaughter - The son or daughter of the householder through marriage but not by birth, excluding sons-in-law and daughters-in-law. If a stepson or stepdaughter of the householder has been legally adopted by the householder, the child is then classified as an adopted child.


  • Own Child
    A never-married child under 18 years who is a son or daughter by birth, a stepchild, or an adopted child of the householder. In certain tabulations, own children are further classified as living with two parents or with one parent only. Own children of the householder living with two parents are by definition found only in married-couple families. (Note: When used in "EMPLOYMENT STATUS" tabulations, own child refers to a never married child under the age of 18 in a family or a subfamily who is a son or daughter, by birth, marriage, or adoption, of a member of the householder's family, but not necessarily of the householder.)

    Related Child
    Any child under 18 years old who is related to the householder by birth, marriage, or adoption. Related children of the householder include ever-married as well as never-married children. Children, by definition, exclude persons under 18 years who maintain households or are spouses or unmarried partners of householders.

    Other Relatives
    In tabulations, the category "other relatives" includes any household member related to the householder by birth, marriage, or adoption, but not included specifically in another relationship category. In certain detailed tabulations, the following categories may be shown:

    • Grandchild -
    The grandson or granddaughter of the householder.
  • Brother/Sister - The brother or sister of the householder, including stepbrothers, stepsisters, and brothers and sisters by adoption. Brothers-in-law and sisters-in-law are included in the "Other Relative" category on the questionnaire.
  • Parent - The father or mother of the householder, including a stepparent or adoptive parent. Fathers-in-law and mothers-in-law are included in the "Parent-in-law" category on the questionnaire.
  • Parent-in-law - The mother-in-law or father-in-law of the householder.
  • Son-in-law or daughter-in-law - The spouse of the child of the householder.
  • Other Relatives - Anyone not listed in a reported category above who is related to the householder by birth, marriage, or adoption (brother-in-law, grandparent, nephew, aunt, cousin, and so forth).


  • Nonrelatives
    This category includes any household member, including foster children, not related to the householder by birth, marriage, or adoption. The following categories may be presented in more detailed tabulations:

    • Roomer or Boarder -
    A roomer or boarder is a person who lives in a room in the household of the householder. Some sort of cash or noncash payment (e.g., chores) is usually made for their living accommodations.
  • Housemate or Roommate - A housemate or roommate is a person age 15 years old and over, who is not related to the householder, and who shares living quarters primarily in order to share expenses.
  • Unmarried Partner - An unmarried partner is a person age 15 years old and over, who is not related to the householder, who shares living quarters, and who has a close personal relationship with the householder. Same-sex spouses are included in this category for tabulation purposes and for public use data files.
  • Foster Child - A foster child is a person under 21 years old, who is placed by the local government in a household to receive parental care. Foster children may be living in the household for just a brief period or for several years. Foster children are nonrelatives of the householder. If the foster child is also related to the householder, the child is classified as that specific relative.
  • Other Nonrelatives - Anyone who is not related by birth, marriage, or adoption to the householder and who is not described by the categories given above.
  • When relationship is not reported for an individual, it is imputed according to the responses for age, sex, and marital status for that person while maintaining consistency with responses for other individuals in the household.

    Unrelated Individual
    An unrelated individual is:

    (1) a householder living alone or with nonrelatives only,

    (2) a household member who is not related to the householder, or

    (3) a person living in group quarters who is not an inmate of an institution.

    Family Households
    A family consists of a householder and one or more other people living in the same household who are related to the householder by birth, marriage, or adoption. All people in a household who are related to the householder are regarded as members of his or her family. A family household may contain people not related to the householder, but those people are not included as part of the householder's family in tabulations. Thus, the number of family households is equal to the number of families, but family households may include more members than do families. A household can contain only one family for purposes of tabulations. Not all households contain families since a household may be comprised of a group of unrelated people or of one person living alone - these are called nonfamily households. Families are classified by type as either a "married- couple family" or "other family" according to the sex of the householder and the presence of relatives. The data on family type are based on answers to questions on sex and relationship that were asked of all people.

    • Married-Couple Family -
    A family in which the householder and his or her spouse are listed as members of the same household.
  • Other Family:

    - Male Householder, No Wife Present -A family with a male householder and no spouse of householder present.

    - Female Householder, No Husband Present - A family with a female householder and no spouse of householder present.

    Family households and married-couple families do not include same-sex married couples even if the marriage was performed in a state issuing marriage certificates for same-sex couples. Same-sex couple households are included in the family households category if there is at least one additional person related to the householder by birth or adoption.

  • Average Family Size
    A measure obtained by dividing the number of people in families by the total number of families (or family householders). In cases where the measures, "people in family" or "people per family" are cross-tabulated by race or Hispanic origin, the race or Hispanic origin refers to the householder rather than the race or Hispanic origin of each individual. Average family size is rounded to the nearest hundredth.

    Subfamily
    A subfamily is a married couple (husband and wife interviewed as members of the same household) with or without never-married children under 18 years old, or one parent with one or more never-married children under 18 years old. A subfamily does not maintain its own household, but lives in a household where the householder or householder's spouse is a relative. The number of subfamilies is not included in the count of families, since subfamily members are counted as part of the householder's family. Subfamilies are defined during processing of data.

    In selected tabulations, subfamilies are further classified by type: married-couple subfamilies, with or without own children; mother-child subfamilies; and father-child subfamilies.

    In some labor force tabulations, children in both one-parent families and one-parent subfamilies are included in the total number of children living with one parent, while children in both married-couple families and married-couple subfamilies are included in the total number of children living with two parents.

    Nonfamily Household
    A householder living alone or with nonrelatives only. Same-sex couple households with no relatives of the householder present are tabulated in nonfamily households.

    Unmarried-Partner Household
    An unmarried-partner household is a household other than a "married-couple household" that includes a householder and an "unmarried partner." An "unmarried partner" can be of the same sex or of the opposite sex as the householder. An "unmarried partner" in an "unmarried-partner household" is an adult who is unrelated to the householder, but shares living quarters and has a close personal relationship with the householder. An unmarried-partner household also may be a family household or a nonfamily household, depending on the presence or absence of another person in the household who is related to the householder. There may be only one unmarried partner per household, and an unmarried partner may not be included in a married-couple household, as the householder cannot have both a spouse and an unmarried partner. Same-sex married couples are included in the count of unmarried-partner households for tabulations purposes and for public use data files.

    Question/Concept History

    Between 1996 and 2007, the question response categories remained the same. In 2008, the "Son or daughter" category was expanded to "Biological son or daughter," "Adopted son or daughter," and "Stepson or stepdaughter." Also "In-law" was expanded to "Parent-in-law" and "Son-in-law or daughter-in-law."

    Limitation of the Data

    Unlike the Current Population Survey (CPS) and the Survey of Income and Program Participation (SIPP), the ACS relationship question does not have a parent pointer to identify whether both parents are present. For example, if a child lives with unmarried parents, we only know the relationship of the child to the householder, not to the other parent. So a count of children living with two biological parents is not precise.

    Comparability

    The relationship categories for the most part can be compared to previous ACS years and to similar data collected in the decennial census, CPS, and SIPP. With the change in 2008 from "In-law" to the two categories of "Parent-in-law" and "Son-in-law or daughter-in-law," caution should be exercised when comparing data on in-laws from previous years. "In-law" encompassed any type of in-law such as sister-in-law. Combining "Parent-in-law" and "son-in-law or daughter-in-law" does not represent all "in-laws" in 2008. The same can be said of comparing the three categories of "biological" "step," and "adopted" child in 2008 to "Child" in previous years. Before 2008, respondents may have considered anyone under 18 as "child" and chosen that category. The ACS includes "foster child" as a category. However, the 2010 census did not contain this category, and "foster children" were included in the "Other nonrelative" category. Therefore, comparison of "foster child" cannot be made to the 2010 Census.

    Household Size
    See Household Type and Relationship.

    Householder
    See Household Type and Relationship.

    Immigrants
    See Foreign-Born Population.

    Income in the Past 12 Months
    The data on income were derived from answers to Questions 47 and 48 in the 2012 American Community Survey, which were asked of the population 15 years old and over. "Total income" is the sum of the amounts reported separately for wage or salary income; net self- employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income.

    Receipts from the following sources are not included as income: capital gains, money received from the sale of property (unless the recipient was engaged in the business of selling such property); the value of income "in kind" from food stamps, public housing subsidies, medical care, employer contributions for individuals, etc.; withdrawal of bank deposits; money borrowed; tax refunds; exchange of money between relatives living in the same household; gifts and lump-sum inheritances, insurance payments, and other types of lump- sum receipts.

    Income is a vital measure of general economic circumstances. Income data are used to determine poverty status, to measure economic well-being, and to assess the need for assistance. These data are included in federal allocation formulas for many government programs. For instance:

    Social Services: Under the Older Americans Act, funds for food, health care, and legal services are distributed to local agencies based on data about elderly people with low incomes. Data about income at the state and county levels are used to allocate funds for food, health care, and classes in meal planning to low-income women with children.

    Employment: Income data are used to identify local areas eligible for grants to stimulate economic recovery, run job-training programs, and define areas such as empowerment or enterprise zones.

    Housing: Under the Low-Income Home Energy Assistance Program, income data are used to allocate funds to areas for home energy aid. Under the Community Development Block Grant Program, funding for housing assistance and other community development is based on income and other census data.

    Education: Data about poor children are used to allocate funds to counties and school districts. These funds provide resources and services to improve the education of economically disadvantaged children.

    In household surveys, respondents tend to underreport income. Asking the list of specific sources of income helps respondents remember all income amounts that have been received, and asking total income increases the overall response rate and thus, the accuracy of the answers to the income questions. The eight specific sources of income also provide needed detail about items such as earnings, retirement income, and public assistance.

    Income Type in the Past 12 Months
    The eight types of income reported in the American Community Survey are defined as follows:

    1. Wage or salary income:
    Wage or salary income includes total money earnings received for work performed as an employee during the past 12 months. It includes wages, salary, Armed Forces pay, commissions, tips, piece-rate payments, and cash bonuses earned before deductions were made for taxes, bonds, pensions, union dues, etc.
  • Self-employment income: Self-employment income includes both farm and non-farm self-employment income.

  • Farm self-employment income includes net money income (gross receipts minus operating expenses) from the operation of a farm by a person on his or her own account, as an owner, renter, or sharecropper. Gross receipts include the value of all products sold, government farm programs, money received from the rental of farm equipment to others, and incidental receipts from the sale of wood, sand, gravel, etc. Operating expenses include cost of feed, fertilizer, seed, and other farming supplies, cash wages paid to farmhands, depreciation charges, rent, interest on farm mortgages, farm building repairs, farm taxes (not state and federal personal income taxes), etc. The value of fuel, food, or other farm products used for family living is not included as part of net income.

    Non-farm self-employment income includes net money income (gross receipts minus expenses) from one's own business, professional enterprise, or partnership. Gross receipts include the value of all goods sold and services rendered. Expenses include costs of goods purchased, rent, heat, light, power, depreciation charges, wages and salaries paid, business taxes (not personal income taxes), etc.
    1. Interest, dividends, net rental income, royalty income, or income from estates and trusts: Interest, dividends, or net rental income includes interest on savings or bonds, dividends from stockholdings or membership in associations, net income from rental of property to others and receipts from boarders or lodgers, net royalties, and periodic payments from an estate or trust fund.
    2. Social Security income: Social Security income includes Social Security pensions and survivor benefits, permanent disability insurance payments made by the Social Security Administration prior to deductions for medical insurance, and railroad retirement insurance checks from the U.S. government. Medicare reimbursements are not included.
    3. Supplemental Security Income (SSI): Supplemental Security Income (SSI) is a nationwide U.S. assistance program administered by the Social Security Administration that guarantees a minimum level of income for needy aged, blind, or disabled individuals. The Puerto Rico Community Survey questionnaire asks about the receipt of SSI; however, SSI is not a federally-administered program in Puerto Rico. Therefore, it is probably not being interpreted by most respondents in the same manner as SSI in the United States. The only way a resident of Puerto Rico could have appropriately reported SSI would have been if they lived in the United States at any time during the past 12-month reference period and received SSI.
    4. Public assistance income: Public assistance income includes general assistance and Temporary Assistance to Needy Families (TANF). Separate payments received for hospital or other medical care (vendor payments) are excluded. This does not include Supplemental Security Income (SSI) or noncash benefits such as Food Stamps. The terms "public assistance income" and "cash public assistance" are used interchangeably in the 2012 ACS data products.
    5. Retirement, survivor, or disability income: Retirement income includes: (1) retirement pensions and survivor benefits from a former employer; labor union; or federal, state, or local government; and the U.S. military; (2) disability income from companies or unions; federal, state, or local government; and the U.S. military; (3) periodic receipts from annuities and insurance; and (4) regular income from IRA and Keogh plans. This does not include Social Security income.
    6. All other income: All other income includes unemployment compensation, worker's compensation, Department of Veterans Affairs (VA) payments, alimony and child support, contributions received periodically from people not living in the household, military family allotments, and other kinds of periodic income other than earnings.


    Cash Public Assistance
    See "Public assistance income."

    Income of Households
    This includes the income of the householder and all other individuals 15 years old and over in the household, whether they are related to the householder or not. Because many households consist of only one person, average household income is usually less than average family income. Although the household income statistics cover the past 12 months, the characteristics of individuals and the composition of households refer to the time of interview. Thus, the income of the household does not include amounts received by individuals who were members of the household during all or part of the past 12 months if these individuals no longer resided in the household at the time of interview. Similarly, income amounts reported by individuals who did not reside in the household during the past 12 months but who were members of the household at the time of interview are included. However, the composition of most households was the same during the past 12 months as at the time of interview.

    Income of Families
    In compiling statistics on family income, the incomes of all members 15 years old and over related to the householder are summed and treated as a single amount. Although the family income statistics cover the past 12 months, the characteristics of individuals and the composition of families refer to the time of interview. Thus, the income of the family does not include amounts received by individuals who were members of the family during all or part of the past 12 months if these individuals no longer resided with the family at the time of interview. Similarly, income amounts reported by individuals who did not reside with the family during the past 12 months but who were members of the family at the time of interview are included. However, the composition of most families was the same during the past 12 months as at the time of interview.

    Income of Individuals
    Income for individuals is obtained by summing the eight types of income for each person 15 years old and over. The characteristics of individuals are based on the time of interview even though the amounts are for the past 12 months.

    Median Income
    The median divides the income distribution into two equal parts: one-half of the cases falling below the median income and one-half above the median. For households and families, the median income is based on the distribution of the total number of households and families including those with no income. The median income for individuals is based on individuals 15 years old and over with income. Median income for households, families, and individuals is computed on the basis of a standard distribution. (See the "Standard Distributions" section under "Derived Measures.") Median income is rounded to the nearest whole dollar. Median income figures are calculated using linear interpolation. (For more information on medians and interpolation, see "Derived Measures.")

    Aggregate Income
    Aggregate income is the sum of all incomes for a particular universe. Aggregate income is subject to rounding, which means that all cells in a matrix are rounded to the nearest hundred dollars. (For more information, see "Aggregate" under "Derived Measures.")

    Mean Income
    Mean income is the amount obtained by dividing the aggregate income of a particular statistical universe by the number of units in that universe. For example, mean household income is obtained by dividing total household income by the total number of households. (The aggregate used to calculate mean income is rounded. For more information, see "Aggregate income.")

    For the various types of income, the means are based on households having those types of income. For household income and family income, the mean is based on the distribution of the total number of households and families including those with no income. The mean income for individuals is based on individuals 15 years old and over with income. Mean income is rounded to the nearest whole dollar.

    Care should be exercised in using and interpreting mean income values for small subgroups of the population. Because the mean is influenced strongly by extreme values in the distribution, it is especially susceptible to the effects of sampling variability, misreporting, and processing errors. The median, which is not affected by extreme values, is, therefore, a better measure than the mean when the population base is small. The mean, nevertheless, is shown in some data products for most small subgroups because, when weighted according to the number of cases, the means can be computed for areas and groups other than those shown in Census Bureau tabulations. (For more information on means, see "Derived Measures.")

    Income Quintile Upper Limits
    Negative incomes are converted to zero for these measures. These measures are the quintile cutoffs, along with the 95th percentile of the distribution. (For more information on quintiles, see "Derived Measures.")

    Means of Household Income by Quintiles
    Means of household income by quintiles are calculated by dividing aggregate household income in each quintile by the number of households in each quintile (one-fifth of the total number of households). (For more information on aggregates, see "Aggregate Income." For more information on quintiles, see "Derived Measures.")

    Shares of Household Income by Quintiles
    Negative incomes are converted to zero for these measures. These measures are the aggregate household income in each quintile as a percentage of the total aggregate household income. (For more information on aggregates, see "Aggregate income." For more information on quintiles, see "Derived Measures.")

    Gini Index of Income Inequality
    Negative incomes are converted to zero. The Gini index of income inequality measures the dispersion of the household income distribution. (For more information on the Gini index, see "Derived Measures.")

    Earnings
    Earnings are defined as the sum of wage or salary income and net income from self-employment. "Earnings" represent the amount of income received regularly for people 16 years old and over before deductions for personal income taxes, Social Security, bond purchases, union dues, Medicare deductions, etc. An individual with earnings is one who has either wage/salary income or self-employment income, or both. Respondents who "break even" in self-employment income and therefore have zero self-employment earnings also are considered "individuals with earnings."

    Median Earnings
    The median divides the earnings distribution into two equal parts: one- half of the cases falling below the median and one-half above the median. Median earnings is restricted to individuals 16 years old and over with earnings and is computed on the basis of a standard distribution. (See the "Standard Distributions" section under "Derived Measures.") Median earnings figures are calculated using linear interpolation. (For more information on medians and interpolation, see "Derived Measures.")

    Aggregate Earnings
    Aggregate earnings are the sum of wage/salary and net self- employment income for a particular universe of people 16 years old and over. Aggregate earnings are rounded to the nearest hundred dollars. (For more information, see "Aggregate" under "Derived Measures.")

    Mean Earnings
    Mean earnings is calculated by dividing aggregate earnings by the population 16 years old and over with earnings. (The aggregate used to calculate mean earnings is rounded. For more information, see "Aggregate earnings.") Mean earnings is rounded to the nearest whole dollar. (For more information on means, see "Derived Measures.")

    Women's Earnings as a Percentage of Men's Earnings
    Women's earnings as a percentage of men's earnings is defined as median earnings for females who worked fulltime, year-round divided by median earnings for males who worked full-time, year-round, multiplied by 100. (For more information see "full-time, year-round workers" under "Usual hours worked per weeks worked in the past 12 months" and "Median earnings.")

    Per Capita Income
    Per capita income is the mean income computed for every man, woman, and child in a particular group including those living in group quarters. It is derived by dividing the aggregate income of a particular group by the total population in that group. (The aggregate used to calculate per capita income is rounded. For more information, see "Aggregate" under "Derived Measures.") Per capita income is rounded to the nearest whole dollar. (For more information on means, see "Derived Measures.")

    Adjusting Income for Inflation
    Income components were reported for the 12 months preceding the interview month. Monthly Consumer Price Indices (CPI) factors were used to inflation-adjust these components to a reference calendar year (January through December). For example, a household interviewed in March 2012 reports their income for March 2011 through February 2012. Their income is adjusted to the 2012 reference calendar year by multiplying their reported income by 2012 average annual CPI (January-December 2012) and then dividing by the average CPI for March 2011-February 2012.

    In order to inflate income amounts from previous years, the dollar values on individual records are inflated to the latest year's dollar values by multiplying by a factor equal to the average annual CPI-U-RS factor for the current year, divided by the average annual CPI-U- RS factor for the earlier/earliest year.

    Question/Concept History

    The 1998 ACS questionnaire deleted references to Aid to Families with Dependent Children (AFDC) because of welfare law reforms.

    In 1999, the ACS questions were changed to be consistent with the questions for the Census 2000. The instructions are slightly different to reflect differences in the reference periods. The ACS asks about the past 12 months, and the questions for the decennial census ask about the previous calendar year.

    Limitation of the Data

    Since answers to income questions are frequently based on memory and not on records, many people tend to forget minor or sporadic sources of income and, therefore, underreport their income. Underreporting tends to be more pronounced for income sources that are not derived from earnings, such as public assistance, interest, dividends, and net rental income.

    Extensive computer editing procedures were instituted in the data processing operation to reduce some of these reporting errors and to improve the accuracy of the income data. These procedures corrected various reporting deficiencies and improved the consistency of reported income questions associated with work experience and information on occupation and class of worker. For example, if people reported they were self-employed on their own farm, not incorporated, but had reported only wage and salary earnings, the latter amount was shifted to self-employment income. Also, if any respondent reported total income only, the amount was generally assigned to one of the types of income questions according to responses to the work experience and class-of-worker questions. Another type of problem involved non- reporting of income data. Where income information was not reported, procedures were devised to impute appropriate values with either no income or positive or negative dollar amounts for the missing entries. (For more information on imputation, see "Accuracy of the Data" on the ACS website at .
    In income tabulations for households and families, the lowest income group (for example, less than $10,000) includes units that were classified as having no income in the past 12 months. Many of these were living on income "in kind," savings, or gifts, were newly created families, or were families in which the sole breadwinner had recently died or left the household. However, many of the households and families who reported no income probably had some money income that was not reported in the American Community Survey.

    Users should exercise caution when comparing income and earnings estimates for individuals since the 2006 ACS to earlier years because of the introduction of group quarters. Household and family income estimates are not affected by the inclusion of group quarters.

    Users should exercise caution when comparing medians from the 2012 ACS to earlier years. There was a change between 2008 and 2009 1-Year and 3-Year Data Products in Income and Earnings median calculations. Medians above $75,000 were most likely to be affected.

    Comparability

    The income data shown in ACS tabulations are not directly comparable with those that may be obtained from statistical summaries of income tax returns. Income, as defined for federal tax purposes, differs somewhat from the Census Bureau concept. Moreover, the coverage of income tax statistics is different because of the exemptions for people having small amounts of income and the inclusion of net capital gains in tax returns. Furthermore, members of some families file separate returns and others file joint returns; consequently, the tax reporting unit is not consistent with the census household, family, or person units.

    The earnings data shown in ACS tabulations are not directly comparable with earnings records of the Social Security Administration (SSA). The earnings record data for SSA excludes the earnings of some civilian government employees, some employees of nonprofit organizations, workers covered by the Railroad Retirement Act, and people not covered by the program because of insufficient earnings. Because ACS data are obtained from household questionnaires, they may differ from SSA earnings record data, which are based upon employers' reports and the federal income tax returns of self-employed people.

    The Commerce Department's Bureau of Economic Analysis (BEA) publishes annual data on aggregate and per-capita personal income received by the population for states, metropolitan areas, and selected counties. Aggregate income estimates based on the income statistics shown in ACS products usually would be less than those shown in the BEA income series for several reasons. The ACS data are obtained from a household survey, whereas the BEA income series is estimated largely on the basis of data from administrative records of business and governmental sources. Moreover, the definitions of income are different. The BEA income series includes some questions not included in the income data shown in ACS publications, such as income "in kind," income received by nonprofit institutions, the value of services of banks and other financial intermediaries rendered to people without the assessment of specific charges, and Medicare payments. On the other hand, the ACS income data include contributions for support received from people not residing in the same household if the income is received on a regular basis.

    In comparing income for the most recent year with income from earlier years, users should note that an increase or decrease in money income does not necessarily represent a comparable change in real income, unless adjusted for inflation.

    Industry
    Industry data describe the kind of business conducted by a person's employing organization. Industry data were derived from answers to questions 42 through 44 in the 2012 American Community Survey. Question 42 asks: "For whom did this person work?" Question 43 asks: "What kind of business or industry was this?" Question 44 provides four checkboxes from which respondents are to select one to indicate whether the business was primarily manufacturing, wholesale trade, retail trade, or other (agriculture, construction, service, government, etc.).

    These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

    Coding Procedures - Written responses to the industry questions are coded using the industry classification system developed for Census 2000 and modified in 2002 and again in 2007. This system consists of 269 categories for employed people, including military, classified into 20 sectors. The modified 2007 census industry classification was developed from the 2007 North American Industry Classification System (NAICS) (http://www.census.gov/eos/www/naics/) published by the Executive Office of the President, Office of Management and Budget. The NAICS was developed to increase comparability in industry definitions between the United States, Mexico, and Canada. It provides industry classifications that group establishments into industries based on the activities in which they are primarily engaged. The NAICS was created for establishment designations and provides detail about the smallest operating establishment, while the American Community Survey data are collected from households and differ in detail and nature from those obtained from establishment surveys. Because of potential disclosure issues, the census industry classification system, while defined in NAICS terms, cannot reflect the full detail for all categories that the NAICS provides.

    Respondents provided the data for the tabulations by writing on the questionnaires descriptions of their kind of business or industry. These write-ins are converted to a code category through automated coding. Cases not autocoded on both industry and occupation are sent to the clerical staff in the National Processing Center in Jeffersonville, Indiana who assign codes by comparing these descriptions to entries in the Alphabetical Index of Industries and Occupations (http://www.census.gov/people/io/methodology/indexes.html).

    The industry category, "Public administration," is limited to regular government functions such as legislative, judicial, administrative, and regulatory activities. Other government organizations such as public schools, public hospitals, and bus lines are classified by industry according to the activity in which they are engaged.
    Some occupation groups are related closely to certain industries. Operators of transportation equipment, farm operators and workers, and healthcare providers account for major portions of their respective industries of transportation, agriculture, and health care. However, the industry categories include people in other occupations. For example, people employed in agriculture include truck drivers and bookkeepers; people employed in the transportation industry include mechanics, freight handlers, and payroll clerks; and people employed in the health care industry include janitors, security guards, and secretaries.

    Editing Procedures - Following the coding operation, a computer edit and allocation process excludes all responses that should not be included in the universe, and evaluates the consistency of the remaining responses. The codes for industry are checked for consistency with the occupation and class of worker data provided for that respondent. Occasionally respondents supply industry descriptions that are not sufficiently specific for precise classification, or they do not report on these questions at all. Certain types of incomplete entries are corrected using the Alphabetical Index of Industries and Occupations. If one or more of the three codes (industry, occupation, or class of worker) is blank after the edit, a code is assigned from a donor respondent who is a "similar" person based on questions such as age, sex, educational attainment, income, employment status, and weeks worked. If all of the labor force and income data are blank, all of these economic questions are assigned from a "similar" person who had provided all the necessary data.

    These questions describe the industrial composition of the American labor force. Data are used to formulate policy and programs for employment, career development and training, and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

    Question/Concept History - Industry data have been collected during decennial censuses intermittently since 1820 and on a continuous basis since 1910. Starting with the 2010 Census, industry data will no longer be collected during the decennial census. Long form data collection has transitioned to the American Community Survey. The American Community Survey began collecting data on industry in 1996. The questions on industry were designed to be consistent with the 1990 Census questions on industry. In the 1990 Census and starting with the 1999 ACS, a check box was added to the employer name questionnaire item that was to be marked by anyone "now on active duty in the Armed Forces..." This information is used by the industry and occupation coders to assist in assigning proper industry codes for active duty military. Prior to 1999, the 1996-1998 ACS class of worker question had an additional response category for "Active duty U.S. Armed Forces member." Other than this exception, American Community Survey questions on industry have remained consistent between 1996 and 2012.

    Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have industry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the industry distribution in some geographic areas with a substantial GQ population.

    Data on occupation, industry, and class of worker are collected for the respondent's current primary job or the most recent job for those who are not employed but have worked in the last 5 years. Other labor force questions, such as questions on earnings or work hours, may have different reference periods and may not limit the response to the primary job. Although the prevalence of multiple jobs is low, data on some labor force items may not exactly correspond to the reported occupation, industry, or class of worker of a respondent.

    Comparability - Comparability of industry data was affected by a number of factors, primarily the system used to classify the questionnaire responses. Changes in the industry classification system limit comparability of the data from one year to another. These changes are needed to recognize the "birth" of new industries, the "death" of others, the growth and decline in existing industries, and the desire of analysts and other users for more detail in the presentation of the data. Probably the greatest cause of noncomparability is the movement of a segment from one category to another. Changes in the nature of jobs, respondent terminology, and refinement of category composition made these movements necessary.

    ACS data from 1996 to 1999 used the same industry classification systems used for the 1990 Census; therefore, the data are comparable. Since 1990, the industry classification has had major revisions to reflect the shift from the Standard Industrial Classification (SIC) to the North American Industry Classification System (NAICS). These changes were reflected in the Census 2000 industry codes. The 2000-2002 ACS data used the same industry and occupation classification systems used for the Census 2000; therefore, the data are comparable. In 2002, NAICS underwent another change and the industry codes were changed accordingly. Because of the possibility of new industries being added to the list of codes, the Census Bureau needed to have more flexibility in adding codes. Consequently, in 2002, industry census codes were expanded from three-digit codes to four-digit codes. The changes to these code classifications mean that the ACS data from 2003-2012 are not completely comparable to the data from earlier surveys. In 2007, NAICS was updated again. This resulted in a minor change in the industry data that will cause it to not be completely comparable to previous years. The changes were concentrated in the Information Sector where one census code was added (6672) and two were deleted (6675, 6692). For more information on industry comparability across classification systems, please see technical paper #65: The Relationship Between the 1990 Census and Census 2000 Industry and Occupation Classification Systems
    (http://www.census.gov/people/io/files/techpaper2000.pdf).

    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Industry Code List.

    See also Occupation and Class of Worker.

    Journey to Work
    Place of Work
    The data on place of work were derived from answers to Question 30 in 2012 American Community Survey, which was asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week. (See "Reference Week.")

    Data were tabulated for workers 16 years old and over, that is, members of the Armed Forces and civilians who were at work during the reference week. Data on place of work refer to the geographic location at which workers carried out their occupational activities during the reference week. In the American Community Survey, the exact address (number and street name) of the place of work was asked, as well as the place (city, town, or post office); whether the place of work was inside or outside the limits of that city or town; and the county, state or foreign country, and ZIP Code. In the Puerto Rico Community Survey, the question asked for the exact address, including the development or condominium name, as well as the place; whether or not the place of work was inside or outside the limits of that city or town; the municipio or U.S. county. Respondents also were asked to "enter Puerto Rico or name of U.S. state or foreign country" and the ZIP Code. If the respondent's employer operated in more than one location, the exact address of the location or branch where he or she worked was requested. When the number and street name were unknown, a description of the location, such as the building name or nearest street or intersection, was to be entered. People who worked at more than one location during the reference week were asked to report the location at which they worked the greatest number of hours. People who regularly worked in several locations each day during the reference week were requested to give the address at which they began work each day. For cases in which daily work did not begin at a central place each day, the respondent was asked to provide as much information as possible to describe the area in which he or she worked most during the reference week.

    Place-of-work data may show a few workers who made unlikely daily work trips (e.g., workers who lived in New York and worked in California). This result is attributable to people who worked during the reference week at a location that was different from their usual place of work, such as people away from home on business.

    In areas where the workplace address was geographically coded to the block level, people were tabulated as working inside or outside a specific place based on the location of that address regardless of the response to Question 30c concerning city/town limits. In areas where it was impossible to code the workplace address to the block level, or the coding system was unable to match the employer name and street address responses, people were tabulated as working inside or outside a specific place based on the combination of state, county, ZIP Code, place name, and city limits indicator. The city limits indicator was used only in coding decisions when there were multiple geographic codes to select from, after matching on the state, county, place, and ZIP Code responses. The accuracy of place-of- work data for census designated places (CDPs) may be affected by the extent to which their census names were familiar to respondents, and by coding problems caused by similarities between the CDP name and the names of other geographic jurisdictions in the same vicinity.

    Place-of-work data are given for selected minor civil divisions (MCDs), (generally cities, towns, and townships) in the 12 strong MCD states (Connecticut, Maine, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin), based on the responses to the place of work question. Many towns and townships are regarded locally as equivalent to a place, and therefore, were reported as the place of work. When a respondent reported a locality or incorporated place that formed a part of a township or town, the coding and tabulating procedure was designed to include the response in the total for the township or town.

    Workplace-based Geography
    The characteristics of workers may be shown using either residence-based or workplace-based geography. If you are interested in the number and characteristics of workers living in a specific area, you should use the standard (residence- based) journey-to-work tables. If you are interested in the number and characteristics of workers who work in a specific area, you should use the workplace-based journey-to-work tables. Because place-of-work information for workers cannot always be specified below the place level, the workplace-based tables are presented only for selected geographic areas.

    Means of Transportation to Work
    The data on means of transportation to work were derived from answers to Question 31 in 2012 American Community Survey, which was asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week. (See "Reference Week.") Means of transportation to work refers to the principal mode of travel or type of conveyance that the worker usually used to get from home to work during the reference week.

    People who used different means of transportation on different days of the week were asked to specify the one they used most often, that is, the greatest number of days. People who used more than one means of transportation to get to work each day were asked to report the one used for the longest distance during the work trip. The category, "Car, truck, or van," includes workers using a car (including company cars but excluding taxicabs), a truck of one- ton capacity or less, or a van. The category, "Public transportation," includes workers who used a bus or trolley bus, streetcar or trolley car, subway or elevated, railroad, or ferryboat, even if each mode is not shown separately in the tabulation. "Carro publico" is included in the public transportation category in Puerto Rico. The category, "Other means," includes workers who used a mode of travel that is not identified separately within the data distribution. The category, "Other means," may vary from table to table, depending on the amount of detail shown in a particular distribution.

    The means of transportation data for some areas may show workers using modes of public transportation that are not available in those areas (for example, subway or elevated riders in a metropolitan area where there is no subway or elevated service). This result is largely due to people who worked during the reference week at a location that was different from their usual place of work (such as people away from home on business in an area where subway service was available), and people who used more than one means of transportation each day but whose principal means was unavailable where they lived (for example, residents of nonmetropolitan areas who drove to the fringe of a metropolitan area, and took the commuter railroad most of the distance to work).

    Private Vehicle Occupancy
    The data on private vehicle occupancy were derived from answers to Question 32 in 2012 American Community Survey. This question was asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week and who reported in 2012 ACS Question 31 that their means of transportation to work was "Car, truck, or van." Data were tabulated for workers 16 years old and over, that is, members of the Armed Forces and civilians who were at work during the reference week. (See "Reference Week.")

    Private vehicle occupancy refers to the number of people who usually rode to work in the vehicle during the reference week. The category, "Drove alone," includes people who usually drove alone to work as well as people who were driven to work by someone who then drove back home or to a non-work destination. The category, "Carpooled," includes workers who reported that two or more people usually rode to work in the vehicle during the reference week.

    Workers Per Car, Truck, or Van
    Workers per car, truck, or van is a ratio obtained by dividing the aggregate number of workers who reported using a car, truck, or van to get to work by the number of such vehicles that they used. Workers per car, truck, or van is rounded to the nearest hundredth. This measure also may be known as "Workers per private vehicle."

    Aggregate Number of Vehicles (Car, Truck, or Van) Used in Commuting
    The aggregate number of vehicles used in commuting is derived by counting each person who drove alone as occupying one vehicle, each person who reported being in a two-person carpool as occupying one-half of a vehicle, each person who reported being in a three-person carpool as occupying one-third of a vehicle, and so on, then summing all the vehicles. This aggregate is used in the calculation for "workers per car, truck, or van."


    Time Leaving Home to Go to Work
    The data on time leaving home to go to work were derived from answers to Question 33 in 2012 American Community Survey. This question was asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week, and who reported in 2012 ACS Question 31 that they worked outside their home. The departure time refers to the time of day that the respondent usually left home to go to work during the reference week. (See "Reference Week.")

    Travel Time to Work
    The data on travel time to work were derived from answers to Question 34 in 2012 American Community Survey. This question was asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week, and who reported in 2012 ACS Question 31 that they worked outside their home. Travel time to work refers to the total number of minutes that it usually took the worker to get from home to work during the reference week. The elapsed time includes time spent waiting for public transportation, picking up passengers in carpools, and time spent in other activities related to getting to work. (See "Reference Week.")

    Aggregate Travel Time to Work (in Minutes)
    Aggregate travel time to work is calculated by adding all of the travel times (in minutes) for workers who did not work at home. Aggregate travel times of workers having specific characteristics also are computed. The aggregate travel time is subject to rounding, which means that all cells in a matrix are rounded to the nearest 5 minutes. (For more information, see "Aggregate" under "Derived Measures.")

    Mean Travel Time to Work (in Minutes)
    Mean travel time to work (in minutes) is the average travel time that workers usually took to get from home to work (one way) during the reference week. This measure is obtained by dividing the total number of minutes taken to get from home to work (the aggregate travel time) by the number of workers 16 years old and over who did not work at home. The travel time includes time spent waiting for public transportation, picking up passengers and carpools, and time spent in other activities related to getting to work. Mean travel times of workers having specific characteristics also are computed. For example, the mean travel time of workers traveling 45 or more minutes to work is computed by dividing the aggregate travel time of workers whose travel times were 45 or more minutes by the number of workers whose travel times were 45 or more minutes. The aggregate travel time to work used to calculate mean travel time to work is rounded. (For more information, see "Aggregate Travel Time to Work (in Minutes).") Mean travel time is rounded to the nearest tenth of a minute. (For more information on means, see "Derived Measures.")

    Time Arriving at Work from Home
    The data on time arriving at work from home were derived from answers to Question 33 (Time Leaving Home to Go to Work) and from answers to Question 34 (Travel Time to Work), both in the 2012 American Community Survey. These questions were asked of people who indicated in 2012 ACS Question 29 that they worked at some time during the reference week, and who reported in 2012 ACS Question 31 that they worked outside their home. The arrival time is calculated by adding the travel time to work to the reported time leaving home to go to work. These data are presented with other characteristics of workers at their workplace. (See "Time Leaving Home to Go to Work" and "Travel Time to Work.")

    The responses to the place of work and journey to work questions provide basic knowledge about commuting patterns and the characteristics of commuter travel. The commuting data are essential for planning highway improvement and developing public transportation services, as well as for designing programs to ease traffic problems during peak periods, conserve energy, reduce pollution, and estimate and project the demand for alternative-fueled vehicles. These data are required to develop standards for reducing work-related vehicle trips and increasing passenger occupancy during peak period of travel. The Bureau of Economic Analysis (BEA) plans to use county-level data in computing gross commuting flows to develop place-of-residence earning estimates from place-of-work estimates by industry. In addition, BEA also plans to use these data for state personal income estimates for determining federal fund allocations.

    Question/Concept History

    Starting in 1999, the American Community Survey questions differ from the 1996-1998 questions in that the labels on the write-in spaces and format of the skip instructions were modified to provide clarifications.

    Beginning in 2004, the category, "Public transportation" for means of transportation was tabulated to exclude workers who used taxicab as their means of transportation.

    The 2004 American Community Survey marked the first time that workplace-based tables were released as a part of a standard census data product.

    Limitation of the Data

    Beginning in 2006, the group quarters (GQ) population is included in the ACS. Some types of GQ populations have place of work distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the place of work distribution. This is particularly true for areas with a substantial GQ population.

    The data on place of work is related to a reference week, that is, the calendar week preceding the date on which the respondents completed their questionnaires or were interviewed. This week is not the same for all respondents because data were collected over a 12-month period. The lack of a uniform reference week means that the place-of-work data reported in the survey will not exactly match the distribution of workplace locations observed or measured during an actual workweek.
    The place-of-work data are estimates of people 16 years and over who were both employed and at work during the reference week (including people in the Armed Forces). People who did not work during the reference week but had jobs or businesses from which they were temporarily absent due to illness, bad weather, industrial dispute, vacation, or other personal reasons are not included in the place-of-work data. Therefore, the data on place of work understate the total number of jobs or total employment in a geographic area during the reference week. It also should be noted that people who had irregular, casual, or unstructured jobs during the reference week might have erroneously reported themselves as not working.

    The address where the individual worked most often during the reference week was recorded on the questionnaire. If a worker held two jobs, only data about the primary job (the job where one worked the greatest number of hours during the preceding week) was requested. People who regularly worked in several locations during the reference week were requested to give the address at which they began work each day. For cases in which daily work was not begun at a central place each day, the respondent was asked to provide as much information as possible to describe the area in which he or she worked most during the reference week.

    Comparability

    This data source is comparable to the decennial censuses for all journey to work variables. Since both the American Community Survey and the decennial censuses are related to a "reference week" that has some variability, the data do not reflect any single week. Since the American Community Survey data are collected over 12 months, the reference week in American Community Survey has a greater range of variation. (See "Reference Week.")
    For more detailed information regarding the difference of place of work and journey to work in the ACS and Census 2000, see Estimates about Journey to Work from the 2005 ACS, C2SS, and Census 2000 on the ACS website (http://www.census.gov/acs).

    See 2012 Code List on the ACS website (http://www.census.gov/acs) for Place of Work Code List.

    Labor Force Status
    See Employment Status.

    Language Spoken at Home
    Language Spoken at Home by the Respondent
    Data on language spoken at home were derived from answers to questions 14a and 14b in the 2012 American Community Survey. These questions were asked only of persons 5 years of age and older. Instructions mailed with the American Community Survey questionnaire instructed respondents to mark "Yes" on Question 14a if they sometimes or always spoke a language other than English at home, and "No" if a language was spoken only at school - or if speaking was limited to a few expressions or slang. For Question 14b, respondents printed the name of the non-English language they spoke at home. If the person spoke more than one non-English language, they reported the language spoken most often. If the language spoken most frequently could not be determined, the respondent reported the language learned first.

    Questions 14a and 14b referred to languages spoken at home in an effort to measure the current use of languages other than English. This category excluded respondents who spoke a language other than English exclusively outside of the home.

    An automated computer system coded write-in responses to Question 14b into more than 380 detailed language categories. This automated procedure compared write-in responses with a master computer code list - which contained approximately 55,000 previously coded language names and variants - and then assigned a detailed language category to each write- in response. The computerized matching assured that identical alphabetic entries received the same code. Clerical coding categorized any write-in responses that did not match the computer dictionary. When multiple languages other than English were specified, only the first was coded.
    The write-in responses represented the names people used for languages they spoke. They may not have matched the names or categories used by professional linguists. The categories used were sometimes geographic and sometimes linguistic. The Four Main Group Classifications and Thirty-Nine Subgroup Classifications of Languages Spoken at Home with Illustrative Examples table in Appendix A provides an illustration of the content of the classification schemes used to present language data.

    Household Language
    In households where one or more people spoke a language other than English, the household language assigned to all household members was the non- English language spoken by the first person with a non-English language. This assignment scheme ranked household members in the following order: householder, spouse, parent, sibling, child, grandchild, other relative, stepchild, unmarried partner, housemate or roommate, and other nonrelatives. Therefore, a person who spoke only English may have had a non-English household language assigned during tabulations by household language.

    Government agencies use information on language spoken at home for their programs that serve the needs of the foreign-born and specifically those who have difficulty with English. Under the Voting Rights Act, language is needed to meet statutory requirements for making voting materials available in minority languages. The Census Bureau is directed, using data about language spoken at home and the ability to speak English, to identify minority groups that speak a language other than English and to assess their English-speaking ability. The U.S. Department of Education uses these data to prepare a report to Congress on the social and economic status of children served by different local school districts.

    Government agencies use information on language spoken at home for their programs that serve the needs of the foreign-born and specifically those who have difficulty with English. Under the Voting Rights Act, language is needed to meet statutory requirements for making voting materials available in minority languages. The Census Bureau is directed, using data about language spoken at home and the ability to speak English, to identify minority groups that speak a language other than English and to assess their English-speaking ability. The U.S. Department of Education uses these data to prepare a report to Congress on the social and economic status of children served by different local school districts. State and local agencies concerned with aging develop health care and other services tailored to the language and cultural diversity of the elderly under the Older Americans Act.

    Question/Concept History

    The Language Spoken Questions have changed only once since ACS began. Examples of languages were listed immediately followed the question "What is this language?" in the 1996-1998 questionnaire. Starting in 1999, the list of languages was moved to below the write-in box.

    Limitation of the Data

    The language question is about current use of a non-English language, not about ability to speak another language or the use of such a language in the past. People who speak a language other than English outside of the home are not reported as speaking a language other than English. Similarly, people whose mother tongue is a non- English language but who do not currently use the language at home do not report the language. Some people who speak a language other than English at home may have first learned that language in school. These people are expected to indicate speaking English "Very well."

    Comparability

    All years of ACS language data are comparable to each other. They are also comparable to Census data from 1980, 1990 and 2000.
    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Language Code List.

    Marital Status/Marital History
    The data on marital status and marital history were derived from answers to Questions 20 through 23 in the 2012 American Community Survey. The marital status question is asked to determine the status of the person at the time of interview. Many government programs need accurate information on marital status, such as the number of married women in the labor force, elderly widowed individuals, or young single people who may establish homes of their own. The marital history data enables multiple agencies to more accurately measure the effects of federal and state policies and programs that focus on the well-being of families. Marital history data can provide estimates of marriage and divorce rates and duration, as well as flows into and out of marriage. This information is critical for more refined analyses of eligibility for program services and benefits, and of changes resulting from federal policies and programs.

    Before 2008, the marital status question was asked of all people. Beginning in 2008, the question on marital status was asked only for people 15 years old and over. People 15 and over were asked whether they were "now married," "widowed," "divorced," "separated," or "never married." People in common-law marriages were allowed to report the marital status they considered the most appropriate. When marital status was not reported, it was imputed according to the person's relationship to the householder, sex, and age.

    Differences in the number of married males and females occur because there is no step in the weighting process to equalize the weighted estimates of husbands and wives.

    Never Married
    Includes all people who have never been married, including people whose only marriage(s) was annulled.

    Ever Married
    Includes people ever married at the time of interview (including those now married, separated, widowed, or divorced).

    Now Married, Except Separated
    Includes people whose current marriage has not ended through widowhood, divorce, or separation (regardless of previous marital history). The category may also include couples who live together or people in common-law marriages if they consider this category the most appropriate. In certain tabulations, currently married people are further classified as "spouse present" or "spouse absent." In tabulations, unless otherwise specified, "now married" does not include same-sex married people even if the marriage was performed in a state issuing marriage certificates for same-sex couples.

    Separated
    Includes people legally separated or otherwise absent from their spouse because of marital discord. Those without a final divorce decree are classified as "separated." This category also includes people who have been deserted or who have parted because they no longer want to live together, but who have not obtained a divorce.

    Widowed
    Includes widows and widowers who have not remarried.

    Divorced
    Includes people who are legally divorced and who have not remarried. Those without a final divorce decree are classified as "separated."
    In selected tabulations, data for married and separated people are reorganized and combined with information on the presence of the spouse in the same household.

    Now Married
    All people whose current marriage has not ended by widowhood or divorce. This category includes people defined above as "separated."

    • Spouse Present -
    Married people whose wife or husband was reported as a member of the same household, including those whose spouses may have been temporarily absent for such reasons as travel or hospitalization.
  • Spouse Absent - Married people whose wife or husband was not reported as a
    member of the same household or people reporting they were married and living in a group quarters facility.
  • Separated - Defined above.
  • Spouse Absent, Other - Married people whose wife or husband was not reported as a member of the same household, excluding separated. Included is any person whose spouse was employed and living away from home or in an institution or serving away from home in the Armed Forces.

  • Differences between the number of married males and the number of married females occur because: some husbands and wives have their usual residence in different areas; and husbands and wives do not have the same weights. By definition, the numbers would be the same.

    Median Age at First Marriage
    The median age at first marriage is calculated indirectly by estimating the proportion of young people who will marry during their lifetime, calculating one-half of this proportion, and determining the age (at the time of the survey) of people at this half-way mark by osculatory interpolation. It does not represent the actual median age of the population who married during the calendar year. It is shown to the nearest tenth of a year. Henry S. Shryock and Jacob S. Siegel outline the osculatory procedure in Methods and Materials of Demography, First Edition (May 1973), Volume 1, pages 291-296.

    Marital History
    Beginning in 2008, people 15 years and over who were ever married (married, widowed, separated, or divorced) were asked if they had been married, widowed, or divorced in the past 12 months. They were asked how many times (once, two times, three or more times) they have been married, and the year of their last marriage.

    Question/Concept History - The word "current" was dropped from the 1996-1998 question. Since 1999, the question states, "What is this person's marital status?" The American Community Survey began providing the median age at first marriage with the 2004 data. Data on marital history were first collected in 2008 at the request of the Department of Health and Human Services to provide more detailed annual information on the marital status of the population. Before 2008, the marital status question was asked of all people and only tabulated for those 15 and over. In 2008, marital status was moved from the basic demographic section, at the beginning of the ACS questionnaire, to the detailed person section - a part of the questionnaire where questions were asked of only people 15 and over. The marital history questions follow the marital status question on the questionnaire.

    Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations have marital status distributions that are very different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the marital status distribution. This is particularly true for areas with a substantial GQ population.

    Comparability - The data on marital status can be compared to previous ACS years and to similar data collected on CPS and SIPP. Marital status is no longer asked on the Decennial Census. The marital history data, and particularly marriage and divorce rates derived from the questions asking if the person got married or divorced in the past 12 months is comparable to vital statistics collected by the National Center for Health Statistics (NCHS).

    Means of Transportation to Work
    See Journey to Work.

    Migration
    See Residence 1 Year Ago.

    Native Population
    The native population includes anyone who was a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were born in the United States, Puerto Rico, a U.S. Island Area (such as Guam), or abroad of American (U.S. citizen) parent or parents. See Citizenship Status.

    Nativity
    See Place of Birth.

    Nativity of Parent
    Nativity of parent indicates the nativity (native or foreign born) of the parent(s) of children living in a family or subfamily with one or more parents present in the household. It applies to "own children," that is, never married children under 18 years of age living with one or more of their parents. (See also "Own Child.") The nativity of the child's parent(s) is determined by the citizenship status of the parent(s). A person is considered native if he/she is a native United States citizen at birth, and foreign born if he/she is not a United States citizen at birth. (See also "Place of Birth.")

    Limitation of the Data - Nativity of parent does not provide information about children over the age of 18 who may live in the same household as their parents, or children of any age who live apart from their parents.

    Comparability - No comparable data were published prior to 2006. However, prior years do include the nativity and relationship data from which "nativity of parent" was created.

    Occupation
    Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2012 American Community Survey. Question 45 asks: "What kind of work was this person doing?" Question 46 asks: "What were this person's most important activities or duties?"

    These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.



    These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.



    Coding Procedures - Occupation statistics are compiled from data that are coded based on the Standard Occupational Classification (SOC) Manual: 2010 (http://www.bls.gov/soc/), published by the Executive Office of the President, Office of Management and Budget. Census occupation codes, based on the 2010 SOC, provide 539 specific occupational categories, for employed people, including military, arranged into 23 major occupational groups.



    Respondents provided the data for the tabulations by writing on the questionnaires descriptions of the kind of work and activities they are doing. These write-ins are converted to a code category through automated coding. Cases not autocoded on both industry and occupation are sent to the clerical staff in the National Processing Center in Jeffersonville, Indiana who assign codes by comparing these descriptions to entries in the Alphabetical Index of Industries and Occupations

    (http://www.census.gov/people/io/methodology/indexes.html).



    Some occupation groups are related closely to certain industries. Operators of transportation equipment, farm operators and workers, and healthcare providers account for major portions of their respective industries of transportation, agriculture, and health care. However, the industry categories include people in other occupations. For example, people employed in agriculture include truck drivers and bookkeepers; people employed in the transportation industry include mechanics, freight handlers, and payroll clerks; and people employed in the health care industry include janitors, security guards, and secretaries.



    Editing Procedures - Following the coding operation, a computer edit and allocation process excludes all responses that should not be included in the universe, and evaluates the consistency of the remaining responses. The codes for occupation are checked for consistency with the industry and class of worker data provided for that respondent.



    Occasionally respondents supply occupation descriptions that are not sufficiently specific for precise classification, or they do not report on these questions at all. Certain types of incomplete entries are corrected using the Alphabetical Index of Industries and Occupations (http://www.census.gov/people/io/methodology/indexes.html).



    If one or more of the three codes (occupation, industry, or class of worker) is blank after the edit, a code is assigned from a donor respondent who is a "similar" person based on questions such as age, sex, educational attainment, income, employment status, and weeks worked. If all of the labor force and income data are blank, all of these economic questions are assigned from a "similar" person who had provided all the necessary data.



    Question/Concept History - Occupation data have been collected during decennial censuses since 1850. Starting with the 2010 Census, occupation data will no longer be collected during the decennial census. Long form data collection has transitioned to the American Community Survey. The American Community Survey began collecting data on occupation in 1996. The questions on occupation were designed to be consistent with the 1990 Census questions on occupation. American Community Survey questions on occupation have remained consistent between 1996 and 2012.



    Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have occupational distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the occupational distribution in some geographic areas with a substantial GQ population.



    Data on occupation, industry, and class of worker are collected for the respondent's current primary job or the most recent job for those who are not employed but have worked in the last 5 years. Other labor force questions, such as questions on earnings or work hours, may have different reference periods and may not limit the response to the primary job. Although the prevalence of multiple jobs is low, data on some labor force items may not exactly correspond to the reported occupation, industry, or class of worker of a respondent.



    Comparability - Comparability of occupation data was affected by a number of factors, primarily the system used to classify the questionnaire responses. Changes in the occupational classification system limit comparability of the data from one year to another. These changes are needed to recognize the "birth" of new occupations, the "death" of others, the growth and decline in existing occupations, and the desire of analysts and other users for more detail in the presentation of the data. Probably the greatest cause of noncomparability is the movement of a segment from one category to another. Changes in the nature of jobs, respondent terminology, and refinement of category composition made these movements necessary.



    ACS data from 1996 to 1999 used the same occupation classification systems used for the 1990 Census; therefore, the data are comparable. Since 1990, the occupation classification has been revised to reflect changes within the Standard Occupational Classification (SOC). The SOC was updated in 2000 and these changes were reflected in the Census 2000 occupation codes. The 2000-2002 ACS data used the same occupation classification systems used for Census 2000; therefore, the data are comparable. Because of the possibility of new occupations being added to the list of codes, the Census Bureau needed to have more flexibility in adding codes. Consequently, in 2002, Census occupation codes were expanded from three-digit codes to four-digit codes. For occupation, this entailed adding a "0" to the end of each occupation code. The SOC was revised once more in 2010. Based on the 2010 SOC changes, Census codes were revised resulting in a net gain of 30 Census occupation codes (from 509 occupations to 539 occupations). Most of these changes were concentrated in information technology, healthcare, printing, and human resources occupations. For more information on occupational comparability across classification systems, please see technical paper #65: The Relationship Between the 1990 Census and Census 2000 Industry and Occupation Classification Systems

    (http://www.census.gov/people/io/files/techpaper2000.pdf). For information on the 2010 SOC and Census codes, please see the summary of 2010 changes and the Census 2002 to 2010 occupation crosswalk on the Industry and Occupation Methodology page (http://www.census.gov/people/io/methodology/) on the ACS website (http://census.gov/acs).



    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Occupation Code List.



    See also, Industry and Class of Worker.



    Own Children
    See Household Type and Relationship.

    Period of Military Service
    See Veteran Status.

    Persons in Family
    See Household Type and Relationship.

    Persons in Household
    See Household Type and Relationship.

    Place of Birth
    The data on place of birth were derived from answers to Question 7 in the 2012 American Community Survey. Respondents were asked to select one of two categories: (1) in the United States, or (2) outside the United States. In the American Community Survey, respondents selecting category (1) were then asked to report the name of the state while respondents selecting category (2) were then asked to report the name of the foreign country, or Puerto Rico, Guam, etc. In the Puerto Rico Community Survey, respondents selecting category (1) were also asked to report the name of the state, while respondents selecting category (2) were then asked to print Puerto Rico or the name of the foreign country, or U.S. Virgin Islands, Guam, etc. People not reporting a place of birth were assigned the state or country of birth of another family member, or were allocated the response of another individual with similar characteristics. People born outside the United States were asked to report their place of birth according to current international boundaries. Since numerous changes in boundaries of foreign countries have occurred in the last century, some people may have reported their place of birth in terms of boundaries that existed at the time of their birth or emigration, or in accordance with their own national preference.

    The place of birth questions along with the citizenship status question provide essential data for setting and evaluating immigration policies and laws. Knowing the characteristics of immigrants helps legislators and others understand how different immigrant groups are assimilated. Federal agencies require these data to develop programs for refugees and other foreign-born individuals. Vital information on lifetime migration among states also comes from the place of birth question.

    Nativity
    Information on place of birth and citizenship status was used to classify the population into two major categories: native and foreign born.

    Native
    The native population includes anyone who was a U.S. citizen at birth. The native population includes those born in the United States, Puerto Rico, American Samoa, Guam, the Northern Marianas, or the U.S. Virgin Islands, as well as those born abroad of at least one U.S. citizen parent. The native population is divided into the following groups: people born in the state in which they resided at the time of the survey; people born in a different state, by region; people born in Puerto Rico or one of the U.S. Island Areas; and people born abroad with at least one U.S. citizen parent. (See also "Citizenship Status.")

    Foreign Born
    The foreign-born population includes anyone who was not a U.S. citizen at birth. This includes respondents who indicated they were a U.S. citizen by naturalization or not a U.S. citizen. (See also "Citizenship Status.")

    The foreign-born population is shown by selected area, country, or region of birth. The places of birth shown in data products were chosen based on the number of respondents who reported that area or country of birth.

    Question/Concept History

    The 1996-1998 American Community Survey question asked respondents to write in the U.S. state, territory, commonwealth or foreign country where this person was born. Beginning in 1999, the question asked "Where was this person born?" and provided two check-boxes, each with a write-in space.

    Limitation of the Data

    Beginning in 2006, the group quarters (GQ) population is included in the ACS. Some types of GQ populations may have place of birth distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the place of birth distribution. This is particularly true for areas with a substantial GQ population.

    Comparability

    This data source is comparable to the decennial censuses.
    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Place of Birth Code List.

    Place of Work
    See Journey to Work.

    Poverty Status in the Past 12 Months
    Poverty statistics in American Community Survey products adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) vary by age (under 65 years or 65 years and older). The poverty thresholds for two-person families also vary by the age of the householder. If a family's total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual's total income is less than the appropriate threshold, then that individual is considered to be in poverty.

    How the Census Bureau Determines Poverty Status
    In determining the poverty status of families and unrelated individuals, the Census Bureau uses thresholds (income cutoffs) arranged in a two-dimensional matrix. The matrix consists of family size (from one person to nine or more people) cross-classified by presence and number of family members under 18 years old (from no children present to eight or more children present). Unrelated individuals and two-person families are further differentiated by age of reference person (householder) (under 65 years old and 65 years old and over).

    To determine a person's poverty status, one compares the person's total family income in the last 12 months with the poverty threshold appropriate for that person's family size and composition (see example below). If the total income of that person's family is less than the threshold appropriate for that family, then the person is considered "below the poverty level," together with every member of his or her family. If a person is not living with anyone related by birth, marriage, or adoption, then the person's own income is compared with his or her poverty threshold. The total number of people below the poverty level is the sum of people in families and the number of unrelated individuals with incomes in the last 12 months below the poverty threshold.

    Since ACS is a continuous survey, people respond throughout the year. Because the income questions specify a period covering the last 12 months, the appropriate poverty thresholds are determined by multiplying the base-year poverty thresholds (1982) by the average of the monthly inflation factors for the 12 months preceding the data collection. See the table in Appendix A titled "Poverty Thresholds in 1982, by Size of Family and Number of Related Children Under 18 Years (Dollars)," for appropriate base thresholds. See the table "The 2012 Poverty Factors" in Appendix A for the appropriate adjustment based on interview month.

    For example, consider a family of three with one child under 18 years of age, interviewed in July 2012 and reporting a total family income of $14,000 for the last 12 months (July 2011 to June 2012). The base year (1982) threshold for such a family is $7,765, while the average of the 12 inflation factors is 2.35795. Multiplying $7,765 by 2.35795 determines the appropriate poverty threshold for this family type, which is $18,309. Comparing the family's income of $14,000 with the poverty threshold shows that the family and all people in the family are considered to have been in poverty. The only difference for determining poverty status for unrelated individuals is that the person's individual total income is compared with the threshold rather than the family's income.

    Individuals for Whom Poverty Status is Determined
    Poverty status was determined for all people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. These groups were excluded from the numerator and denominator when calculating poverty rates.

    Specified Poverty Levels
    Specified poverty levels are adjusted thresholds that are obtained by multiplying the official thresholds by specific factor. Using the threshold cited from the previous example (a family of three with one related child under 18 years responding in July 2012), the dollar value at 125 percent of the poverty threshold was $22,886 ($18,309 x 1.25).

    Income Deficit
    Income deficit represents the difference between the total income in the last 12 months of families and unrelated individuals below the poverty level and their respective poverty thresholds. In computing the income deficit, families reporting a net income loss are assigned zero dollars and for such cases the deficit is equal to the poverty threshold.

    This measure provides an estimate of the amount, which would be required to raise the incomes of all poor families and unrelated individuals to their respective poverty thresholds. The income deficit is thus a measure of the degree of the impoverishment of a family or unrelated individual. However, please use caution when comparing the average deficits of families with different characteristics. Apparent differences in average income deficits may, to some extent, be a function of differences in family size.

    Aggregate Income Deficit
    Aggregate income deficit refers only to those families or unrelated individuals who are classified as below the poverty level. It is defined as the group (e.g., type of family) sum total of differences between the appropriate threshold and total family income or total personal income. Aggregate income deficit is subject to rounding, which means that all cells in a matrix are rounded to the nearest hundred dollars. (For more information, see "Aggregate" under "Derived Measures.")

    Mean Income Deficit
    Mean income deficit represents the amount obtained by dividing the aggregate income deficit for a group below the poverty level by the number of families (or unrelated individuals) in that group. (The aggregate used to calculate mean income deficit is rounded. For more information, see "Aggregate Income Deficit.") As mentioned above, please use caution when comparing mean income deficits of families with different characteristics, as apparent differences may, to some extent, be a function of differences in family size. Mean income deficit is rounded to the nearest whole dollar. (For more information on means, see "Derived Measures.")

    Poverty Status of Households in the Past 12 Months
    Since poverty is defined at the family level and not the household level, the poverty status of the household is determined by the poverty status of the householder. Households are classified as poor when the total income of the householder's family in the last 12 months is below the appropriate poverty threshold. (For nonfamily householders, their own income is compared with the appropriate threshold.) The income of people living in the household who are unrelated to the householder is not considered when determining the poverty status of a household, nor does their presence affect the family size in determining the appropriate threshold. The poverty thresholds vary depending upon three criteria: size of family, number of children, and, for one- and two- person families, age of the householder.

    Question/Concept History -

    Derivation of the Current Poverty Measure

    When the original poverty definition was developed in 1964 by the Social Security Administration (SSA), it focused on family food consumption. The U.S. Department of Agriculture (USDA) used its data about the nutritional needs of children and adults to construct food plans for families. Within each food plan, dollar amounts varied according to the total number of people in the family and the family's composition, that is, the number of children within each family. The cheapest of these plans, the Economy Food Plan, was designed to address the dietary needs of families on an austere budget.

    Since the USDA's 1955 Food Consumption Survey showed that families of three or more people across all income levels spent roughly one-third of their income on food, the SSA multiplied the cost of the Economy Food Plan by three to obtain dollar figures for total family income. These dollar figures, with some adjustments, later became the official poverty thresholds. Since the Economy Food Plan budgets varied by family size and composition, so too did the poverty thresholds. For two-person families, the thresholds were adjusted by slightly higher factors because those households had higher fixed costs. Thresholds for unrelated individuals were calculated as a fixed proportion of the corresponding thresholds for two-person families.

    The poverty thresholds are revised annually to allow for changes in the cost of living as reflected in the Consumer Price Index for All Urban Consumers (CPI-U). The poverty thresholds are the same for all parts of the country; they are not adjusted for regional, state, or local variations in the cost of living.

    Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) is included in the ACS. The part of the group quarters population in the poverty universe (for example, people living in group homes or those living in agriculture workers' dormitories) is many times more likely to be in poverty than people living in households. Direct comparisons of the data would likely result in erroneous conclusions about changes in the poverty status of all people in the poverty universe.

    Comparability - Because of differences in survey methodology (questionnaire design, method of data collection, sample size, etc.), the poverty rate estimates obtained from American Community Survey data may differ from those reported in the Current Population Survey, Annual Social and Economic Supplement, and those reported in Census 2000. Please refer to (http://www.census.gov/acs) for more details.

    Private Vehicle Occupancy
    See Journey to Work.

    The data on race were derived from answers to the question on race that was asked of all people. The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self- identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or sociocultural groups. People may choose to report more than one race to indicate their racial mixture, such as "American Indian" and "White." People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

    The racial classifications used by the Census Bureau adhere to the October 30, 1997, Federal Register notice entitled, "Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity" issued by OMB. These standards govern the categories used to collect and present federal data on race and ethnicity. OMB requires five minimum categories (White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander) for race. The race categories are described below with a sixth category, "Some Other Race," added with OMB approval. In addition to the five race groups, OMB also states that respondents should be offered the option of selecting one or more races.

    If an individual did not provide a race response, the race or races of the householder or other household members were imputed using specific rules of precedence of household relationship. For example, if race was missing for a natural-born child in the household, then either the race or races of the householder, another natural-born child, or spouse of the householder were imputed.

    If race was not reported for anyone in the household, then the race or races of a householder in a previously processed household were imputed.
    Definitions from OMB guide the Census Bureau in classifying written responses to the race question:

    A person having origins in any of the original peoples of Europe, the Middle East, or North Africa. It includes people who indicate their race as "White" or report entries such as Irish, German, Italian, Lebanese, Arab, Moroccan, or Caucasian.

    Black or African American
    A person having origins in any of the Black racial groups of Africa. It includes people who indicate their race as "Black, African Am., or Negro" or report entries such as African American, Kenyan, Nigerian, or Haitian.

    American Indian or Alaska Native
    A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment. This category includes people who indicate their race as "American Indian or Alaska Native" or report entries such as Navajo, Blackfeet, Inupiat, Yup'ik, or Central American Indian groups, or South American Indian groups.

    Respondents who identified themselves as "American Indian or Alaska Native" were asked to report their enrolled or principal tribe. Therefore, tribal data in tabulations reflect the written entries reported on the questionnaires. Some of the entries (for example, Metlakatla Indian Community and Umatilla) represent reservations or a confederation of tribes on a reservation. The information on tribe is based on self-identification and, therefore, does not reflect any designation of federally or state-recognized tribe. The information for the 2012 ACS Detail Race tables were derived from the American Indian and Alaska Native Tribal Classification List for the 2010 Census, which was updated through 2009 based on the annual Federal Register notice entitled "Indian Entities Recognized and Eligible to Receive Services From the United States Bureau of Indian Affairs," Department of the Interior, Bureau of Indian Affairs, issued by OMB, and through consultation with American Indian and Alaska Native communities and leaders.

    The American Indian categories shown in the 2012 ACS Detailed Race tables represent tribal groupings, which refer to the combining of individual American Indian tribes, such as Fort Sill Apache, Mescalero Apache, and San Carlos Apache, into the general Apache tribal grouping.

    The Alaska Native categories shown in the 2012 ACS Detailed Race tables represent tribal groupings, which refer to the combining of individual Alaska Native tribes, such as King Salmon Tribe, Native Village of Kanatak, and Sun'aq Tribe of Kodiak, into the general Aleut tribal grouping.

    All Other American Indian Tribes (with only one tribe reported)
    Includes respondents who provide a response of another American Indian tribe not shown
    separately, such as Abenaki, Catawba, Eastern Tribes, Kickapoo, Mattaponi, Quapaw, Shawnee, or Yuchi.

    American Indian Tribes, not specified
    Includes people who provide a generic term such as "American Indian" or tribal groupings not elsewhere classified.

    Alaska Native Tribes, not specified
    Includes people who provide a generic term such as "Alaska Indian" or "Alaska Native" or tribal groupings not elsewhere classified.

    American Indian Tribes or Alaska Native Tribes, not specified
    Includes respondents who checked the American Indian or Alaska Native response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "American Indian or Alaska Native."

    Two or more American Indian or Alaska Native Tribes
    Includes respondents who provided multiple American Indian or Alaska Native Tribes responses such as Blackfeet and Pueblo; or Alaskan Athabascan and Tlingit-Haida; or Paiute and Aleut.

    A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. It includes people who indicate their race as "Asian Indian," "Chinese," "Filipino," "Korean," "Japanese," "Vietnamese," and "Other Asian" or provide other detailed Asian responses.

    Asian Indian
    Includes respondents who indicate their race as "Asian Indian" or report entries such as India or East Indian.

    Bangladeshi
    Includes respondents who report entries such as Bangladeshi or Bangladesh.

    Bhutanese
    Includes respondents who report entries such as Bhutanese or Bhutan.

    Burmese
    Includes respondents who report entries such as Burmese or Burma.

    Cambodian
    Includes respondents who report entries such as Cambodian or Cambodia.

    Chinese, except Taiwanese
    Includes respondents who indicate their race as "Chinese" or report entries such as China or Chinese American.

    Filipino
    Includes respondents who indicate their race as "Filipino" or report entries such as Philippines or Filipino American. Hmong. Includes respondents who report entries such as Hmong or Mong.

    Indonesian
    Includes respondents who report entries such as Indonesian or Indonesia.

    Japanese
    Includes respondents who indicate their race as "Japanese" or report entries such as Japan or Japanese American.

    Korean
    Includes respondents who indicate their race as "Korean" or report entries such as Korea or Korean American.

    Laotian
    Includes respondents who report entries such as Laotian or Laos.

    Malaysian
    Includes respondents who report entries such as Malaysian or Malaysia.

    Mongolian
    Includes respondents who report entries such as Mongolian, Mongolia or Mongol.

    Nepalese
    Includes respondents who report entries such as Nepalese or Nepal.

    Okinawan
    Includes respondents who report entries such as Okinawan or Okinawa.

    Pakistani
    Includes respondents who report entries such as Pakistani or Pakistan.

    Sri Lankan
    Includes respondents who report entries such as Sri Lankan or Sri Lanka.

    Taiwanese
    Includes respondents who report entries such as Taiwanese or Taiwan.

    Includes respondents who report entries such as Thai or Thailand. Vietnamese. Includes respondents who indicate their race as "Vietnamese" or report entries such as Vietnam or Vietnamese American.

    Other Asian, specified
    Includes respondents who provide a response of another Asian group not shown separately, such as Iwo Jiman, Maldivian, or Singaporean.

    Other Asian, not specified
    Includes respondents who checked the "Other Asian" response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian," or "Asiatic."

    Two or more Asian
    Includes respondents who provided multiple Asian responses such as Asian Indian and Japanese; or Vietnamese, Chinese and Hmong.

    Native Hawaiian or Other Pacific Islander
    A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. It includes people who indicate their race as "Native Hawaiian," "Guamanian or Chamorro," "Samoan," and "Other Pacific Islander" or provide other detailed Pacific Islander responses.

    Native Hawaiian
    Includes respondents who indicate their race as "Native Hawaiian" or report entries such as Part Hawaiian or Hawaiian.

    Samoan
    Includes respondents who indicate their race as "Samoan" or report entries such as American Samoan or Western Samoan.

    Tongan
    Includes respondents who report entries such as Tongan or Tonga.

    Other Polynesian
    Includes respondents who provide a response of another Polynesian group, such as Tahitian, Tokelauan, or wrote in a generic term such as "Polynesian."

    Guamanian or Chamorro
    Includes respondents who indicate their race as "Guamanian or Chamorro" or report entries such as Chamorro or Guam.

    Marshallese
    Includes respondents who report entries such as Marshallese or Marshall Island.

    Other Micronesian
    Includes respondents who provide a response of another Micronesian group, such as Carolinian, Chuukese, I-Kiribati, Kosraean, Mariana Islander, Palauan, Pohnpeian, Saipanese, Yapese, or wrote in a generic term such as "Micronesian."

    Fijian
    Includes respondents who report entries such as Fijian or Fiji.

    Other Melanesian
    Includes respondents who provide a response of another Melanesian group, such as Papua New Guinean, Ni-Vanuatu (New Hebrides Islander), Solomon Islander, or wrote in a generic term such as "Melanesian."

    Other Pacific Islander, not specified
    Includes respondents who checked the Other Pacific Islander response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Pacific Islander."

    Two or more Native Hawaiian and Pacific Islander
    Includes respondents who provide multiple Pacific Islander responses such as Native Hawaiian and Guamanian or Chamorro; or Tokelauan and Tongan.

    Some Other Race
    Includes all other responses not included in the "White," "Black or African American," "American Indian or Alaska Native," "Asian," and "Native Hawaiian or Other Pacific Islander" race categories described above. Respondents reporting entries such as multiracial, mixed, interracial, or a Hispanic, Latino, or Spanish group (for example, Mexican, Puerto Rican, Cuban, or Spanish) in response to the race question are included in this category.

    Two or More Races
    People may choose to provide two or more races either by checking two or more race response check boxes, by providing multiple responses, or by some combination of check boxes and other responses. The race response categories shown on the questionnaire are collapsed into the five minimum race groups identified by OMB, and the Census Bureau's "Some Other Race" category. For data product purposes, "Two or More Races" refers to combinations of two or more of the following race categories:

    1. White
    2. Black or African American
    3. American Indian or Alaska Native
    4. Asian
    5. Native Hawaiian or Other Pacific Islander
    6. Some Other Race

    There are 57 possible combinations (see "Race Combinations" in Appendix A) involving the race categories shown above. Thus, according to this approach, a response of "White" and "Asian" was tallied as Two or More Races, while a response of "Japanese" and "Chinese" was not because "Japanese" and "Chinese" are both Asian responses.

    Race Concepts
    Given the many possible ways of displaying data on race, data products will provide varying levels of detail. There are several concepts used to display and tabulate race information for the six major race categories (White; Black or African American; American Indian or Alaska Native; Asian; Native Hawaiian or Other Pacific Islander; and Some Other Race) and the various details within these groups.

    The concept "race alone" includes people who reported a single entry (i.e., Korean) and no other race, as well as people who reported two or more entries within the same major race group (i.e., Asian). For example, respondents who reported Korean and Vietnamese are part of the larger "Asian alone" race group.

    The concept "race alone or in combination" includes people who reported a single race alone (i.e., Asian) and people who reported that race in combination with one or more of the other major race groups (i.e., White, Black or African American, American Indian and Alaska Native, Native Hawaiian and Other Pacific Islander, and Some Other Race). The "race alone or in combination" concept, therefore, represents the maximum number of people who reported as that race group, either alone, or in combination with another race(s). The sum of the six individual race "alone or in combination" categories may add to more than the total population because people who reported more than one race were tallied in each race category.

    The concept "race alone or in any combination" applies only to detailed race iteration groups, such as American Indian and Alaska Native tribes, detailed Asian groups, and detailed Pacific Islander groups. For example, Korean alone or in any combination includes people who reported a single response (i.e., Korean), people who reported Korean and another Asian group (i.e., Korean and Vietnamese), and people who reported Korean in combination with one or more other non-Asian race groups (i.e., White, Black or African American, American Indian and Alaska Native, Native Hawaiian and Other Pacific Islander, or Some Other Race).

    Coding of Write-in Entries
    The 2012 ACS included an automated review, computer edit, and coding operation on a 100 percent basis for the write-in responses to the race question, similar to that used in the 2010 Census. There were two types of coding operations: (1) automated coding where a write-in response was automatically coded if it matched a write-in response already contained in a database known as the "master file" and (2) expert coding, which took place when a write-in response did not match an entry already on the master file and was sent to expert coders familiar with the subject matter. During the coding process, subject-matter specialists reviewed and coded written entries from the response areas on the race question: American Indian or Alaska Native, Other Asian, Other Pacific Islander, and Some Other Race. Up to 30 text characters were collected from each race write-in area, and up to two responses were coded and tabulated from each separate race write-in area.

    Question/Concept History

    1996-1998 American Community Survey

    • The sequence of the questions on race and Hispanic origin was switched. In the 1996-1998 ACS, the question on race immediately followed the question on Hispanic origin. This approach differed from the 1990 Census, where the question on race preceded the question on Hispanic origin with two intervening questions.
    • The 1990 Census category, "Black or Negro" was changed to "Black, African Am."
    • The 1990 Census category, "Other race," was renamed "Some other race." A separate "Multiracial" category was added. The instruction to "print the race(s) or group below" pertained to both the "Some other race" and "Multiracial" categories.
    • The "Indian (Amer.)," "Other Asian/Pacific Islander," "Some other race," and "Multiracial" response categories all shared a single write-in area.

    1999-2002 American Community Survey
    • The response category "Black, African Am." was changed to "Black, African Am., or Negro" to correspond with the Census 2000 response category.
    • The separate 1990 Census and 1996-1998 ACS response categories "Indian (Amer.)," "Eskimo," and "Aleut," were combined into one response category, "American Indian or Alaska Native." Respondents were asked to "print name of enrolled or principal tribe" on a separate write-in line to correspond with the Census 2000 response category.
    • The 1990 Asian or Pacific Islander category was separated into two categories, "Asian" and "Native Hawaiian or Other Pacific Islander." Also, the six detailed Asian groups were alphabetized; and the three detailed Pacific Islander groups were alphabetized after the Native Hawaiian response category.
    • The response category "Hawaiian" was changed to "Native Hawaiian." The response category "Guamanian" was changed to "Guamanian or Chamorro." The response category "Other Asian/Pacific Islander" was split into two separate response categories, "Other Asian," and "Other Pacific Islander." These changes correspond to those in the Census 2000 response categories.
    • The separate "multiracial" response category was dropped. Rather, respondents were instructed to "Mark [x] one or more races to indicate what this person considers himself/herself to be." Respondents were allowed to select more than one category for race in Census 2000.
    • In the American Community Survey, the "Other Asian," "Other Pacific Islander," and "Some other race" response categories shared the same write-in area. On the Census 2000 questionnaire, only the "Other Asian" and "Other Pacific Islander" response categories shared the same write-in area, and the "Some other race" category had a separate write-in area.

    2003-2007 American Community Survey
    • The response category "Black, African Am., or Negro" was changed to "Black or African American."

    Puerto Rico Community Survey, started in 2005
    • Separate questions on race and Hispanic origin were included on the questionnaire. These questions were identical to the questions used in the United States.
    2008-2012 American Community Survey
    • The wording of the race question was changed to read, "What is Person 1's race? Mark (X) one or more boxes" and the reference to what this person considers him/herself to be was deleted.
    • The response category "Black or African American" was changed to "Black, African Am., or Negro."
    • Examples were added to the "Other Asian" response categories (Hmong, Laotian, Thai, Pakistani, Cambodian, and so on) and the "Other Pacific Islander" response categories (Fijian, Tongan, and so on).
    Limitation of the data - Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have race distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the race distribution. This is particularly true for areas with a substantial GQ population.

    Comparability - The data on race in the 2012 American Community Survey are not directly comparable across all years. Ongoing research conducted following the 1990 Census affected the ACS question on race since its inception in 1996. Also, the October 1997 revised standards for federal data on race and ethnicity issued by the OMB led to changes in the question on race for Census 2000. Consequently, in order to achieve consistency, other census-administered surveys such as the ACS were modified to reflect changes required by OMB. The 2010 Census and ACS data collections continue to follow the 1997 OMB Standards.

    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Race Code List.

    Reference Week
    The data on employment status and journey to work relate to the reference week, that is, the calendar week preceding the date on which the respondents completed their questionnaires or were interviewed. This week is not the same for all respondents since the interviewing was conducted over a 12-month period. The occurrence of holidays during the relative reference week could affect the data on actual hours worked during the reference week, but probably had no effect on overall measurement of employment status.

    Relatives and Nonrelatives
    See Household Type and Relationship.

    Residence 1 Year Ago
    The data on residence 1 year ago were derived from answers to Question 15 in the 2012 American Community Survey, which were asked of the population 1 year and older. For the American Community Survey, people who had moved from another residence in the United States or Puerto Rico 1 year earlier were asked to report the exact address (number and street name); the name of the city, town, or post office; the name of the U.S. county or municipio in Puerto Rico; state or Puerto Rico; and the ZIP Code where they lived 1 year ago. People living outside the United States and Puerto Rico were asked to report the name of the foreign country or U.S. Island Area where they were living 1 year ago.

    For the Puerto Rico Community Survey, people who moved from another residence in Puerto Rico or the United States 1 year ago were asked to report the exact address, including the development or condominium name; the name of the city, town, or post office; the municipio in Puerto Rico (county equivalent) or county in the U.S.; and the ZIP Code where they lived. People living outside Puerto Rico and the United States were asked to report the name of the foreign country or U.S. Island Area where they were living 1 year ago.

    Residence 1 year ago is used in conjunction with location of current residence to determine the extent of residential mobility of the population and the resulting redistribution of the population across the various states, metropolitan areas, and regions of the country.

    When no information on previous residence was reported for a person, information for other family members, if available, was used to assign a location of residence 1 year ago. All cases of nonresponse or incomplete response that were not assigned a previous residence based on information from other family members were allocated the previous residence of another person with similar characteristics who provided complete information.

    The tabulation category, "Same house," includes all people 1 year and over who did not move during the 1 year as well as those who had moved and returned to their residence 1 year ago. The category, "Different house in the United States" includes people who lived in the United States 1 year ago but in a different house or apartment from the one they occupied at the time of interview. These movers are then further subdivided according to the type of move.

    In most tabulations, movers within the U.S. are divided into three groups according to their previous residence: "Different house, same county," "Different county, same state," and "Different state." The last group may be further subdivided into region of residence 1 year ago. An additional category, "Abroad," includes those whose previous residence was in a foreign country, Puerto Rico, American Samoa, Guam, the Northern Marianas, or the U.S. Virgin Islands, including members of the Armed Forces and their dependents. Some tabulations show movers who were residing in Puerto Rico or one of the U.S. Island Areas 1 year ago separately from those residing in foreign countries.

    In most tabulations, movers within Puerto Rico are divided into two groups according to their residence 1 year ago: "Same municipio" and "Different municipio." Other tabulations show movers within or between metropolitan areas similar to the stateside tabulations.

    Residence-1-Year-Ago-based Geography
    The characteristics of movers may be shown using either current residence-based or previous residence-based geography. If you are interested in the number and characteristics of movers living in a specific area, you should use the standard (residence-based) tables. If you are interested in the number and characteristics of movers who previous residence was in a specific area, you should use the residence-1-year-ago-based tables. Because residence-1-year-ago information for movers cannot always be specified below the place level, the previous residence-based tables are presented only for selected geographic areas.

    Residence 1 year ago is used to assess the residential stability and the effects of migration in both urban and rural areas. This item provides information on the mobility of our population. Knowing the number and characteristics of movers is essential for federal programs dealing with employment, housing, education, and the elderly. The U.S. Department of Veterans Affairs develops its mandated projection of the need for hospitals and other veteran benefits for each state with migration data about veterans. The Census Bureau develops state age and sex estimates and small-area population projections based on data about residence 1 year ago.
    Question/Concept History

    The 1996-1998 questions asked about residence 5 years ago. Beginning in 1999, the time period was changed to that of 1 year ago, which reflects the ongoing data collection on the American Community Survey, and allows for annual estimatesof migration. Beginning in 1999, a separate write-in line and a skip instruction were added for a foreign country response. This write-in line was moved to one of the answer categories for the residence one year ago question. The migration parts (city, county, and state response areas) were also reordered. Beginning in 2003, the numerical order was changed so that part c of this question would not be displayed in a separate column of the questionnaire.

    Beginning with 2008, a write-in space for street address was included and the questions were reworded on both the ACS and the PRCS so that the geographic specificity is maintained for movers within and between the U.S. and Puerto Rico. Municipio of previous residence in Puerto Rico is available for people living in the United States as a result of this change. For more information, see the report titled Report P.3: Evaluation Report Covering Residence 1 Year Ago (Migration) on the ACS website (http://www.census.gov/acs).

    Limitation of the Data - Beginning in 2006, the group quarters (GQ) population is included in the ACS. Some types of GQ populations have residence one year ago (migration) distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the residence one year ago (migration) distribution. This is particularly true for areas with a substantial GQ population.

    Comparability - This data source is not comparable to the Census 2000. The ACS asked for residence 1 year ago whereas Census 2000 asked for residence 5 years ago.

    See the 2012 Code List on the ACS website (http://www.census.gov/acs) for Migration Code List.

    School Enrollment and Type of School
    School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

    Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2012 American Community Survey. People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to "include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree." Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

    School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in "vocational, technical, or business school" such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

    Enrolled in Public and Private School
    Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for "public school, public college," or "private school, private college, home school." The instruction guide defines a public school as "any school or college controlled and supported primarily by a local, county, state, or federal government." Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as "parental-guided education outside of public or private school for grades 1-12." Respondents who marked both the "public" and "private" boxes are edited to the first entry, "public."

    Grade in Which Enrolled
    From 1999-2007, in the American Community Survey, people reported to be enrolled in "public school, public college" or "private school, private college" were classified by grade or level according to responses to Question 10b, "What grade or level was this person attending?" Seven levels were identified: "nursery school, preschool;" "kindergarten;" elementary "grade 1 to grade 4" or "grade 5 to grade 8;" high school "grade 9 to grade 12;" "college undergraduate years (freshman to senior);" and "graduate or professional school (for example: medical, dental, or law school)."

    In 2008, the school enrollment questions had several changes. "Home school" was explicitly included in the "private school, private college" category. For question 10b the categories changed to the following "Nursery school, preschool," "Kindergarten," "Grade 1 through grade 12," "College undergraduate years (freshman to senior)," "Graduate or professional school beyond a bachelor's degree (for example: MA or PhD program, or medical or law school)." The survey question allowed a write-in for the grades enrolled from 1-12.

    Question/Concept History

    Since 1999, the American Community Survey enrollment status question (Question 10a) refers to "regular school or college," while the 1996-1998 American Community Survey did not restrict reporting to "regular" school, and contained an additional category for the "vocational, technical or business school."
    The 1996-1998 American Community Survey used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 American Community Survey questionnaire.

    Limitation of the Data

    Beginning in 2006, the population universe in the American Community Survey includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.

    Comparability

    Data about level of enrollment are also collected from the decennial Census and from the Current Population Survey (CPS). ACS data is generally comparable to data from the Census. Although it should be noted that the ACS reference period was 3 months preceding the date of interview, while the Census 2000 reference period was any time since February 1, 2000. For more information about the comparability of ACS and CPS data, please see the School Enrollment Fact Sheet on the ACS website (http://www.census.gov/hhes/school/data/acs/factsheet.html).

    Data on school enrollment also are collected and published by other federal, state, and local government agencies. Because these data are obtained from administrative records of school systems and institutions of higher learning, they are only roughly comparable to data from population censuses and surveys. Differences in definitions and concepts, subject matter covered, time references, and data collection methods contribute to the differences in estimates. At the local level, the difference between the location of the institution and the residence of the student may affect the comparability of census and administrative data because census data are collected from and based on a respondent's residence. Differences between the boundaries of school districts and census geographic units also may affect these comparisons.

    The data on sex were derived from answers to Question 3 in the 2012 American Community Survey. Individuals were asked to mark either "male" or "female" to indicate their biological sex. For most cases in which sex was invalid, the appropriate entry was determined from other information provided for that person, such as the person's given (i.e., first) name and household relationship. Otherwise, sex was allocated from a hot deck.

    Sex is asked for all persons in a household or group quarters. On the mailout/mailback paper questionnaire for households, sex is asked for all persons listed on the form. This form accommodates asking sex for up to 12 people listed as living or residing in the household for at least 2 months. If a respondent indicates that more people are listed as part of the total persons living in the household than the form can accommodate, or if any person included on the form is missing sex, then the household is eligible for Failed Edit Follow-up (FEFU). During FEFU operations, telephone center staffers call respondents to obtain missing data. This includes asking sex for any person in the household missing sex information. In Computer Assisted Telephone Interviews (CATI) and Computer Assisted Personal Interview (CAPI) instruments sex is asked for all persons. In 2006, the ACS began collecting data in group quarters (GQs). This included asking sex for persons living in a group quarters. For additional data collection methodology, please see http://www.census.gov/acs.

    Data on sex are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. The sex data collected on the forms are aggregated and provide the number of males and females in the population. These data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Data about sex are critical because so many federal programs must differentiate between males and females. The U.S. Departments of Education and Health and Human Services are required by statute to use these data to fund, implement, and evaluate various social and welfare programs, such as the Special Supplemental Food Program for Women, Infants, and Children (WIC) or the Low-Income Home Energy Assistance Program (LIHEAP). Laws to promote equal employment opportunity for women also require census data on sex. The U.S. Department of Veterans Affairs must use census data to develop its state projections of veterans' facilities and benefits. For more information on the use of sex data in Federal programs, please see http://www.census.gov/acs.

    Sex Ratio
    The sex ratio represents the balance between the male and female populations. Ratios above 100 indicate a larger male population, and ratios below 100 indicate a larger female population. This measure is derived by dividing the total number of males by the total number of females and then multiplying by 100. It is rounded to the nearest tenth.

    Question/Concept History

    Sex has been asked of all persons living in a household since the 1996 ACS Test phase. When group quarters were included in the survey universe in 2006, sex was asked of all person in group quarters as well.

    Beginning in 2008, the layout of the sex question response categories was changed to a horizontal side-by-side layout from a vertically stacked layout on the mail paper ACS questionnaire.

    Limitation of the data

    Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have sex distributions that are very different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the sex distribution. This is particularly true for a given geographic area. This is particularly true for areas with a substantial GQ population.

    The Census Bureau tested the changes introduced to the 2008 version of the sex question in the 2007 ACS Grid-Sequential Test (http://www.census.gov/acs). The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008.

    Comparability

    Sex is generally comparable across different data sources and data years. However, data users should still be aware of methodological differences that may exist between different data sources if they are comparing American Community Survey sex data to other data sources, such as Population Estimates or Decennial Census data. For example, the American Community Survey data are that of a respondent-based survey and subject to various quality measures, such as sampling and nonsampling error, response rates and item allocation. This differs in design and methodology from other data sources, such as Population Estimates, which is not a survey and involves computational methodology to derive intercensal estimates of the population. While ACS estimates are controlled to Population Estimates for sex at the nation, state and county levels of geography as part of the ACS weighting procedure, variation may exist in the sex structure of a population at lower levels of geography when comparing different time periods or comparing across time due to the absence of controls below the county geography level. For more information on American Community Survey data accuracy and weighting procedures, please see the ACS website (http://www.census.gov/acs).

    It should also be noted that although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties. See http://factfinder2.census.gov for data.

    Social Security income
    See Income in the Past 12 Months.

    Subfamily
    See Household Type and Relationship.

    Time Leaving Home to Go to Work
    See Journey to Work.

    Travel Time to Work
    See Journey to Work.

    Type of School
    See School Enrollment.

    Usual Hours Worked in the Past 12 Months
    See Work Experience.

    Veteran Status
    Data on veteran status and period of military service were derived from answers to Questions 26 and 27 in the 2012 American Community Survey.

    Veteran Status
    Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps. All other civilians are classified as nonveterans.

    While it is possible for 17 year olds to be veterans of the Armed Forces, ACS data products are restricted to the population 18 years and older.
    Answers to this question provide specific information about veterans. Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. ACS data define civilian veteran as a person 18 years old and over who served (even for a short time), but is not now serving on acting duty in the U.S. Army, Navy, Air Force, Marine Corps or Coast Guard, or who served as a Merchant Marine seaman during World War II. Individuals who have training for Reserves or National Guard but no active duty service are not considered veterans in the ACS. These data are used primarily by the Department of Veterans Affairs to measure the needs of veterans.

    Also, Veteran Status is:

    • Used at state and county levels to plan programs for medical and nursing home care for veterans.
    • Used by the Department of Veterans Affairs (VA) to plan the locations and sizes of veterans' cemeteries.
    • Used by local agencies, under the Older Americans Act, to develop health care and other services for elderly veterans. Used to allocate funds to states and local areas for employment and job training programs for veterans under the Job Training Partnership Act.
    Question/Concept History

    For the 1999-2002 American Community Survey, the question was changed to match the Census 2000 item. The response categories were modified by expanding the "No active duty service" answer category to distinguish persons whose only military service was for training in the Reserves or National Guard, from persons with no military experience whatsoever.

    Beginning in 2003, the "Yes, on active duty in the past, but not now" category was split into two categories. Veterans are now asked whether or not their service ended in the last 12 months.

    Limitation of the Data

    There may be a tendency for the following kinds of persons to report erroneously that they served on active duty in the Armed Forces: (a) persons who served in the National Guard or Military Reserves but were never called to duty; (b) civilian employees or volunteers for the USO, Red Cross, or the Department of Defense (or its predecessors, the Department of War and the Department of the Navy); and (c) employees of the Merchant Marine or Public Health Service.

    Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations may have period of military service and veteran status distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the period of service and veteran status distributions. This is particularly true for areas with a substantial GQ population.

    Comparability

    The ACS has two separate questions for veteran status and period of military service, whereas in Census 2000, it was a two-part question. The wording for the veteran status question remains the same; however, the response categories have changed over time (see the section "Question/Concept History").
    The Group Quarters (GQ) population was included in the 2006 ACS and not included in prior years of ACS data, thus comparisons should be made only if the geographic area of interest does not include a substantial GQ population.

    For comparisons to the Current Population Survey (CPS), please see "Comparison of ACS and ASEC Data on Veteran Status and Period of Military Service: 2007" on the ACS website (http://census.gov/acs).

    Period of Military Service
    People who indicate that they had ever served on active duty in the past or were currently on active duty are asked to indicate the period or periods in which they served. Currently, there are 11 periods of service on the ACS questionnaire. Respondents are instructed to mark a box for each period in which they served, even if just for part of the period. The periods were determined by the Department of Veterans Affairs and generally alternate between peacetime and wartime, with a few exceptions. The responses to this question are edited for consistency and reasonableness. The edit eliminates inconsistencies between reported period(s) of service and age of the person; it also removes reported combinations of periods containing unreasonable gaps (for example, it will not accept a response that indicated the person had served in World War II and in the Vietnam era, but not in the Korean conflict).

    Period of military service distinguishes veterans who served during wartime periods from those whose only service was during peacetime. Questions about period of military service provide necessary information to estimate the number of veterans who are eligible to receive specific benefits.

    Question/Concept History

    In 1999, the response categories were modified by closing the "August 1990 or later (including Persian Gulf War)" period at March 1995, and adding the "April 1995" or later category.

    For the 2001-2002 American Community Survey question, the response category was changed from "Korean conflict" to "Korean War."
    Beginning in 2003, the response categories for the question were modified in several ways. The first category "April 1995 or later" was changed to "September 2001 or later" to reflect the era that began after the events of September 11, 2001; the second category "August 1990 to March 1995" was then expanded to "August 1990 to August 2001 (including Persian Gulf War)." The category "February 1955 to July 1964" was split into two categories: "March 1961 to July 1964" and "February 1955 to February 1961." To match the revised dates for war-time periods of the Department of Veterans Affairs, the dates for the "World War II" category were changed from "September 1940 to July 1947" to "December 1941 to December 1946," and the dates for the "Korean War" were changed from "June 1950 to January 1955" to "July 1950 to January 1955." To increase specificity, the "Some other time" category was split into two categories: "January 1947 to June 1950" and "November 1941 or earlier."

    Limitation of the Data

    There may be a tendency for people to mark the most recent period in which they served or the period in which they began their service, but not all periods in which they served.

    Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have period of military service and veteran status distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the period of service and veteran status distributions. This is particularly true for areas with a substantial GQ population.

    Comparability

    Since Census 2000, the period of military service categories on the ACS questionnaire were updated to: 1) include the most recent period "September 2001 or later;" 2) list all "peace time" periods without showing a date-breakup in the list; and 3) update the Korean War and World War II dates to match the official dates as listed in US Code, Title 38. While the response categories differ slightly from those in Census 2000, data from the two questions can still be compared to one another.

    Due to an editing error, veteran's period of service (VPS) prior to 2007 was being incorrectly assigned for some individuals. The majority of the errors misclassified some people who reported only serving during the Vietnam Era as having served in the category "Gulf War and Vietnam Era." The remainder of the errors misclassified some people who reported only serving between the Vietnam Era and Gulf War as having served in the category "Gulf War."

    The Group Quarters (GQ) population was included in the 2006 ACS and not included in prior years of ACS data, thus comparisons should be made only if the geographic area of interest does not include a substantial GQ population.

    For comparisons to the Current Population Survey (CPS), please see "Comparison of ACS and ASEC Data on Veteran Status and Period of Military Service: 2007" on the ACS website (http://census.gov/acs).

    Service-Connected Disability Status and Ratings
    Data on service-connected disability- rating status and service-connected disability ratings were derived from answers to Questions 28a and 28b in 2012 American Community Survey.

    Service-Connected Disability-Rating Status
    People who indicated they had served on active duty in the U.S. Armed Forces, military Reserves, or National Guard, or trained with the Reserves or National Guard or were now on active duty were asked to indicate whether or not they had a Department of Veterans Affairs (VA) service-connected disability rating.

    These disabilities are evaluated according to the VA Schedule for Rating Disabilities in Title 38, U.S. Code of Federal Regulations, Part 4.

    "Service-connected" means the disability was a result of disease or injury incurred or aggravated during active military service.

    The Department of Veterans Affairs (VA) uses a priority system to allocate health care services among veterans enrolled in its programs. Data on service-connected disability status and ratings are used by the Department of Veterans Affairs to measure the demand for VA health care services in local market areas across the country as well as to classify veterans into priority groups for VA health care enrollment.

    Question/Concept History

    This question was added to the American Community Survey in 2008. For more information, see "Evaluation Report Covering Service-Connected Disability" on the ACS website (http://census.gov/acs).

    Limitation of the Data

    There may be a tendency for people to erroneously report having a 0 percent rating when they have no service-connected disability rating at all.

    Comparability - The question was not asked in Census 2000. It was added to the ACS in 2008.

    Service-Connected Disability Rating
    This question is asked of people who reported having a VA service-connected disability rating. These ratings are graduated according to degrees of disability on a scale from 0 to 100 percent, in increments of 10 percent. The ratings determine the amount of compensation payments made to the veterans. A zero-rating, which is different than having no rating at all, means a disability exists but it is not so disabling that it entitles the veteran to compensation payments.

    The Department of Veterans Affairs (VA) uses a priority system to allocate health care services among veterans enrolled in its programs. Data on service-connected disability status and ratings are used by the Department of Veterans Affairs to measure the demand for VA health care services in local market areas across the country as well as to classify veterans into priority groups for VA health care enrollment.

    Question/Concept History

    This question was added to the American Community Survey in 2008. For more information, see "Evaluation Report Covering Service-Connected Disability" on the ACS website (http://census.gov/acs).

    Limitation of the Data

    There may be a tendency for people to erroneously report having a 0 percent rating when they have no service-connected disability rating at all.

    Comparability

    The question was not asked in Census 2000. It was added to the ACS in 2008.

    Weeks Worked in the Past 12 Months
    See Work Experience.

    Work Experience
    The data on work experience were derived from answers to Questions 38, 39, and 40 in the 2012 American Community Survey. This term relates to work status in the past 12 months, weeks worked in the past 12 months, and usual hours worked per week worked in the past 12 months.

    To comply with provisions of the Civil Rights Act, the U.S. Department of Justice uses these data to determine the availability of individuals for work. Government agencies, in considering the programmatic and policy aspects of providing federal assistance to areas, have emphasized the requirements for reliable data to determine the employment resources available. Data about the number of weeks and hours worked last year are essential because these data allow the characterization of workers by full-time/part-time and full-year/part-year status. Data about working last year are also necessary for collecting accurate income data by defining the universe of persons who should have earnings as part of their total income.

    Work Status in the Past 12 Months
    The data on work status in the past 12 months were derived from answers to Question 38 in the 2012 American Community Survey. People 16 years old and over who worked 1 or more weeks according to the criteria described below are classified as "Worked in the past 12 months." All other people 16 years old and over are classified as "Did not work in the past 12 months."

    Weeks Worked in the Past 12 Months
    The data on weeks worked in the past 12 months were derived from responses to Question 39 in the 2012 American Community Survey, which was asked of people 16 years old and over who indicated that they worked during the past 12 months.

    The data pertain to the number of weeks during the past 12 months in which a person did any work for pay or profit (including paid vacation and paid sick leave) or worked without pay on a family farm or in a family business. Weeks of active service in the Armed Forces are also included.

    Usual Hours Worked Per Week Worked in the Past 12 Months
    The data on usual hours worked per week worked in the past 12 months were derived from answers to Question 40 in 2012 American Community Survey. This question was asked of people 16 years old and over who indicated that they worked during the past 12 months.

    The data pertain to the number of hours a person usually worked during the weeks worked in the past 12 months. The respondent was to report the number of hours worked per week in the majority of the weeks he or she worked in the past 12 months. If the hours worked per week varied considerably during the past 12 months, the respondent was to report an approximate average of the hours worked per week.

    People 16 years old and over who reported that they usually worked 35 or more hours each week during the weeks they worked are classified as "Usually worked full time;" people who reported that they usually worked 1 to 34 hours are classified as "Usually worked part time."

    Aggregate Usual Hours Worked Per Week in the Past 12 Months
    Aggregate usual hours worked is the sum of the values for usual hours worked each week of all the people in a particular universe. (For more information, see "Aggregate" under "Derived Measures.")

    Mean Usual Hours Worked Per Week in the Past 12 Months
    Mean usual hours worked is the number obtained by dividing the aggregate number of hours worked each week of a particular universe by the number of people in that universe. For example, mean usual hours worked for workers 16 to 64 years old is obtained by dividing the aggregate usual hours worked each week for workers 16 to 64 years old by the total number of workers 16 to 64 years old. Mean usual hours worked values are rounded to the nearest one-tenth of an hour. (For more information, see "Mean" under "Derived Measures.")

    Full-Time, Year-Round Workers
    All people 16 years old and over who usually worked 35 hours or more per week for 50 to 52 weeks in the past 12 months.

    Number of Workers in Family in the Past 12 Months
    The term "worker" as used for these data is defined based on the criteria for work status in the past 12 months.

    Question/Concept History

    Beginning in 2008, the weeks worked question was separated into 2 parts: part (a) asked whether the respondent worked 50 or more weeks in the past 12 months and part (b) asked respondents who answered 'no' to part (a) how many weeks they worked, even for a few hours.

    Limitation of the Data

    It is probable that the number of people who worked in the past 12 months and the number of weeks worked are understated since there is some tendency for respondents to forget intermittent or short periods of employment or to exclude weeks worked without pay. There may also be a tendency for people not to include weeks of paid vacation among their weeks worked; one result may be that the American Community Survey figures understate the number of people who worked "50 to 52 weeks."

    The American Community Survey data refer to the 12 months preceding the date of interview. Since not all people in the American Community Survey were interviewed at the same time, the reference period for the American Community Survey data is neither fixed nor uniform.

    Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have work experience distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the work experience distribution. This is particularly true for areas with a substantial GQ population.

    The Census Bureau tested the changes introduced to the 2008 version of the weeks worked question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Weeks Worked" on the ACS website (http://census.gov/acs).

    Comparability

    For information on Work Experience data comparability, please see the comparability section for Employment Status.

    Work Status in the Past 12 Months
    See Work Experience.

    Year of Entry
    The data on year of entry were derived from answers to Question 9 in the 2012 American Community Survey. This question was asked about Persons 1 through 5 in the ACS, and was restricted to those persons who on Question 8 answered that they were in citizenship categories (2) born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas, (3) born abroad of U.S. citizen parent or parents, (4) U.S. citizen by naturalization, or (5) not a U.S citizen.

    All respondents born outside the United States were asked for the year in which they came to live in the United States. This includes people born in Puerto Rico and U.S. Island Areas; people born abroad of an U.S. citizen parent or parents; and the foreign born. (See "Citizenship Status.") For the Puerto Rico Community Survey, respondents were asked for the year in which they came to live in Puerto Rico.

    The responses to this question indicate when persons born outside of the U.S. came to live in the United States.

    Question/Concept History

    Since 1996, the year of entry questions for the American Community Survey and for the Puerto Rico Survey were identical. An instruction was added beginning in 1999 to "Print numbers in boxes."

    Limitation of the Data

    Respondents were directed to indicate the year they entered the U.S. "to live" (or "to live" in Puerto Rico, for the Puerto Community Survey). For respondents who entered the U.S. (or entered Puerto Rico for the Puerto Rico Community Survey) multiple times, the interviewers were instructed to request the most recent year of entry. For respondents who entered multiple times and did not ask the interviewer for clarification or who mailed back the questionnaire without being interviewed in person, it is unclear which year of entry was provided (i.e. first or most recent).

    Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have year of entry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the year of entry distribution. This is particularly true for areas with substantial GQ populations.

    Comparability

    Year of entry was comparable across ACS years. A note of caution when comparing ACS and Census 2000 year of entry data: Census 2000 represents data collected as of April 1, 2000 and thus the "2000" year of entry category accounts only for the first quarter (Jan-Mar) in 2000. In comparison, the ACS represents data collected throughout the entire year and thus the "2000" year of entry category accounts for the entire year of 2000.

    Derived Measures
    Census data products include various derived measures, such as medians, means, and percentages, as well as certain rates and ratios. Most derived measures that round to less than 0.1 are shown as zero.

    Aggregate
    See "Mean."

    Average
    See "Mean."

    Gini Index
    The Gini is a measure of how much a distribution varies from a proportionate distribution. A purely proportionate distribution would have every value in the distribution being equal (that is 20% of the values would equal 20% of the aggregate total of all the values). This is also known as "perfect equality" - all households have an equal share of income. An example of a distribution that deviates the most from perfect equality would be have every value except one equal to zero, and one value that would be equal to the nonzero aggregate total for all the values. This is also known as "perfect inequality" - one household has all income.
    The Gini ranges from zero (perfect equality) to one (perfect inequality), and it is calculated by measuring the difference between a diagonal line (the purely proportionate distribution) and the distribution of actual values (a Lorenz curve). This measure is presented for household income.

    Interpolation
    Interpolation is frequently used to calculate medians or quartiles and to approximate standard errors from tables based on interval data. Different kinds of interpolation may be used to estimate the value of a function between two known values, depending on the form of the distribution. The most common distributional assumption is that the data are linear, resulting in linear interpolation.

    This measure represents an arithmetic average of a set of values. It is derived by dividing the sum (or aggregate) of a group of numerical questions by the total number of questions in that group. For example, mean household earnings is obtained by dividing the aggregate of all earnings reported by individuals with earnings living in households by the total number of households with earnings. (Additional information on means and aggregates is included in the separate explanations of many population and housing variables.)

    Aggregate
    An aggregate is the sum of the values for each of the elements in the universe. For example, aggregate household income is the sum of the incomes of all households in a given geographic area. Means are derived by dividing the aggregate by the appropriate universe. When an aggregate used as a numerator is rounded in the detailed (base) tables, the rounded value is used for the calculation of the mean.

    Rounding for selected aggregates
    To protect the confidentiality of responses, the aggregates shown in matrices for the list of subjects below are rounded. This means that the aggregates for these subjects, except for travel time to work, are rounded to the nearest hundred dollars. Unless special rounding rules apply (see below); $150 rounds up to $200; $149 rounds down to $100; $100 stays $100 unless otherwise noted. Note that each cell in a matrix is rounded individually. This means that an aggregate value shown for the United States may not necessarily be the sum total of the aggregate values in the matrices for the states. This also means that the cells in the aggregate matrices may not add to the total and/or subtotal lines.

    Special rounding rules for aggregates.

    -If the dollar value is -$99 through +$99, then the dollar value is rounded to $0.

    -If the dollar value is less than -$100, then the dollar value is rounded to the nearest -$100.

    -If the dollar value is $100 or -$100, do not change the value.

    Aggregates Subject to Rounding:

    Contract Rent, Rent Asked

    Earnings in the Past 12 Months (Households)

    Earnings in the Past 12 Months (Individuals)

    Gross Rent*

    Income Deficit in the Past 12 Months (Families)

    Income Deficit in the Past 12 Months Per Family Member

    Income Deficit in the Past 12 Months Per Unrelated Individual

    Income in the Past 12 Months (Household/Family/Nonfamily Household)

    Income in the Past 12 Months (Individuals)

    Mobile Home Costs

    Real Estate Taxes (Per $1,000 Value)

    Rent Asked

    Selected Monthly Owner Costs* by Mortgage Status Total Mortgage Payment Travel Time to Work**

    Type of Income in the Past 12 Months (Households) Value, Price Asked

    [*Note: Gross Rent and Selected Monthly Owner Costs include other aggregates that also are subject to rounding. For example, Gross Rent includes aggregates of payments for "contract rent" and the "costs of utilities and fuels." Selected Monthly Owner Costs includes aggregates of payments for "mortgages, deeds of trust, contracts to purchase, or similar debts on the property (including payments for the first mortgage, second mortgage, home equity loans, and other junior mortgages); real estate taxes; fire, hazard, and flood insurance on the property, and the costs of utilities and fuels."]

    [**Note: Aggregate Travel Time to Work is zero if the aggregate is zero, is rounded to 4 minutes if the aggregate is 1 to 7 minutes, and is rounded to the nearest multiple of 5 minutes for all other values (if the aggregate is not already evenly divisible by 5).]

    Median
    This measure represents the middle value (if n is odd) or the average of the two middle values (if n is even) in an ordered list of n data values. The median divides the total frequency distribution into two equal parts: one-half of the cases falling below the median and one-half above the median. Each median is calculated using a standard distribution (see below). (For more information, see "Interpolation.")

    For data products displayed in American FactFinder, medians that fall in the upper-most category of an open-ended distribution will be shown with a plus symbol (+) appended (e.g., "$2,000+" for contract rent), and medians that fall in the lowest category of an open-ended distribution will be shown with a minus symbol (-) appended (e.g., "$100- for contract rent"). For other data products and data files that are downloaded by users (i.e., FTP files), plus and minus signs will not be appended. Contract Rent, for example will be shown as $2001 if the median falls in the upper-most category ($2,000 or more) and $99 if the median falls in the lowest category (Less than $100). (The "Standard Distributions" section in Appendix A shows the open-ended intervals for medians.)

    Standard Distributions
    In order to provide consistency in the values within and among data products, standard distributions from which medians and quartiles are calculated are used for the American Community Survey. The American Community Survey Mean Standard Distributions are listed in Appendix A.

    Percentage
    This measure is calculated by taking the number of questions in a group possessing a characteristic of interest and dividing by the total number of questions in that group, and then multiplying by 100.

    Quartile
    This measure divides a distribution into four equal parts. The first quartile (or lower quartile) is the value that defines the upper limit of the lowest one-quarter of the cases. The second quartile is the median. The third quartile (or upper quartile) is defined as the upper limit of the lowest three quarters of cases in the distribution. Quartiles are presented for certain financial characteristics such as housing value and contract rent. The distribution used to compute quartiles is the same as that used to compute medians for that variable.

    Quintile
    This measure divides a distribution into five equal parts. The first quintile (or lowest quintile) is the value that defines the upper limit of the lowest one-fifth of the cases. The second quintile is the 40th percentile. The third quintile is the 60th percentile. The fourth quintile is defined as the upper limit of the lowest four fifths of cases in the distribution, or the 80th percentile. Quintiles are presented for household incomes.

    This is a measure of occurrences in a given period of time divided by the possible number of occurrences during that period. For example, the homeowner vacancy rate is calculated by dividing the number of vacant units "for sale only" by the sum of owner-occupied units and vacant units that are "for sale only," and then multiplying by 100. Rates are sometimes presented as percentages.

    This is a measure of the relative size of one number to a second number expressed as the quotient of the first number divided by the second. For example, the sex ratio is calculated by dividing the total number of males by the total number of females, and then multiplying by 100.

    Quality Measures
    General Information
    Measures describing the quality of the American Community Survey sample and the data collected by the ACS - including sample sizes, coverage rates, and response rates - are available for 2000 through 2006 on the ACS web page, at http://census.gov/acs. The quality measures illustrate the steps the Census Bureau takes to ensure that ACS survey data are accurate and reliable.
    Beginning in 2007, the quality measures are available through American FactFinder in the B98* series of Detailed Tables.

    Sample Size
    Initially Selected Housing Unit Addresses
    The number of addresses in each state and for the nation that were selected for the ACS sample for a particular year. Each year's sample is systematically divided into 12 monthly samples for ACS interviewing. This initial number includes addresses later determined to be commercial or nonexistent, as well as housing units that are not interviewed due to subsampling for personal visit follow-up, refusals or other reasons.

    Housing Unit Final Interviews
    The final number of interviews across all three modes of data collection for the ACS in a given year. This number includes occupied and vacant housing units that were interviewed by mail, telephone, or personal visit methods between January 1 - December 31. It excludes addresses determined to be nonexistent or commercial, and addresses not selected in the subsample for personal visit follow-up, and addresses that are not interviewed due to refusals or other reasons.

    Group Quarters Person Initial Sample Selected
    The number of people living in GQs that could be contacted for ACS interviewing in a given year for a given geographic area. Each year's sample is systematically divided into 12 monthly samples for ACS interviewing. This initial number includes people thought to be in group quarters that were later determined to be out of scope or nonexistent, as well as people not interviewed due to the group quarter refusing entry, the person refusing to respond, or other reasons.

    Group Quarters Person Final Interviews
    The final number of person interviews for the ACS for those living in group quarters in a given year for a given geographic area.

    Coverage Rates
    There are two kinds of coverage error: under-coverage and over-coverage. Under-coverage exists when housing units or people do not have a chance of being selected in the sample. Over-coverage exists when housing units or people have more than one chance of selection in the sample, or are included in the sample when they should not have been. If the characteristics of under-covered or over-covered housing units or individuals differ from those that are selected, the ACS may not provide an accurate picture of the population.

    The coverage rates measure coverage error in the ACS. The coverage rate is the ratio of the ACS population or housing estimate of an area or group to the independent estimate for that area or group, times 100.

    Coverage rates for the total resident population are calculated by sex at the national, state, and Puerto Rico levels, and at the national level only for total Hispanics, and non-Hispanics crossed by the five major race categories: White, Black, American Indian and Alaska Native, Asian, and Native Hawaiian and Other Pacific Islander. The total resident population includes persons in both housing units and group quarters. In addition, a coverage rate that includes only the group quarters population is calculated at the national level. Coverage rates for housing units are calculated at the national and state level, except for Puerto Rico because independent housing unit estimates are not available. These rates are weighted to reflect the probability of selection into the sample, the subsampling for personal visit follow-up, and non-response adjustment.

    Response Rates
    The survey response rate is the ratio of the estimate of units interviewed after data collection is complete to the estimate of all units that should have been interviewed. Separate rates are calculated for housing unit response and GQ person response. For housing units, this means all interviews after mail, telephone and personal visit follow-up. For GQ persons, this means all interviews after the personal visit. Interviews include complete and partial interviews with enough information to be processed.

    All final noninterviews have been grouped into one of the following Reasons for Noninterviews:

    Refusal: Even though the ACS is a mandatory survey and households whose addresses are selected and GQ persons who are selected for the survey are required to answer the survey questions, a few are reluctant to cooperate and refuse to participate.

    Unable to Locate: If the interviewer cannot find the sample address after using all possible sources, they consider it "unable to locate." For GQ persons, the individual could not be located.

    No One Home: Interviewers assign this code if they could not find anyone at the housing unit during the entire month's interview period. There is no equivalent rate for GQ persons.

    Temporarily Absent: The interviewers confirm that all household members or the GQ person are away during the entire month's interview period on vacation, a business trip, or caring for sick relatives.

    Language Problem: The interviewer could not conduct an interview because of language barriers, was not able to get an interpreter who could translate, and the supervisor or regional office could not help complete this case.

    Insufficient Data: To be considered an interviewed unit in ACS, a household or GQ person's response needs to have a minimum amount of data. Occupied housing units and GQ persons not meeting this minimum are treated as noninterviews in the estimation process. Responses for vacant housing units are not subject to a minimum data requirement.

    Other: Unique situations when the reason for noninterview does not fit into one of the classifications described above. Possible reasons include "death in the family," "household quarantined," or "roads impassable."

    Whole GQ Refusal: Some group quarters refuse to allow the ACS to interview any of their residents, citing legal or other reasons.

    Whole GQ Other: These account for other situations where no one in the GQ was interviewed due to reasons other than refusals.

    Imputation Rates
    Missing data for a particular question or item is called item nonresponse. It occurs when a respondent fails to provide an answer to a required item. The ACS also considers invalid answers as item nonresponse. The Census Bureau uses imputation methods that either use rules to determine acceptable answers or use answers from similar housing units or people who provided the item information. One type of imputation, allocation, involves using statistical procedures, such as within-household or nearest neighbor matrices populated by donors, to impute for missing values.

    Overall Person Characteristic Imputation Rate - This rate is calculated by adding together the weighted number of allocated items across a set of person characteristics, and dividing by the total weighted number of responses across the same set of characteristics.

    Overall Housing Characteristic Imputation Rate - This rate is calculated by adding together the weighted number of allocated items across a set of household and housing unit characteristics, and dividing by the total weighted number of responses across the same set of characteristics.

    These rates give an overall picture of the rate of item nonresponse for a geographic area.


    Group Quarters Definitions
    A group quarters is a place where people live or stay, in a group living arrangement, that is owned or managed by an entity or organization providing housing and/or services for the residents. This is not a typical household-type living arrangement. These services may include custodial or medical care as well as other types of assistance, and residency is commonly restricted to those receiving these services. People living in group quarters are usually not related to each other.
    Group quarters include such places as college residence halls, residential treatment centers, skilled nursing facilities, group homes, military barracks, correctional facilities, and workers' dormitories.
    1. Correctional Facilities for Adults
    Correctional Residential Facilities
    These are community-based facilities operated for correctional purposes. The facility residents may be allowed extensive contact with the community, such as for employment or attending school, but are obligated to occupy the premises at night.

    Examples are halfway houses, restitution centers, and prerelease, work release, and study centers.
    Federal Detention Centers
    Stand alone, generally multi-level, federally operated correctional facilities that provide "short-term" confinement or custody of adults pending adjudication or sentencing. These facilities may hold pretrial detainees, holdovers, sentenced offenders, and Immigration and Customs Enforcement (ICE) inmates, formerly called Immigration and Naturalization Service (INS) inmates. These facilities include: Metropolitan Correctional Centers (MCCs), Metropolitan Detention Centers (MDCs), Federal Detention Centers (FDCs), Bureau of Indian Affairs Detention Centers, ICE Service Processing Centers, and ICE contract detention facilities.

    Federal and State Prisons
    Adult correctional facilities where people convicted of crimes serve their sentences. Common names include: prison, penitentiary, correctional institution, federal or state correctional facility, and conservation camp. The prisons are classified by two types of control: (1) "federal" (operated by or for the Bureau of Prisons of the Department of Justice) and (2) "state." Residents who are forensic patients or criminally insane are classified on the basis of where they resided at the time of interview. Patients in hospitals (units, wings, or floors) operated by or for federal or state correctional authorities are interviewed in the prison population. Other forensic patients will be interviewed in psychiatric hospital units and floors for long-term non-acute patients. This category may include privately operated correctional facilities.
    Local Jails and Other Municipal Confinement Facilities
    Correctional facilities operated by or for counties, cities, and American Indian and Alaska Native tribal governments. These facilities hold adults detained pending adjudication and/or people committed after adjudication. This category also includes work farms and camps used to hold people awaiting trial or serving time on relatively short sentences. Residents who are forensic patients or criminally insane are classified on the basis of where they resided at the time of interview. Patients in hospitals (units, wings, or floors) operated by or for local correctional authorities are counted in the jail population. Other forensic patients will be interviewed in psychiatric hospital units and floors for long-term non-acute patients. This category may include privately operated correctional facilities.
    Military Disciplinary Barracks and Jails
    Correctional facilities managed by the military to hold those awaiting trial or convicted of crimes.


    2. Juvenile Facilities
    Correctional Facilities Intended for Juveniles
    Includes specialized facilities that provide strict confinement for its residents and detain juveniles awaiting adjudication, commitment or placement, and/or those being held for diagnosis or classification. Also included are correctional facilities where residents are permitted contact with the community, for purposes such as attending school or holding a job.
    Examples are residential training schools and farms, reception and diagnostic centers, group homes operated by or for correctional authorities, detention centers, and boot camps for juvenile delinquents.
    Group Homes for Juveniles (non-correctional)
    Includes community-based group living arrangements for youth in residential settings that are able to accommodate three or more clients of a service provider. The group home provides room and board and services, including behavioral, psychological, or social programs. Generally, clients are not related to the care giver or to each other.
    Examples are maternity homes for unwed mothers, orphanages, and homes for abused and neglected children in need of services. Group homes for juveniles do not include residential treatment centers for juveniles or group homes operated by or for correctional authorities.
    Residential Treatment Centers for Juveniles (non-correctional)
    Includes facilities that primarily serve youth that provide services on-site in a highly structured live- in environment for the treatment of drug/alcohol abuse, mental illness, and emotional/behavioral disorders. These facilities are staffed 24-hours a day. The focus of a residential treatment center is on the treatment program. Residential treatment centers for juveniles do not include facilities operated by or for correctional authorities.

    3. Nursing Facilities/Skilled Nursing Facilities
    Nursing Facilities/Skilled-Nursing Facilities
    Includes facilities licensed to provide medical care with seven day, twenty-four hour coverage for people requiring long-term non-acute care. People in these facilities require nursing care, regardless of age. Either of these types of facilities may be referred to as nursing homes.
    4. Other Health Care Facilities
    Hospitals with Patients Who Have No Usual Home Elsewhere
    Includes hospitals if they have any patients who have no exit or disposition plan, or who are known as "boarder patients" or "boarder babies." All hospitals are eligible for inclusion in this category except psychiatric hospitals, units, wings or floors operated by federal, state or local correctional authorities. Patients in hospitals operated by these correctional authorities will be interviewed in the prison or jail population. Psychiatric units and hospice units in hospitals are also excluded. Only patients with no usual home elsewhere are interviewed in this category.
    In-Patient Hospice Facilities
    Includes in-patient hospice facilities (both free-standing and units in hospitals) that provide palliative, comfort, and supportive care for the terminally ill patient and their families. All patients in these GQs are included in the ACS GQ sample.
    Mental (Psychiatric) Hospitals and Psychiatric Units in Other Hospitals
    Includes psychiatric hospitals, units and floors for long-term non-acute care patients. The primary function of the hospital, unit, or floor is to provide diagnostic and treatment services for long-term non-acute patients who have psychiatric-related illness.
    Military Treatment Facilities with Assigned Patients
    These facilities include military hospitals and medical centers with active duty patients assigned to the facility. Only these patients are interviewed in this category.
    Residential Schools for People with Disabilities
    Includes schools that provide the teaching of skills for daily living, education programs, and care for students with disabilities in a live-in environment.
    Examples are residential schools for the physically or developmentally disabled.
    5. College/University Student Housing
    College/University Student Housing
    Includes residence halls and dormitories, which house college and university students in a group living arrangement. These facilities are owned, leased, or managed either by a college, university, or seminary, or by a private entity or organization. Fraternity and sorority housing recognized by the college or university are included as college student housing.
    Students attending the U.S. Naval Academy, the U.S. Military Academy (West Point), the U.S. Coast Guard Academy, and the U.S. Air Force Academy are interviewed in military group quarters.

    6. Military Group Quarters
    Military Quarters
    These facilities include military personnel living in barracks (including "open" barrack transient quarters) and dormitories and military ships. Patients assigned to Military Treatment Facilities and people being held in military disciplinary barracks and jails are not interviewed in this category. Patients in Military Treatment Facilities with no usual home elsewhere are not interviewed in this category.
    7. Other Noninstitutional Facilities
    Emergency and Transitional Shelters (with Sleeping Facilities) for People Experiencing Homelessness
    Facilities where people experiencing homelessness stay overnight. These include:
    1. shelters that operate on a first-come, first-serve basis where people must leave in the morning and have no guaranteed bed for the next night;
    2. shelters where people know that they have a bed for a specified period of time (even if they leave the building every day); and
    3. shelters that provide temporary shelter during extremely cold weather (such as churches). This category does not include shelters that operate only in the event of a natural disaster.


    Examples are emergency and transitional shelters; missions; hotels and motels used to shelter people experiencing homelessness; shelters for children who are runaways, neglected or experiencing homelessness; and similar places known to have people experiencing homelessness.

    Group Homes Intended for Adults
    Group homes are community-based group living arrangements in residential settings that are able to accommodate three or more clients of a service provider. The group home provides room and board and services, including behavioral, psychological, or social programs. Generally, clients are not related to the care giver or to each other. Group homes do not include residential treatment centers or facilities operated by or for correctional authorities.
    Residential Treatment Centers for Adults
    Residential facilities that provide treatment on-site in a highly structured live-in environment for the treatment of drug/alcohol abuse, mental illness, and emotional/behavioral disorders. They are staffed 24-hours a day. The focus of a residential treatment center is on the treatment program. Residential treatment centers do not include facilities operated by or for correctional authorities.
    Religious Group Quarters
    These are living quarters owned or operated by religious organizations that are intended to house their members in a group living situation. This category includes such places as convents, monasteries, and abbeys.
    Living quarters for students living or staying in seminaries are classified as college student housing not religious group quarters.
    Workers' Group Living Quarters and Job Corps Centers
    Includes facilities such as dormitories, bunkhouses, and similar types of group living arrangements for agricultural and non-agricultural workers. This category also includes facilities that provide a full-time, year-round residential program offering a vocational training and employment program that helps young people 16-to-24 years old learn a trade, earn a high school diploma or GED and get help finding a job.
    Examples are group living quarters at migratory farm worker camps, construction workers' camps, Job Corps centers, and vocational training facilities, and energy enclaves in Alaska.


    Instructions for Applying Statistical Testing to the 2010-2012 ACS 3-Year Data and the 2008-2012 ACS 5-Year Data
    This document provides some basic instructions for obtaining the ACS standard errors needed to do statistical tests, as well as performing the statistical testing.

    In general, ACS estimates are period estimates that describe the average characteristics of the population and housing over a period of data collection. For example, the 2012 ACS 1-year estimates are averages over the period from January 1, 2012 to December 31, 2012 because this is the period of time for which sample data were collected. Similarly, multiyear estimates are averages of the characteristics over several years. For example, the 2010-2012 ACS 3-year estimates are averages over the period from January 1, 2010 to December 31, 2012, and the 2008-2012 ACS 5-year estimates are averages over the period from January 1, 2008 to December 31, 2012. Multiyear estimates cannot be used to say what was going on in any particular year in the period, only what the average value is over the full time period.

    For more information regarding multiyear ACS data products see any ACS Multiyear Accuracy document available under Data and Documentation on the ACS website http://www.census.gov/acs/www/.
    Obtaining Standard Errors
    The location and type of ACS data, as well as when it was released, will determine if standard errors are readily available or users have to calculate them. If the estimate of interest is published on American FactFinder (AFF), then AFF should also be the source of the standard errors. Possible sources for data and where to get standard errors are:
    1. ACS data from published tables on American FactFinder
    All ACS estimates from tables on AFF include either the 90 percent margin of error or 90 percent confidence bounds. The margin of error is the maximum difference between the estimate and the upper and lower confidence bounds. Most tables on AFF containing single-year or multiyear ACS data display the margin of error.
    Use the margin of error to calculate the standard error (dropping the "+/-" from the displayed value first) as:
    Standard Error = Margin of Error / Z
    where Z = 1.645 for 2006 ACS data and recent years and Z = 1.65 for 2005 and earlier years.
    If confidence bounds are provided instead (as with most ACS data products for 2004 and earlier), calculate the margin of error first before calculating the standard error:
    Margin of Error = max (upper bound - estimate, estimate - lower bound)
    All published ACS estimates use 1.645 (for 2006 and recent years) or 1.65 (for 2005 and
    previous years) to calculate 90 percent margins of error and confidence bounds. Other
    surveys may use other values.
    2. ACS public-use microdata sample (PUMS) tabulations
    Using the methods described in the Accuracy of the PUMS documentation users can calculate standard errors for their tabulations using a design factor method or a replicate weight method. For example, 2010-2012 Accuracy of the PUMS documentation should be used with the 2010-2012 ACS PUMS file to calculate standard errors. This document is available under Data and Documentation on the ACS website http://www.census.gov/acs/www/ .

    NOTE: ACS PUMS design factors provided in the Accuracy of the PUMS document should not be used to calculate standard errors of full ACS sample estimates, such as those found in data tables on AFF. In addition, Census 2000 design factors should not be used to calculate standard errors for any ACS estimate.
    Obtaining Standard Errors for Derived Estimates
    Once users have obtained standard errors for the basic estimates, there may be situations where users create derived estimates, such as percentages or differences that also require standard errors.

    All methods in this section are approximations and users should be cautious in using them. This is because these methods do not consider the correlation or covariance between the basic estimates. They may be overestimates or underestimates of the derived estimate's standard error depending on whether the two basic estimates are highly correlated in either the positive or negative direction. As a result, the approximated standard error may not match direct calculations of standard errors or calculations obtained through other methods.
    • Sum or Difference of Estimates

    As the number of basic estimates involved in the sum or difference increases, the results of this formula become increasingly different from the standard error derived directly from the ACS microdata. Care should be taken to work with the fewest number of basic estimates as possible. If there are estimates involved in the sum that are controlled in the weighting then the approximate standard error can be tremendously different.
    • Proportions and Percents

    Here we define a proportion as a ratio where the numerator is a subset of the denominator, for example the proportion of persons 25 and over with a high school diploma or higher.
    Let

    If the value under the square root sign is negative, then instead use

    If P = 1 then use

    If Q = 100% x P (a percent instead of a proportion), then SE(Q) = 100% x SE(P).
    • Means and Other Ratios

    If the estimate is a ratio but the numerator is not a subset of the denominator, such as persons per household, per capita income, or percent change, then


    • Products

    For a product of two estimates - for example if users want to estimate a proportion's numerator by multiplying the proportion by its denominator - the standard error can be approximated as


    Users may combine these procedures for complicated estimates. For example, if the desired estimate is then SE(A+B+C) and SE(D+E) can be estimated first, and then those results used to calculate SE(P).
    • Comparing Estimates for Overlapping Periods of Identical Length
    Calculating the standard error when comparing two individual estimates for different but overlapping time periods is a special case of the Sum or Difference of Estimates standard error approximation mentioned above. For example, A may represent an estimate of a characteristic for the period 2009-2011 and B the estimate of the same characteristic for 2010-2012. Data for 2010 and 2011 are includedin both estimates, and their contribution is largely subtracted out when differences are calculated.

    In this case, it is possible to approximate the sampling correlation between the two estimates to improve upon the previous expression for the standard error of a difference, namely:


    where C is the fraction of overlapping years. For example, the periods 2009-2011 and 2010-2012 overlap by two out of three years, so C = 2 / 3 = 0.667.

    • Comparing Estimates for Non-Overlapping Periods
    The comparison of two individual estimates for different non-overlapping time periods uses the same formula as the Sum or Difference of Estimates standard error approximation mentioned above. For example, A may represent an estimate of a characteristic for the period 2007-2009 and B the estimate of the same characteristic for 2010-2012. In this case, no approximation of the sampling correlation is needed since there is no data used for both estimates. Therefore, the standard error of a difference is simply:



    For examples of these formulas, please see any Accuracy of the Data document available under Data and Documentation on the ACS website http://www.census.gov/acs/www/.

    Instructions for Statistical Testing
    Once standard errors have been obtained, doing the statistical test to determine significance is not difficult. The determination of statistical significance takes into account the difference between the two estimates as well as the standard errors of both estimates. For two estimates, A and B, with standard errors SE(A) and SE(B), let

    If Z 1.645, then the difference between A and B is significant at the 90 percent confidence level. Otherwise, the difference is not significant. This means that there is less than a 10 percent chance that the difference between these two estimates would be as large or larger by random chance alone.

    Users may choose to apply a confidence level different from 90 percent to their tests of statistical significance. For example, if Z 1.96, then the difference between A and B is significant at the 95 percent confidence level.
    This method can be used for any types of estimates: counts, percentages, proportions, means, medians, etc. It can be used for comparing across years, or across surveys. If one of the estimates is a fixed value or comes from a source without sampling error (such as a count from the 2010 Census), use zero for the standard error for that estimate in the above equation for Z.
    NOTE: Making comparisons between ACS single-year and multiyear estimates is very difficult, and is not advised.
    In addition, using the rule of thumb of overlapping confidence intervals does not constitute a valid significance test and users are discouraged from using that method.


    American Community Survey/Puerto Rico Community Survey
    American Community Survey Multiyear Accuracy of the Data (3-year 2010-2012 and 5-year 2008-2012)
    Introduction
    This multiyear ACS Accuracy of the Data document pertains to both the 2010-2012 3-year ACS data products and the 2008-2012 5-year ACS data products. Differences will be noted where applicable.
    The data contained in these data products are based on the American Community Survey (ACS) sample. For the 3-year data products interviews from January 1, 2010 through December 31, 2012 were used. For the 5-year data products, interviews from January 1, 2008 through December 31, 2012 were used. Data products were produced for 1-year estimates (2008, 2009, 2010, 2011 and 2012), in addition to this set of 3-year and 5-year estimates.
    In general, ACS estimates are period estimates that describe the average characteristics of population and housing over a period of data collection. The 2010-2012 3-year ACS estimates are averages over the period from January 1, 2010 to December 31, 2012, and the 2008-2012 5-year ACS estimates from January 1, 2008 through December 31, 2012, respectively. Multiyear estimates cannot be used to say what is going on in any particular year in the period, only what the average value is over the full period.
    The ACS sample is selected from all counties and county-equivalents in the United States. In 2006, the ACS began collection of data from sampled persons in group quarters (GQ) - for example, military barracks, college dormitories, nursing homes, and correctional facilities. Persons in group quarters are included with persons in housing units (HUs) in all 2010-2012 3-year and 2008-2012 5-year ACS estimates based on the total population.
    The ACS, like any statistical activity, is subject to error. The purpose of this documentation is to provide data users with a basic understanding of the ACS sample design, estimation methodology, and accuracy of the 2010-2012 3-year and 2008-2012 5-year ACS estimates. The ACS is sponsored by the U.S. Census Bureau, and is part of the 2010 Decennial Census Program.
    Additional information on the design and methodology of the ACS, including data collection and processing, can be found at: http://www.census.gov/acs/www/methodology/methodology_main/.

    The Multiyear Accuracy of the Data from the Puerto Rico Community Survey can be found at http://www.census.gov/acs/www/Downloads/data_documentation/Accuracy/MultiyearPRCSAccuracyofData2012.pdf.

    Data Collection
    Housing Units
    The ACS employs three modes of data collection:
    • Mailout/Mailback
    • Computer Assisted Telephone Interview (CATI)
    • Computer Assisted Personal Interview (CAPI)
    With the exception of addresses in Remote Alaska, the general timing of data collection is:
    Month 1: Addresses in sample that are determined to be mailable are sent a questionnaire via the U.S. Postal Service.
    Month 2: All mail non-responding addresses with an available phone number are sent to CATI.
    Month 3: A sample of mail non-responses without a phone number, CATI non-responses, and unmailable addresses are selected and sent to CAPI.
    Sample Design
    Sampling rates are assigned independently at the census block level. A measure of size is calculated for each of the following governmental units:
    - Counties
    - Places
    - School Districts (elementary, secondary, and unified)
    - American Indian Areas
    - Tribal Subdivisions
    - Alaska Native Village Statistical Areas
    - Hawaiian Homelands
    - Minor Civil Divisions - in Connecticut, Maine, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin (these are the states where MCDs are active, functioning governmental units)

    - Census Designated Places - in Hawaii only

    The measure of size for all areas except American Indian Areas, Tribal Subdivisions, and Alaska Native Village Statistical Areas is an estimate of the number of occupied HUs in the area. This is calculated by multiplying the number of ACS addresses by an estimated occupancy rate at the block level. A measure of size for each Census Tract is also calculated in the same manner.

    For American Indian Areas, the measure of size is the estimated number of occupied HUs multiplied by the proportion of people reporting American Indian alone or in combination in the Census. Prior to 2011, this was calculated using Census 2000 occupancy and response data. Beginning in 2011, the ACS uses occupancy and response data from the 2010 Census.

    Each block is then assigned the smallest measure of size from the set of all entities of which it is a part. The 2008-2010 second-stage sampling strata and the overall first-phase sampling rates are shown in Table 1 below. Sampling rates for 2011 and 2012 are shown in a separate table, Table 2. Beginning in 2011 the ACS implemented a sample reallocation as well as a sample increase. The sample reallocation increased the number of second-stage sampling strata from seven to 16. The sample increase changed the target annual sample size from 2.9 million to 3.54 million.

    There are two sets of rates for 2011 shown in Table 2, since the sample increase from 2.9 to 3.54 million occurred midway through the 2011 sample year. The 3.54 million target sampling rates are the rates that would have been used if the entire 2011 sample was at the 3.54 million level. The second set of sample rates for 2011 represent the actual percent in sample that was realized for the 2011 sample year. The 2012 sample was 3.54 million.

    Table 1. 2008 Through 2010 Sampling Rates for the United States

    Stratum Thresholds 2008 Sampling Rates 2009 Sampling Rates 2010 Sampling Rates
    0 < MOS1 ≤ 200 10.0% 10.0% 10.0%
    200 < MOS ≤ 800 6.6% 6.5% 6.7%
    800 < MOS ≤1,200 3.3% 3.3% 3.3%
    2,000 ≤TRACTMOS2 1.5% 1.5% 1.5%
    2,000< TRACTMOS H.R3 1.6% 1.6% 1.6%
    All other areas H.R. 2.0% 2.0% 2.0%
    All other areas 2.2% 2.2% 2.2%
    1MOS = Measure of size of the smallest governmental entity
    2TRACTMOS = Census Tract measure of size.
    3H.R. = areas where predicted levels of completed mail and CATI interviews are > 60%


    Table 2. 2011 and 2012 Sampling Rates for the United States
    Stratum Thresholds Target Sampling Rate(3.54 Million) 2011 Percent In Sample 2012 Sampling Rates
    0 < MOS1 ≤ 200 15.00% 14.81% 15.00%
    200 < MOS ≤ 400 10.00% 9.94% 10.00%
    400 < MOS ≤ 800 7.00% 6.97% 7.00%
    800 < MOS ≤ 1,200 4.93% 4.44% 4.40%
    0 < TRACTMOS2 ≤ 400 6.16% 5.55% 5.55%
    0 < TRACTMOS ≤ 400 H.R.3 5.67% 5.00% 5.06%
    400 < TRACTMOS ≤ 1,000 4.93% 4.46% 4.40%
    400 < TRACTMOS ≤ 1,000 H.R. 4.53% 4.10% 4.04%
    1,000 < TRACTMOS ≤ 2,000 2.99% 2.71% 2.67%
    1,000 < TRACTMOS ≤ 2,000 H.R. 2.75% 2.49% 2.46%
    2,000 < TRACTMOS ≤ 4,000 1.76% 1.61% 1.57%
    2,000 < TRACTMOS ≤ 4,000 H.R. 1.62% 1.47% 1.44%
    4,000 < TRACTMOS ≤ 6,000 1.06% 0.96% 0.94%
    4,000 < TRACTMOS ≤ 6,000 H.R. 0.97% 0.89% 0.87%
    6,000 < TRACTMOS 0.62% 0.57% 0.55%
    6,000 < TRACTMOS H.R. 0.57% 0.53% 0.51%
    1MOS = Measure of size of the smallest governmental entity
    2TRACTMOS = Census Tract measure of size.
    3H.R. = areas where predicted levels of completed mail and CATI interviews are > 60%


    Prior to 2011, all addresses determined to be unmailable were subsampled for the CAPI phase of data collection at a rate of 2-in-3. All other sample addresses that did not respond to the mail or CATI modes of data collections were subsampled for CAPI at a rate of 1-in-2, 2-in-5 or 2-in-3. Unmailable addresses, which include Remote Alaska addresses, do not go to the CATI phase of data collection. Beginning in 2011, at the same time as the sample increase, there was a change in how addresses were selected for CAPI. Table 3 shows both the old CAPI sampling rates and the new rates that were implemented in 2011 (midway through the year).

    Table 3. 2006 Through 2012 CAPI Subsampling Rates for the United States

    Address and Tract Characteristics CAPI Subsampling Rate(Prior to 2011) CAPI Subsampling Rate (2011 - )
    Addresses in Remote Alaska1 66.7% 100%
    Addresses in Hawaiian Homelands, Alaska Native Village Statistical areas and a subset of American Indian areas1 NA2 100%
    Unmailable addresses that are not in the previous two categories 66.7% 66.7%
    Mailable addresses in tracts with predicted levels of completed mail and CATI interviews prior to CAPI subsampling between 0% and less than 36% 50.0% 50.0%
    Mailable addresses in tracts with predicted levels of completed mail and CATI interviews prior to CAPI subsampling greater than 35% and less than 51% 40.0% 40.0%
    Mailable addresses in other tracts 33.3% 33.3%
    1The full CAPI follow-up procedure for these two categories is new to the ACS sample design.
    2These areas were subsampled for CAPI using the same methodology as other non-remote Alaska areas.


    For a more detailed description of the ACS sampling methodology, see the 2012 ACS Accuracy of the Data document (http://www.census.gov/acs/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of_Data_2012.pdf). For more information relating to sampling in a specific year, please refer to the individual years Accuracy of the Data document http://www.census.gov/acs/www/data_documentation/documentation_main/.
    Weighting Methodology
    The multiyear estimates should be interpreted as estimates that describe a time period rather than a specific reference year. For example, a 3-year estimate for the poverty rate of a given area describes the total set of people who lived in that area over those three years much the same way as a 1-year estimate for the same characteristic describes the set of people who lived in that area over one year. The only fundamental difference between the estimates is the number of months of collected data which are considered in forming the estimate. For this reason, the estimation procedure used for the multiyear estimates is an extension of the 2012 1-year estimation procedure. In this document only the procedures that are unique to the multiyear estimates are discussed.

    To weight the 3-year estimates, 36 months of collected data are pooled together and for the 5-year estimates, 60 months were pooled. The pooled data are then reweighted using the procedures developed for the 2012 1-year estimates with a few adjustments. These adjustments concern geography, month-specific weighting steps, and population and housing unit controls. In addition to these adjustments, there is one multiyear specific model-assisted weighting step.

    Some of the weighting steps use the month of tabulation in forming the weighting cells within which the weighting adjustments are made. One such example is the non-interview adjustment. In these weighting steps, the month of tabulation is used independently of year. Thus, for the 3-year, sample cases from May 2010, May 2011, and May 2012 are combined into one weighting cell and for the 5-year, sample cases from May 2008, May 2009, May 2010, May 2011, and May 2012 are combined.

    Since the multiyear estimates represent estimates for the period, the controls are not a single years housing or population estimates from the Population Estimates Program, but rather are an average of these estimates over the period. For the housing unit controls, a simple average of the 1-year housing unit estimates over the period is calculated for each county or subcounty area. The version or vintage of estimates used is always the last year of the period since these are considered to be the most up-to-date and are created using a consistent methodology. For example, the housing unit control used for a given county in the 2008-2012 weighting is equal to the simple average of the 2008, 2009, 2010, 2011, and 2012 estimates that were produced using the 2012 methodology (the 2012 vintage). Likewise, the population controls by race, ethnicity, age, and sex are obtained by taking a simple average of the 1-year population estimates of the county or weighting area by race, ethnicity, age, and sex. For example, the 2008-2012 control total used for Hispanic males age 20-24 in a given county would be obtained by averaging the 1-year population estimates for that demographic group for 2008, 2009, 2010, 2011, and 2012. The version or vintage of estimates used is always that of the last year of the period since these are considered to be the most up to date and are created using a consistent methodology.

    One multiyear specific step is a model-assisted (generalized regression or GREG) weighting step. The objective of this additional step is to reduce the variances of base demographics at the place and MCD level in the 3-year estimates and at the tract level in the 5-year estimates. While reducing the variances, the estimates themselves are relatively unchanged. This process involves linking administrative record data with ACS data.

    The GQ weighting methodology imputes GQ person records into the 2010-2012 3-year ACS, and into the 2008-2012 5-year ACS. See the American Community Survey Accuracy of the Data (2012) for details on the GQ imputation.

    In addition, a finite population correction (FPC) factor is included in the creation of the replicate weights for both the 3-year and 5-year data at the tract level. It reduces the estimate of the variance and the margin of error by taking the sampling rate into account. A two-tiered approach was used. One FPC was calculated for mail and CATI respondents and another for CAPI respondents. The CAPI was given a separate FPC to take into account the fact that CAPI respondents are subsampled. The FPC is not included in the 1-year data because the sampling rates are relatively small and thus the FPC does not have an appreciable impact on the variance.

    For more information on the replicate weights and replicate factors, see the Design and Methodology Report located at http://www.census.gov/acs/www/data_documentation/documentation_main/.
    Estimation Methodology For Multiyear Estimates
    For the 1-year estimation, the tabulation geography for the data is based on the boundaries defined on January 1 of the tabulation year, which is consistent with the tabulation geography used to produce the population estimates. All sample addresses are updated with this geography prior to weighting. For the multiyear estimation, the tabulation geography for the data is referenced to the final year in the multiyear period. For example, the 2010-2012 period uses the 2012 reference geography. Thus, all data collected over the period of 2010-2012 in the blocks that are contained in the 2012 boundaries for a given place are tabulated as though they were a part of that place for the entire period.
    Monetary values for the ACS 3-year estimates are inflation-adjusted to the final year of the period. For example, the 2010-2012 ACS 3-year estimates are tabulated using 2012-adjusted dollars. These adjustments use the national Consumer Price Index (CPI) since a regional-based CPI is not available for the entire country. The ACS 5-year estimates are also inflation-adjusted in the same manner.
    For a more detailed description of the ACS estimation methodology, see the 2012 Accuracy of the Data document (http://www.census.gov/acs/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of_Data_2012.pdf). For more information relating to sampling in a specific year, please refer to the individual years Accuracy of the Data document http://www.census.gov/acs/www/data_documentation/documentation_main/.
    Confidentiality of the Data
    The Census Bureau has modified or filtered some data on this site to protect confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified.

    The Census Bureau's internal Disclosure Review Board sets the confidentiality rules for all data releases. A checklist approach is used to ensure that all potential risks to the confidentiality of the data are considered and addressed.

    • Title 13, United States Code: Title 13 of the United States Code authorizes the Census Bureau to conduct censuses and surveys. Section 9 of the same Title requires that any information collected from the public under the authority of Title 13 be maintained as confidential. Section 214 of Title 13 and Sections 3559 and 3571 of Title 18 of the United States Code provide for the imposition of penalties of up to five years in prison and up to $250,000 in fines for wrongful disclosure of confidential census information.
    • Disclosure Avoidance: Disclosure avoidance is the process for protecting the confidentiality of data. A disclosure of data occurs when someone can use published statistical information to identify an individual that has provided information under a pledge of confidentiality. For data tabulations, the Census Bureau uses disclosure avoidance procedures to modify or remove the characteristics that put confidential information at risk for disclosure. Although it may appear that a table shows information about a specific individual, the Census Bureau has taken steps to disguise or suppress the original data while making sure the results are still useful. The techniques used by the Census Bureau to protect confidentiality in tabulations vary, depending on the type of data. All disclosure avoidance procedures are done prior to the whole person imputation into not-in-sample GQ facilities.
    • Data Swapping: Data swapping is a method of disclosure avoidance designed to protect confidentiality in tables of frequency data (the number or percent of the population with certain characteristics). Data swapping is done by editing the source data or exchanging records for a sample of cases when creating a table. A sample of households is selected and matched on a set of selected key variables with households in neighboring geographic areas that have similar characteristics (such as the same number of adults and same number of children). Because the swap often occurs within a neighboring area, there is no effect on the marginal totals for the area or for totals that include data from multiple areas. Because of data swapping, users should not assume that tables with cells having a value of one or two reveal information about specific individuals. Data swapping procedures were first used in the 1990 Census, and were used again in Census 2000 and the 2010 Census.
    The data use the same disclosure limitation methodology as the original 1-year data. The confidentiality edit was previously applied to the raw data files when they were created to produce the 1-year estimates and these same data files with the original confidentiality edit were used to produce the 3-year and 5-year estimates.
    Errors In The Data
    • Sampling Error - The data in the ACS products are estimates of the actual figures that would have been obtained by interviewing the entire population using the same methodology. The estimates from the chosen sample also differ from other samples of housing units and persons within those housing units. Sampling error in data arises due to the use of probability sampling, which is necessary to ensure the integrity and representativeness of sample survey results. The implementation of statistical sampling procedures provides the basis for the statistical analysis of sample data. Measures used to estimate the sampling error are provided in the next section.
    • Nonsampling Error - In addition to sampling error, data users should realize that other types of errors may be introduced during any of the various complex operations used to collect and process survey data. For example, operations such as data entry from questionnaires and editing may introduce error into the estimates. Another source is through the use of controls in the weighting. The controls are designed to mitigate the effects of systematic undercoverage of certain groups who are difficult to enumerate as well as to reduce the variance. The controls are based on the population estimates extrapolated from the previous census. Errors can be brought into the data if the extrapolation methods do not properly reflect the population. However, the potential risk from using the controls in the weighting process is offset by far greater benefits to the ACS estimates. These benefits include reducing the effects of a larger coverage problem found in most surveys, including the ACS, and the reduction of standard errors of ACS estimates. These and other sources of error contribute to the nonsampling error component of the total error of survey estimates. Nonsampling errors may affect the data in two ways. Errors that are introduced randomly increase the variability of the data. Systematic errors which are consistent in one direction introduce bias into the results of a sample survey. The Census Bureau protects against the effect of systematic errors on survey estimates by conducting extensive research and evaluation programs on sampling techniques, questionnaire design, and data collection and processing procedures. In addition, an important goal of the ACS is to minimize the amount of nonsampling error introduced through nonresponse for sample housing units. One way of accomplishing this is by following up on mail nonrespondents during the CATI and CAPI phases.

    Measures of Sampling Error
    Sampling error is the difference between an estimate based on a sample and the corresponding value that would be obtained if the estimate were based on the entire population (as from a census). Note that sample-based estimates will vary depending on the particular sample selected from the population. Measures of the magnitude of sampling error reflect the variation in the estimates over all possible samples that could have been selected from the population using the same sampling methodology.
    Estimates of the magnitude of sampling errors - in the form of margins of error - are provided with all published ACS data. The Census Bureau recommends that data users incorporate this information into their analyses, as sampling error in survey estimates could impact the conclusions drawn from the results.
    Confidence Intervals and Margins of Error
    Confidence Intervals - A sample estimate and its estimated standard error may be used to construct confidence intervals about the estimate. These intervals are ranges that will contain the average value of the estimated characteristic that results over all possible samples, with a known probability.

    For example, if all possible samples that could result under the ACS sample design were independently selected and surveyed under the same conditions, and if the estimate and its estimated standard error were calculated for each of these samples, then:
    1. Approximately 68 percent of the intervals from one estimated standard error below the estimate to one estimated standard error above the estimate would contain the average result from all possible samples;
    2. Approximately 90 percent of the intervals from 1.645 times the estimated standard error below the estimate to 1.645 times the estimated standard error above the estimate would contain the average result from all possible samples.
    3. Approximately 95 percent of the intervals from two estimated standard errors below the estimate to two estimated standard errors above the estimate would contain the average result from all possible samples.
    The intervals are referred to as 68 percent, 90 percent, and 95 percent confidence intervals, respectively.
    Margin of Error - Instead of providing the upper and lower confidence bounds in published ACS tables, the margin of error is provided instead. The margin of error is the difference between an estimate and its upper or lower confidence bound. Both the confidence bounds and the standard error can easily be computed from the margin of error. All ACS published margins of error are based on a 90 percent confidence level.
    Standard Error = Margin of Error / 1.645
    Lower Confidence Bound = Estimate - Margin of Error
    Upper Confidence Bound = Estimate + Margin of Error

    When constructing confidence bounds from the margin of error, the user should be aware of any "natural" limits on the bounds. For example, if a characteristic estimate for the population is near zero, the calculated value of the lower confidence bound may be negative. However, a negative number of people does not make sense, so the lower confidence bound should be reported as zero instead. However, for other estimates such as income, negative values do make sense. The context and meaning of the estimate must be kept in mind when creating these bounds. Another of these natural limits would be 100 percent for the upper bound of a percent estimate.

    If the margin of error is displayed as '*****' (five asterisks), the estimate has been controlled to be equal to a fixed value and so it has no sampling error. When using any of the formulas in the following section, use a standard error of zero for these controlled estimates.
    Limitations -The user should be careful when computing and interpreting confidence intervals.
    • The estimated standard errors (and thus margins of error) included in these data products do not include portions of the variability due to nonsampling error that may be present in the data. In particular, the standard errors do not reflect the effect of correlated errors introduced by interviewers, coders, or other field or processing personnel. Nor do they reflect the error from imputed values due to missing responses. Thus, the standard errors calculated represent a lower bound of the total error. As a result, confidence intervals formed using these estimated standard errors may not meet the stated levels of confidence (i.e., 68, 90, or 95 percent). Thus, some care must be exercised in the interpretation of the data in this data product based on the estimated standard errors.
    • Zero or small estimates; very large estimates - The value of almost all ACS characteristics is greater than or equal to zero by definition. For zero or small estimates, use of the method given previously for calculating confidence intervals relies on large sample theory, and may result in negative values which for most characteristics are not admissible. In this case the lower limit of the confidence interval is set to zero by default. A similar caution holds for estimates of totals close to a control total or estimated proportion near one, where the upper limit of the confidence interval is set to its largest admissible value. In these situations the level of confidence of the adjusted range of values is less than the prescribed confidence level.


    Calculation of Standard Errors
    Direct estimates of the margin of error were calculated for all estimates reported in this product. The margin of error is calculated from the variance. The variance, in most cases, is calculated using a replicate-based methodology known as successive difference replication that takes into account the sample design and estimation procedures.
    It is calculated using the ACS estimate and the 80 replicate estimates computed using the replicate weights. The formula for the variance is provided below:


    Where X0 is the estimate calculated using the production weight and Xr is the estimate calculated using the rth replicate weight. The standard error is the square root of the variance. The 90th percent margin of error is 1.645 times the standard error.
    For more information on the formation of the replicate weights, see chapter 12 of the Design and Methodology documentation at http://www.census.gov/acs/www/Downloads/survey_methodology/Chapter_12_RevisedDec2010.pdf.

    Beginning with the ACS 2011 1-year estimates, a new imputation-based methodology was incorporated into processing (see the description in the Group Quarters Person Weighting Section). An adjustment was made to the production replicate weight variance methodology to account for the non-negligible amount of additional variation being introduced by the new technique.5
    Excluding the base weights, replicate weights were allowed to be negative in order to avoid underestimating the standard error. Exceptions include:
    1. The estimate of the number or proportion of people, households, families, or housing units in a geographic area with a specific characteristic is zero. A special procedure is used to estimate the standard error.
    2. There are either no sample observations available to compute an estimate or standard error of a median, an aggregate, a proportion, or some other ratio, or there are too few sample observations to compute a stable estimate of the standard error. The estimate is represented in the tables by "-" and the margin of error by "**" (two asterisks).
    3. The estimate of a median falls in the lower open-ended interval or upper open-ended interval of a distribution. If the median occurs in the lowest interval, then a "-" follows the estimate, and if the median occurs in the upper interval, then a "+" follows the estimate. In both cases the margin of error is represented in the tables by "***" (three asterisks).

    Sums and Differences of Direct Standard Errors
    The standard errors estimated from these tables are for individual estimates. Additional calculations are required to estimate the standard errors for sums of or the differences between two or more sample estimates.
    The standard error of the sum of two sample estimates is the square root of the sum of the two individual standard errors squared plus a covariance term. That is, for standard errors and of estimates and



    The covariance measures the interactions between two estimates. Currently the covariance terms are not available. Data users should use the approximation:



    However, this method will underestimate or overestimate the standard error if the two estimates interact in either a positive or negative way.
    The approximation formula (2) can be expanded to more than two estimates by adding in the individual standard errors squared inside the radical. As the number of estimates involved in the sum or difference increases, the results of formula (2) become increasingly different from the standard error derived directly from the ACS microdata. Care should be taken to work with the fewest number of estimates as possible. If there are estimates involved in the sum that are controlled in the weighting then the approximate standard error can be increasingly different. Several examples are provided starting on page 32 to demonstrate issues associated with approximating the standard errors when summing large numbers of estimates together.

    Ratios
    The statistic of interest may be the ratio of two estimates. First is the case where the numerator is not a subset of the denominator. The standard error of this ratio between two sample estimates is approximated as:



    Proportions/Percents
    For a proportion (or percent), a ratio where the numerator is a subset of the denominator, a slightly different estimator is used. If , then the standard error of this proportion is approximated as:



    If (P is the proportion and Q is its corresponding percent), then. Note the difference between the formulas to approximate the standard error for proportions (4) and ratios (3) - the plus sign in the previous formula has been replaced with a minus sign. If the value under the radical is negative, use the ratio standard error formula above, instead.

    Percent Change
    This calculates the percent change from one time period to another, for example, computing the percent change of a 2012 estimate to a 2011 estimate. Normally, the current estimate is compared to the older estimate.
    Let the current estimate and the earlier estimate then the formula for percent change is:

    This reduces to a ratio. The ratio formula above may be used to calculate the standard error. As a caveat, this formula does not take into account the correlation when calculating overlapping time periods.

    Products
    For a product of two estimates - for example if you want to estimate a proportion's numerator by multiplying the proportion by its denominator - the standard error can be approximated as:



    Differences of Estimates for Overlapping Periods of Identical Length
    For example, may represent an estimate of a characteristic for the period 2009-2011 and the estimate of the same characteristic for 2010-2012. In this case, data for 2010 and 2011 are included in both estimates, and their contribution is largely subtracted out when differences are calculated. In this case, it is possible to approximate the sampling correlation between the two estimates to improve upon the previous expression, namely:


    where C is the fraction of overlapping years. For example, the periods 2009-2011 and 2010-2012 overlap by two out of three years, so C = 2 / 3 and 1 - C = 0.33. If the periods do not overlap, such as 2007-2009 and 2010-2012, then no factor is needed. Due to the difficulty in interpreting overlapping time periods, the Census Bureau currently discourages users from making such comparisons.
    Testing for Significant Differences
    Significant differences - Users may conduct a statistical test to see if the difference between a PRCS estimate and any other chosen estimates is statistically significant at a given confidence level. "Statistically significant" means that the difference is not likely due to random chance alone. With the two estimates (Est1 and Est2) and their respective standard errors (SE1 and SE2), calculate a Z statistic:





    If Z > 1.645 or Z 1 Any estimate can be compared to an ACS estimate using this method, including other ACS estimates from the current year, the ACS estimate for the same characteristic and geographic area but from a previous year, 2010 Census counts, estimates from other Census Bureau surveys, and estimates from other sources. Not all estimates have sampling error - Census 2010 counts and Census 2000 100 percent counts do not, for example, although Census 2000 long form estimates do - but they should be used if they exist to give the most accurate result of the test.
    Users are also cautioned to not rely on looking at whether confidence intervals for two estimates overlap or not to determine statistical significance, because there are circumstances where that method will not give the correct test result. If two confidence intervals do not overlap, then the estimates will be significantly different (i.e. the significance test will always agree). However, if two confidence intervals do overlap, then the estimates may or may not be significantly different. The Z calculation above is recommended in all cases.

    Here is a simple example of why it is not recommended to use the overlapping confidence bounds rule of thumb as a substitute for a statistical test.

    Let: X1 = 6.0 with SE1 = 0.5 and X2 = 5.0 with SE2 = 0.2.

    The Lower Bound for X12 = 5.0 + 0.2 x 1.645 = 5.3. The confidence bounds overlap, so, the rule of thumb would indicate that the estimates are not significantly different at the 90% level.

    However, if we apply the statistical significance test we obtain:



    Z = 1.857 > 1.645 which means that the difference is significant (at the 90% level).

    All statistical testing in ACS data products is based on the 90 percent confidence level. Users should understand that all testing was done using unrounded estimates and standard errors, and it may not be possible to replicate test results using the rounded estimates and margins of error as published.

    1The ACS Accuracy of the Data document in 2005 used a Z statistic of +/-1.65. Data users should use +/-1.65 for estimates published in 2005 or earlier.



    Examples of Standard Error Calculations
    We will present some examples based on the real data to demonstrate the use of the formulas. All of the data used here are from 2010-2012 3-year data, but the process would be the same is 2008-2012 5-year data were used instead.
    Example 1 - Calculating the Standard Error from the Margin of Error
    The estimated number of males, never married is 43,507,043 from summary table B12001 for the period 2010-2012 in the United States. The margin of error is 65,200.
    Standard Error = Margin of Error / 1.645
    Calculating the standard error using the margin of error, we have:
    SE(43,507,043) = 65,200 / 1.645 = 39,635.
    Example 2 - Calculating the Standard Error of a Sum or a Difference
    We are interested in the number of people who have never married for the period 2010-2012 in the United States. From example 1, we know the number of males, never married is 43,507,043. From summary table B12001 we have the number of females, never married is 37,609,082 with a margin of error of 56,905. So, the estimated number of people who have never been married is 43,507,043 + 37,609,082 = 81,116,125. To calculate the standard error of this sum, we need the standard errors of the two estimates in the sum. We have the standard error for the number of males never married from example 1 as 39,635. The standard error for the number of females never married is calculated using the margin of error:
    SE(37,609,082) = 56,905 / 1.645 = 34,593.br />
    So using formula (2) for the approximate standard error of a sum or difference we have:


    Caution: This method will underestimate or overestimate the standard error if the two estimates interact in either a positive or negative way.
    To calculate the lower and upper bounds of the 90 percent confidence interval around 81,116,125 using the standard error, simply multiply 52,608 by 1.645, then add and subtract the product from 81,116,125. Thus the 90 percent confidence interval for this estimate is [81,116,125 - 1.645(52,608)] to [81,116,125 + 1.645(52,608)] or 81,029,585 to 81,202,665.
    Example 3 - Calculating the Standard Error of a Proportion/Percent
    We are interested in the percentage of females who have never married to the number of people who have never married during the period of 2010-2012. The number of females, never married is 37,609,082, and the number of people who have never married is 81,116,125. To calculate the standard error of this percent, we need the standard errors of the two estimates in the percent. We have the standard error for the number of females never married from example 2 as 34,593 and the standard error for the number of people never married calculated from example 2 as 52,608.
    The estimate is (37,609,082 / 81,116,125) * 100% = 46.36%
    So, using formula (4) for the approximate standard error of a proportion or percent, we have:


    To calculate the lower and upper bounds of the 90 percent confidence interval around 46.36 using the standard error, simply multiply 0.03 by 1.645, then add and subtract the product from 46.36. Thus the 90 percent confidence interval for this estimate is
    [46.36 - 1.645(0.03)] to [46.36 + 1.645(0.03)], or 46.31% to 46.41%.
    Example 4 - Calculating the Standard Error of a Ratio
    Now, let us calculate the estimate of the ratio of the number of unmarried males to the number of unmarried females and its standard error. From the above examples, the estimate for the number of unmarried men is 43,507,043 with a standard error of 39,635, and the estimate for the number of unmarried women is 37,609,082 with a standard error of 34,593.
    The estimate of the ratio is 43,507,043 / 37,609,082 = 1.157.
    The standard error of this ratio is


    The 90 percent margin of error for this estimate would be 0.00150 multiplied by 1.645, or about 0.002. The 90 percent lower and upper 90 percent confidence bounds would then be [1.157 - 1.645(0.00150)] to [1.157 + 1.645(0.00150)], or 1.155 and 1.159.
    Example 5 - Calculating the Standard Error of a Product
    We are interested in the number of 1-unit detached owner-occupied housing units in the U.S. The number of owner-occupied housing units is 74,542,299 with a margin of error of 157,739 from subject table S2504 for 2010-2012, and the percent of 1-unit detached owner-occupied housing units is 82.2% (0.822) with a margin of error of 0.1% (0.001). So the number of 1-unit detached owner-occupied housing units is 74,542,299 * 0.822 = 61,273,770. Calculating the standard error for the estimates using the margin of error we have:

    SE(74,542,299) = 157,739 / 1.645 = 95,890

    and

    SE(0.822) = 0.001 / 1.645 = 0.0006079

    The standard error for number of 1-unit detached owner-occupied housing units is calculated using the formula for products as:



    To calculate the lower and upper bounds of the 90 percent confidence interval around 61,273,770 using the standard error, simply multiply 90,919 by 1.645, then add and subtract the product from 61,273,770. Thus, the 90 percent confidence interval for this estimate is [61,273,770 - 1.645(90,919)] to [61,273,770 + 1.645(90,919)] or 61,124,208 to 61,423,332.

    Example 6 - Calculating the Standard Error of the Difference of Overlapping Periods of Identical Length
    It should be noted that due to the difficulty in interpreting the "difference" in overlapping period estimates, the Census Bureau currently discourages users from making such comparisons.
    We are interested in the "difference" of two estimates of the total population for age 3 and over in Midland County, Texas. This can be found in table B14001. The estimated population for 2010-2012 is 134,808 with a margin of error of 467. For 2009-2011, the comparable estimate was 131,335 with a margin of error of 520, giving an estimated "difference" of 3,473.
    To compute the standard error for the estimated "difference", we first compute the standard errors for the 2010-2012 and 2009-2011 estimates by dividing the margins of error by 1.645, obtaining 284 and 316, respectively. The 2009-2011 data overlaps the 2010-2012 data for 2010 and 2011 so we apply the formula for the differences of estimates for overlapping periods of identical length, using C = 2/3 (due to 2 overlapping years),

    We get an estimated standard error for the "difference" of 3,473. To obtain a 90 percent confidence interval for the "difference", we multiply 245 by 1.645 to get 403, then add and subtract this result from the estimated difference of 3,473 to get a 90 percent confidence interval of 3,070 to 3,876. Note that if we had ignored correcting to incorporate the correlation, the confidence interval would have been even wider.
    Control of Nonsampling Error
    As mentioned earlier, sample data are subject to nonsampling error. This component of error could introduce serious bias into the data, and the total error could increase dramatically over that which would result purely from sampling. While it is impossible to completely eliminate nonsampling error from a survey operation, the Census Bureau attempts to control the sources of such error during the collection and processing operations. Described below are the primary sources of nonsampling error and the programs instituted for control of this error. The success of these programs, however, is contingent upon how well the instructions were carried out during the survey.

    • Coverage Error
    - It is possible for some sample housing units or persons to be missed entirely by the survey (undercoverage), but it is also possible for some sample housing units and persons to be counted more than once (overcoverage). Both the undercoverage and overcoverage of persons and housing units can introduce biases into the data, increase respondent burden and survey costs.
    A major way to avoid coverage error in a survey is to ensure that its sampling frame, for ACS an address list in each state, is as complete and accurate as possible. The source of addresses for the ACS is the MAF. An attempt is made to assign all appropriate geographic codes to each MAF address via an automated procedure using the Census Bureau TIGER (Topologically Integrated Geographic Encoding and Referencing) files. A manual coding operation based in the appropriate regional offices is attempted for addresses which could not be automatically coded. The MAF was used as the source of addresses for selecting sample housing units and mailing questionnaires. TIGER produced the location maps for CAPI assignments. Sometimes the MAF has an address that is the duplicate of another address already on the MAF. This could occur when there is a slight difference in the address such as 123 Main Street versus 123 Maine Street.
    In the CATI and CAPI nonresponse follow-up phases, efforts were made to minimize the chances that housing units that were not part of the sample were interviewed in place of units in sample by mistake. If a CATI interviewer called a mail nonresponse case and was not able to reach the exact address, no interview was conducted and the case was eligible for CAPI. During CAPI follow-up, the interviewer had to locate the exact address for each sample housing unit. If the interviewer could not locate the exact sample unit in a multi-unit structure, or found a different number of units than expected, the interviewers were instructed to list the units in the building and follow a specific procedure to select a replacement sample unit. Person overcoverage can occur when an individual is included as a member of a housing unit but does not meet ACS residency rules.
    Coverage rates give a measure of undercoverage or overcoverage of persons or housing units in a given geographic area. Rates below 100 percent indicate undercoverage, while rates above 100 percent indicate overcoverage. Coverage rates are released concurrent with the release of estimates on American FactFinder in the B98 series of detailed tables. Further information about ACS coverage rates may be found at http://www.census.gov/acs/www/methodology/coverage_rates_data/.

    • Nonresponse Error
    - Survey nonresponse is a well-known source of nonsampling error. There are two types of nonresponse error - unit nonresponse and item nonresponse. Nonresponse errors affect survey estimates to varying levels depending on amount of nonresponse and the extent to which nonrespondents differ from respondents on the characteristics measured by the survey. The exact amount of nonresponse error or bias on an estimate is almost never known. Therefore, survey researchers generally rely on proxy measures, such as the nonresponse rate, to indicate the potential for nonresponse error.

    - Unit Nonresponse - Unit nonresponse is the failure to obtain data from housing units in the sample. Unit nonresponse may occur because households are unwilling or unable to participate, or because an interviewer is unable to make contact with a housing unit. Unit nonresponse is problematic when there are systematic or variable differences between interviewed and noninterviewed housing units on the characteristics measured by the survey. Nonresponse bias is introduced into an estimate when differences are systematic, while nonresponse error for an estimate evolves from variable differences between interviewed and noninterviewed households.

    The ACS makes every effort to minimize unit nonresponse, and thus, the potential for nonresponse error. First, the ACS used a combination of mail, CATI, and CAPI data collection modes to maximize response. The mail phase included a series of three to four mailings to encourage housing units to return the questionnaire. Subsequently, mail nonrespondents (for which phone numbers are available) were contacted by CATI for an interview. Finally, a subsample of the mail and telephone nonrespondents was contacted by personal visit to attempt an interview. Combined, these three efforts resulted in a very high overall response rate for the ACS.

    ACS response rates measure the percent of units with a completed interview. The higher the response rate, and consequently the lower the nonresponse rate, the less chance estimates may be affected by nonresponse bias. Response and nonresponse rates, as well as rates for specific types of nonresponse, are released concurrent with the release of estimates on American FactFinder in the B98 series of detailed tables. Further information about response and nonresponse rates may be found at http://www.census.gov/acs/www/methodology/response_rates_data/.

    - Item Nonresponse - Nonresponse to particular questions on the survey questionnaire and instrument allows for the introduction of error or bias into the data, since the characteristics of the nonrespondents have not been observed and may differ from those reported by respondents. As a result, any imputation procedure using respondent data may not completely reflect this difference either at the elemental level (individual person or housing unit) or on average.

    Some protection against the introduction of large errors or biases is afforded by minimizing nonresponse. In the ACS, item nonresponse for the CATI and CAPI operations was minimized by the requirement that the automated instrument receive a response to each question before the next one could be asked. Questionnaires returned by mail were edited for completeness and acceptability. They were reviewed by computer for content omissions and population coverage. If necessary, a telephone follow-up was made to obtain missing information. Potential coverage errors were included in this follow-up.

    Allocation tables provide the weighted estimate of persons or housing units for which a value was imputed, as well as the total estimate of persons or housing units that were eligible to answer the question. The smaller the number of imputed responses, the lower the chance that the item nonresponse is contributing a bias to the estimates. Allocation tables are released concurrent with the release of estimates on American Factfinder in the B99 series of detailed tables with the overall allocation rates across all person and housing unit characteristics in the B98 series of detailed tables. Additional information on item nonresponse and allocations can be found at http://www.census.gov/acs/www/methodology/item_allocation_rates_data/.

    • Measurement and Processing Error
    - The person completing the questionnaire or responding to the questions posed by an interviewer could serve as a source of error, although the questions were cognitively tested for phrasing and detailed instructions for completing the questionnaire were provided to each household.
    - Interviewer monitoring - The interviewer may misinterpret or otherwise incorrectly enter information given by a respondent; may fail to collect some of the information for a person or household; or may collect data for households that were not designated as part of the sample. To control these problems, the work of interviewers was monitored carefully. Field staff were prepared for their tasks by using specially developed training packages that included hands-on experience in using survey materials. A sample of the households interviewed by CAPI interviewers was reinterviewed to control for the possibility that interviewers may have fabricated data.
    - Processing Error - The many phases involved in processing the survey data represent potential sources for the introduction of nonsampling error. The processing of the survey questionnaires includes the keying of data from completed questionnaires, automated clerical review, follow-up by telephone, manual coding of write-in responses, and automated data processing. The various field, coding and computer operations undergo a number of quality control checks to insure their accurate application.

    - Content Editing - After data collection was completed, any remaining incomplete or inconsistent information was imputed during the final content edit of the collected data. Imputations, or computer assignments of acceptable codes in place of unacceptable entries or blanks, were needed most often when an entry for a given item was missing or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in other surveys and previous censuses, the general procedure for changing unacceptable entries was to allocate an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. Imputing acceptable values in place of blanks or unacceptable entries enhances the usefulness of the data.

    Issues With Approximating the Standard Error of Linear Combinations of Multiple Estimates
    Several examples are provided here to demonstrate how different the approximated standard errors of sums can be compared to those derived and published with ACS microdata. These examples use estimates from the 2005-2009 ACS 5-year data products.

    A. With the release of the 5-year data, detailed tables down to tract and block group will be available. At these geographic levels, many estimates may be zero. As mentioned in the ' Calculations of Standard Errors section, a special procedure is used to estimate the MOE when an estimate is zero. For a given geographic level, the MOEs will be identical for zero estimates. When summing estimates which include many zero estimates, the standard error and MOE in general will become unnaturally inflated. Therefore, users are advised to sum only one of the MOEs from all of the zero estimates.

    Suppose we wish to estimate the total number of people whose first reported ancestry was ' Subsaharan African in Rutland County, Vermont.

    Table A: 2005-2009 Ancestry Categories from Table B04001: First Ancestry Reported

    First Ancestry Reported Category Estimate MOE
    Subsaharan African: 48 43
         
    Cape Verdean 9 15
    Ethiopian 0 93
    Ghanaian 0 93
    Kenyan 0 93
    Liberian 0 93
    Nigerian 0 93
    Senegalese 0 93
    Sierra Leonean 0 93
    Somalian 0 93
    South African 10 16
    Sudanese 0 93
    Ugandan 0 93
    Zimbabwean 0 93
    African 20 33
    Other Subsaharan African 9 16
    2009 American FactFinder


    To estimate the total number of people, we add up all of the categories.

    Total Number of People = 9 + 0 + ... + 0 + 10 + 0 ... + 20 + 9 = 48

    To approximate the standard error using all of the MOEs we obtain:



    Using only one of the MOEs from the zero estimates, we obtain:



    From the table, we know that the actual MOE is 43, giving a standard error of 43 / 1.645 = 26.1. The first method is roughly seven times larger than the actual standard error, while the second method is roughly 2.4 times larger.

    Leaving out all of the MOEs from zero estimates we obtain:



    In this case, it is very close to the actual SE. This is not always the case, as can be seen in the examples below.

    B. Suppose we wish to estimate the total number of males with income below the poverty level in the past 12 months using both state and PUMA level estimates for the state of Wyoming. Part of the detailed table B170012 is displayed below with estimates and their margins of error in parentheses.

    2Table C17001 is used in this example for the 2009 1-year Accuracy documents. C17001 is not published for the 2005-2009 5-year data.

    Table B: 2005-2009 ACS estimates of Males with Income Below Poverty from table B17001: Poverty Status in the Past 12 Months by Sex by Age

    Characteristic Wyoming PUMA 00100 PUMA 00200 PUMA 00300 PUMA 00400
    Male 21,769 (1,480) 4,496 (713) 5,891 (622) 4,706 (665) 6,676 (742)
    Under 5 Years 3,064 (422) 550 (236) 882 (222) 746 (196) 886 (237)
    5 Years Old 348 (106) 113 (65) 89 (57) 82 (55) 64 (44)
    6 to 11 Years Old 2,424 (421) 737 (272) 488 (157) 562 (163) 637 (196)
    12 to 14 Years Old 1,281 (282) 419 (157) 406 (141) 229 (106) 227 (111)
    15 Years Old 391 (128) 51 (37) 167 (101) 132 (64) 41 (38)
    16 and 17 Years Old 779 (258) 309 (197) 220 (91) 112 (72) 138 (112)
    18 to 24 Years old 4,504 (581) 488 (192) 843 (224) 521 (343) 2,652 (481)
    25 to 34 Years Old 2,289 (366) 516 (231) 566 (158) 542 (178) 665 (207)
    35 to 44 Years Old 2,003 (311) 441 (122) 535 (160) 492 (148) 535 (169)
    45 to 54 Years Old 1,719 (264) 326 (131) 620 (181) 475 (136) 298 (113)
    55 to 64 Years Old 1,766 (323) 343 (139) 653 (180) 420 (135) 350 (125)
    65 to 74 Years Old 628 (142) 109 (69) 207 (77) 217 (72) 95 (55)
    75 Years and Older 573 (147) 94 (53) 215 (86) 176 (72) 88 (62)
    2009 American FactFinder


    The first way is to sum the thirteen age groups for Wyoming:

    Estimate(Male) = 3,064 + 348 + … + 573 = 21,769.

    The first approximation for the standard error in this case gives us:



    A second way is to sum the four PUMA estimates for Male to obtain:

    Estimate(Male) = 4,496 + 5,891 + 4,706 + 6,676 = 21,769 as before.

    The second approximation for the standard error yields:



    Finally, we can sum up all thirteen age groups for all four PUMAs to obtain an estimate based on a total of 52 estimates:

    Estimate(Male) = 550 + 113 + ... + 88 = 21,769

    And the third approximated standard error is



    However, we do know that the standard error using the published MOE is 1,480 /1.645 = 899.7. In this instance, all of the approximations under-estimate the published standard error and should be used with caution.

    C. Suppose we wish to estimate the total number of males at the national level using age and citizenship status. The relevant data from table B05003 is displayed in table C below.

    Table C: 2005-2009 ACS estimates of males from B05003: Sex by Age by Citizenship Status

    Characteristic Estimate MOE
    Male 148,535,646 6,574
        Under 18 Years 37,971,739 6,285
            Native 36,469,916 10,786
            Foreign Born 1,501,823 11,083
                Naturalized U.S. Citizen 282,744 4,284
                Not a U.S. Citizen 1,219,079 10,388
        18 Years and Older 110,563,907 6,908
            Native 93,306,609 57,285
            Foreign Born 17,257,298 52,916
                Naturalized U.S. Citizen 7,114,681 20,147
                Not a U.S. Citizen 10,142,617 53,041
    2009 American FactFinder


    The estimate and its MOE are actually published. However, if they were not available in the tables, one way of obtaining them would be to add together the number of males under 18 and over 18 to get:

    Estimate(Male) = 37,971,739 + 110,563,907 = 148,535,646

    And the first approximated standard error is



    Another way would be to add up the estimates for the three subcategories (Native, and the two subcategories for Foreign Born: Naturalized U.S. Citizen, and Not a U.S. Citizen), for males under and over 18 years of age. From these six estimates we obtain:

    Estimate(Male) = 36,469,916 + 282,744 + 1,219,079 + 93,306,609 + 7,114,681 + 101,42,617 = 148,535,646

    With a second approximated standard error of:



    We do know that the standard error using the published margin of error is 6,574 / 1.645 = 3,996.4. With a quick glance, we can see that the ratio of the standard error of the first method to the published-based standard error yields 1.42; an over-estimate of roughly 42%, whereas the second method yields a ratio of 12.49 or an over-estimate of 1,149%. This is an example of what could happen to the approximate SE when the sum involves a controlled estimate. In this case, it is sex by age.

    D. Suppose we are interested in the total number of people aged 65 or older and its standard error. Table D shows some of the estimates for the national level from table B01001 (the estimates in gray were derived for the purpose of this example only).

    Table D: Some Estimates from AFF Table B01001: Sex by Age for 2005-2009

    Age Category Estimate, Male MOE, Male Estimate, Female MOE, Female Total Approximated MOE, Total
    65 and 66 years old 2,248,426 8,047 2,532,831 9,662 4,781,257 12,574
    67 to 69 years old 2,834,475 8,953 3,277,067 8,760 6,111,542 12,526
    70 to 74 years old 3,924,928 8,937 4,778,305 10,517 8,703,233 13,801
    75 to 79 years old 3,178,944 9,162 4,293,987 11,355 7,472,931 14,590
    80 to 84 years old 2,226,817 6,799 3,551,245 9,898 5,778,062 12,008
    85 years and older 1,613,740 7058 3,540,105 10,920 5,153,845 13,002
    Total 16,027,330 20,119 21,973,540 25,037 38,000,870 32,119
    2009 American FactFinder


    To begin we find the total number of people aged 65 and over by simply adding the totals for males and females to get 16,027,330 + 21,973,540 = 38,000,870. One way we could use is summing males and female for each age category and then using their MOEs to approximate the standard error for the total number of people over 65.



    ... etc. ...

    Now, we calculate for the number of people aged 65 or older to be 38,000,870 using the six derived estimates and approximate the standard error:



    For this example the estimate and its MOE are published in table B09017. The total number of people aged 65 or older is 38,000,870 with a margin of error of 4,944. Therefore the published-based standard error is:

    SE(38,000,870) = 4,944 / 1.645 = 3,005.

    The approximated standard error, using six derived age group estimates, yields an approximated standard error roughly 10.7 times larger than the published-based standard error.

    As a note, there are two additional ways to approximate the standard error of people aged 65 and over in addition to the way used above. The first is to find the published MOEs for the males age 65 and older and of females aged 65 and older separately and then combine to find the approximate standard error for the total. The second is to use all twelve of the published estimates together, that is, all estimates from the male age categories and female age categories, to create the SE for people aged 65 and older. However, in this particular example, the results from all three ways are the same. So no matter which way you use, you will obtain the same approximation for the SE. This is different from the results seen in example B.

    E. For an alternative to approximating the standard error for people 65 years and older seen in part D, we could find the estimate and its SE by summing all of the estimate for the ages less than 65 years old and subtracting them from the estimate for the total population. Due to the large number of estimates, Table E does not show all of the age groups. In addition, the estimates in part of the table shaded gray were derived for the purposes of this example only and cannot be found in base table B01001.

    Table E: Some Estimates from AFF Table B01001: Sex by Age for 2005-2009:

    Age Category Estimate, Male MOE, Male Estimate, Female MOE, Female Total Estimated MOE, Total
    Total Population 148,535,646 6,574 152,925,887 6,584 301,461,533 9,304
    Under 5 years 10,663,983 3,725 10,196,361 3,557 20,860,344 5,151
    5 to 9 years old 10,137,130 15,577 9,726,229 16,323 19,863,359 22,563
    10 to 14 years old 10,567,932 16,183 10,022,963 17,199 20,590,895 23,616
    ... ... ... ... ...    
    62 to 64 years old 3,888,274 11,186 4,257,076 11,970 8,145,350 16,383
    Total for Age 0 to 64 years old 132,508,316 48,688 130,952,347 49,105 263,460,663 69,151
    Total for Age 65 years and older 16,027,330 49,130 21,973,540 49,544 38,000,870 69,774
    2009 American FactFinder


    An estimate for the number of people age 65 and older is equal to the total population minus the population between the ages of zero and 64 years old:

    Number of people aged 65 and older: 301,461,533 - 263,460,663 = 38,000,870.

    The way to approximate the SE is the same as in part D. First we will sum male and female estimates across each age category and then approximate the MOEs. We will use that information to approximate the standard error for our estimate of interest:



    ... etc. ...

    And the SE for the total number of people aged 65 and older is:



    Again, as in Example D, the estimate and its MOE are published in B09017. The total number of people aged 65 or older is 38,000,870 with a margin of error of 4,944. Therefore the standard error is:

    SE(38,000,870) = 4,944 / 1.645 = 3,005.

    The approximated standard error using the seventeen derived age group estimates yields a standard error roughly 14.1 times larger than the actual SE.

    Data users can mitigate the problems shown in examples A through E to some extent by utilizing a collapsed version of a detailed table (if it is available) which will reduce the number of estimates used in the approximation. These issues may also be avoided by creating estimates and SEs using the Public Use Microdata Sample (PUMS) or by requesting a custom tabulation, a fee-based service offered under certain conditions by the Census Bureau. More information regarding custom tabulations may be found at http://www.census.gov/acs/www/data_documentation/custom_tabulations/.
    Puerto Rico Community Survey Multiyear Accuracy of the Data (3-year 2010-2012 and 5-year 2008-2012)
    Introduction
    This multiyear PRCS Accuracy of the Data document pertains to both the 2010-2012 3-year PRCS data products and the 2008-2012 5-year PRCS data products. Differences will be noted where applicable.
    The data contained in these data products are based on the Puerto Rican Community Survey (PRCS) sample. For the 3-year data products interviews from January 1, 2010 through December 31, 2012 were used. For the 5-year data products, interviews from January 1, 2008 through December 31, 2012 were used. Data products were produced for 1-year estimates (2008, 2009, 2010, 2011 and 2012), in addition to the set of 3-year and 5-year estimates.
    In general, PRCS estimates are period estimates that describe the average characteristics of population and housing over a period of data collection. The 2010-2012 3-year PRCS estimates are averages over the period from January 1, 2010 to December 31, 2012 and the 2008-2012 5-year PRCS estimates from January 1, 2008 to December 31, 2012, respectively. Multiyear estimates cannot be used to say what is going on in any particular year in the period, only what the average value is over the full period.
    The PRCS sample is selected from all municipios in Puerto Rico (PR). In 2006, the PRCS began collection of data from sampled persons in group quarters (GQs) - for example, military barracks, college dormitories, nursing homes, and correctional facilities. Persons in group quarters are included with persons in housing units (HUs) in all 2010-2012 3-year and 2008-2012 5-year PRCS estimates based on the total population.
    The PRCS, like other statistical activity, is subject to error. The purpose of this documentation is to provide data users with a basic understanding of the PRCS sample design, estimation methodology, and accuracy of the 2010-2012 3-year and 2008-2012 5-year PRCS estimates. The PRCS is sponsored by the U.S. Census Bureau, and is part of the 2010 Decennial Census Program.
    Additional information on the design and methodology of the PRCS, including data collection and processing, can be found at:
    http://www.census.gov/acs/www/methodology/methodology_main/.
    The Multiyear Accuracy of the Data from the American Community Survey can be found at http://www.census.gov/acs/www/Downloads/data_documentation/Accuracy/MultiyearACSAccuracyofData2012.pdf.
    Data Collection
    The PRCS employs three modes of data collection:
    • Mailout/Mailback
    • Computer Assisted Telephone Interview (CATI)
    • Computer Assisted Personal Interview (CAPI)
    The general timing of data collection is:
    Month 1: Addresses in sample that are determined to be mailable are sent a questionnaire via the U.S. Postal Service.
    Month 2: All mail non-responding addresses with an available phone number are sent to CATI.
    Month 3: A sample of mail non-responses without a phone number, CATI non-responses, and unmailable addresses are selected and sent to CAPI.
    Sample Design
    Sampling rates are assigned independently at the census block level. A measure of size is calculated for each municipio. The measure of size is an estimate of the number of occupied housing units in the municipio. This is calculated by multiplying the number of PRCS addresses by an estimate of the occupancy rate from the 2010 Census and the PRCS at the block level. A measure of size for each Census Tract is also calculated in the same manner.

    Each block is then assigned the smallest measure of size (GUMOS) from the set of all entities it is a part of. The 2008-2010 second-stage sampling strata and the overall first-phase sampling rates are shown in Table 1 below. Sampling rates for 2011 and 2012 are shown in a separate table, Table 2. Beginning in 2011 the PRCS (along with the ACS) implemented a sample reallocation, increasing the number of second-stage sampling strata from seven to 16. Not all of the 16 sampling strata are applicable in Puerto Rico. Table 2 gives only the sampling rates for the PRCS that are in applicable strata.

    Table 1. 2008 Through 2010 Sampling Rates for Puerto Ricos

    Stratum Thresholds 2008 Sampling Rates 2009 Sampling Rates 2010 Sampling Rates
    0 < MOS1 ≤ 200 10.0% 10.0% 10.0%
    200 < MOS ≤ 800 8.0% 8.0% 7.9%
    800 < MOS ≤1,200 4.0% 4.0% 3.9%
    2,000 ≤TRACTMOS2 2.0% 2.0% 2.0%
    All other areas 2.7% 2.7% 2.6%
    1MOS = Measure of size of the smallest governmental entity
    2TRACTMOS = Census Tract measure of size.


    Table 2. 2011 Sampling Rates for Puerto Rico

    Stratum Thresholds Target Sampling Rate(3.54 Million) 2011 Percent In Sample 2012 Sampling Rates
    0 < MOS1 ≤ 200 15.00% 14.81% 15.00%
    200 < MOS ≤ 400 10.00% 9.94% 10.00%
    400 < MOS ≤ 800 7.00% 6.97% 7.00%
    800 < MOS ≤ 1,200 4.34% 4.44% 3.95%
    0 < TRACTMOS2 ≤ 400 5.43% 5.55% 4.94%
    400 < TRACTMOS ≤ 1,000 4.34% 4.46% 3.95%
    1,000 < TRACTMOS ≤ 2,000 2.64% 2.71% 2.40%
    2,000 < TRACTMOS ≤ 4,000 1.55% 1.61% 1.41%
    4,000 < TRACTMOS ≤ 6,000 0.93% 0.96% 0.85%
    6,000 < TRACTMOS 0.54% 0.57% 0.49%
    1MOS = Measure of size of the smallest governmental entity
    2TRACTMOS = Census Tract measure of size.

    Addresses determined to be unmailable do not go to the CATI phase of data collection and are subsampled for the CAPI phase of data collection at a rate of 2-in-3. Subsequent to CATI, all addresses for which no response has been obtained are subsampled. This subsample is sent to the CAPI data collection phase. Beginning with the CAPI sample for the January 2006 panel (March 2006 data collection), the CAPI subsampling rate was based on the expected rate of completed mail and CATI interviews at the tract level.

    Table 3. 2006 Through 2012 CAPI Subsampling Rates for Puerto Rico
    Address and Tract Characteristics 2006, through 2012 CAPI Subsampling Rates
    Unmailable addresses 66.7%
    Mailable addresses (June through December) 50.0%


    For a more detailed description of the PRCS sampling methodology, see the 2012 PRCS Accuracy of the Data for Puerto Rico document http://www.census.gov/acs/www/Downloads/data_documentation/Accuracy/PRCS_Accuracy_of_Data_2012.pdf

    For more information relating to sampling in a specific year, please refer to the individual years Accuracy of the Data document http://www.census.gov/acs/www/data_documentation/documentation_main/.

    Weighting Methodology
    The multiyear estimates should be interpreted as estimates that describe a time period rather than a specific reference year. For example, a 5-year estimate for the poverty rate of a given area describes the total set of people who lived in that area over those five years much the same way as a 1-year estimate for the same characteristic describes the set of people who lived in that area over one year. The only fundamental difference between the estimates is the number of months of collected data which are considered in forming the estimate. For this reason, the estimation procedure used for the multiyear estimates is an extension of the 2012 1-year estimation procedure. In this document only the procedures that are unique to the multiyear estimates are discussed.

    To weight the 3-year estimates, 36 months of collected data are pooled together. For the 5-year estimates, 60 months are pooled. The pooled data are then reweighted using the procedures developed for the 2012 1-year estimates with a few adjustments. These adjustments concern geography, month-specific weighting steps, and population controls. In addition to these adjustments, there is one multiyear specific model-assisted weighting step.<