Housing Units Without a Mortgage - B25092003 - Median Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months - American Community Survey 2013 (3-Year Estimates) (ACS2013_3yr) - Survey ACS 2013 (3-Year Estimates)

Data Dictionary:

ACS 2013 (3-Year Estimates)

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Survey: ACS 2013 (3-Year Estimates)

Data Source:

U.S. Census Bureau

Data set: American Community Survey 2013 (3-Year Estimates) (ACS2013_3yr)

Table:

B25092. Median Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months [3]

Universe: Universe: Owner-occupied housing units

Variable Details

B25092.	Median Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months
	Universe: Universe: Owner-occupied housing units
	B25092001Universe: Owner-occupied housing units B25092003 Housing Units Without a Mortgage Percent base: None - percentages not computed Aggregation method: Median, using bracket table: B25091, interpolation method: Pareto

Relevant Documentation:

Excerpt from:	Social Explorer; U.S. Census Bureau; American Community Survey 2013 3yr Summary File: Technical Documentation.
	ACS 2013-3yr Summary File: Technical Documentation -> Appendix A: Supplemental Documentation -> 2013 Subject Definitions -> Derived Measures -> Median

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.

Excerpt from:	Social Explorer; U.S. Census Bureau; American Community Survey 2013 3yr Summary File: Technical Documentation.
	ACS 2013-3yr Summary File: Technical Documentation -> Appendix A: Supplemental Documentation -> 2013 Subject Definitions -> Housing Variables -> Monthly Housing Costs as a Percentage of Household Income

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.