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Data Dictionary: ACS 2012 (3-Year Estimates)
you are here: choose a survey survey data set table variable details
Data Source: Social Explorer; U.S. Census Bureau
Universe: Housing units with a mortgage
Variable Details
T125. Selected Monthly Owner Costs as a Percentage of Household Income in 2012 for Housing Units with a Mortgage
Universe: Housing units with a mortgage
T125_001Housing Units with a Mortgage:
Percent base:
None - percentages not computed (variable is table universe)
Aggregation method:
Addition
Formula used to compute this variable:
Return_Value = ACS2012_3yr:B25091002; if (ACS2012_3yr:B25091002.IsNull) Return_Value.IsNull = true
Variables used in the formula:
ACS2012_3yr:B25091002
Owner-Occupied Housing Units: Housing Units with a Mortgage
Relevant Documentation:
Excerpt from: Social Explorer; U.S. Census Bureau; American Community Survey 2012 3yr Summary File: Technical Documentation.
  ACS 2012-3yr Summary File: Technical Documentation -> Appendix A: Supplemental Documentation -> 2010-2012 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.