Hi,
I am trying to replicate the HUD AMI Household income distribution using the 2017-2021 ACS PUMS data for Colorado (see https://www.huduser.gov/portal/datasets/cp.html) . Does anyone have a source for the algorithm used by the Census Bureua to calculate the counts HUD uses?
Specifically, I'd like information estimating the number of households at 30% AMI used by HUD CHAS data
This working paper presents analysis of custom tabulations of the 2006-2010 American Community Survey (ACS), known as the "CHAS data." The CHAS data combine ACS microdata with HUD adjusted median family incomes (HAMFI) to create estimates of the number of households that would qualify for HUD assistance. Using these data, I estimate the number of rental units and ownership units that would be available to prototypical households at specified income levels.
https://www.huduser.gov/portal/publications/workpapr.html?search=program%20evaluation%20division
TIA
AB
I'm working on a related project that tries to do a similar analysis by recreating the HUD AMI data (as close as possible) using ACS (PUMS) data (via Small Area Estimation if needed).
One issue that I have is finding a cross walk between HUD AMI areas (mostly counties ?) and say county FIPS or census tract FIPS for the HUD AMI data as discussed in this paper
https://www.huduser.gov/portal/datasets/il/il24/Medians-Methodology-FY24.pdf
Any help appreciated.
Dave Dorer
Hi David -- yes, AMI areas are based on counties. Counties in metro areas are grouped together (but these groupings may not reflect the official OMB delineations), while each non-metropolitan county is its own AMI area. HUD's Excel workbook of income limits shows the relationship between counties (the `fips` field) and AMI areas (the `hud_area_code` field). The 2024 version is linked from https://www.huduser.gov/portal/datasets/il.html#data_2024.
As you probably saw in the methodology document you linked to, though, not every non-metropolitan county gets its own set of income limits because of how HUD handles differences in the reliability of ACS income data.