FMR Methodology Changes Under Consideration

The Department of Housing and Urban Development (HUD) is proposing to change the methodology used for estimating fair market rents. Fair market rents (FMRs) are used as the basis for payment standards which determine the maximum level of assistance in the housing choice voucher program. They are also used by certain other programs. The Department’s FMRs are set at a level that should allow a program participant to afford to rent a unit for approximately 40 percent of an area’s standard quality stock.

The Department is updating the methodology for calculating FMRs because in the past it has received comments stating that “FMRs need to incorporate more local and more timely data.” In its comments on the fiscal year (FY) 2019 FMRs, NAHRO recommended that HUD use more timely data when calculating FMRs, fund local research surveys, and continue to refine its methodology for calculating FMRs. Additionally, the Senate Transportation and Housing and Urban Development (THUD) Appropriations subcommittee, in report language, urged HUD to improve its FMR estimates to “better reflect the rent inflation that occurs between the time that American Community Survey data is collected and the fiscal year for which the FMRs are produced.”

Comments on the updated process are due in 30 days. (6/5/19 edit – Comments are due by July 5, 2019.)

Click below to read more.

Current Process
Currently, HUD calculates FMRs by using American Community Survey (ACS) data to calculate a gross rent (shelter rent plus utilities) for the year three years before the fiscal year of the new FMRs are published (e.g., ACS data is used to calculate the gross rent for 2017 for the FY 2020 FMRs). The Department then updates this gross rent through the end of the next year using the annual change in certain components of the Consumer Price Index (CPI). Finally, the Department uses a trend factor (incorporating assumptions from the President’s Budget) to estimate the final FMRs. In using a trend factor, the Department utilizes a forecast of the Gross Rent Index. The forecast of the Gross Rent Index “is made up of two independently forecasted components of the Consumer Price Index: “Housing, Shelter, Rent of Primary Residence” and “Housing, Fuels and Utilities.” The forecasts are combined “using long-term average expenditure combination factors of approximately 80 percent and 20 percent.” This method is used for certain areas where the model can produce reliable forecasts. Other areas use a regionally based local trend factor.

Three Models
The Department is considering using one of three models to update the Gross Rent Index depending on the region and whether the model provides reliable forecasts in a particular region. These models were examined by a multi-disciplinary HUD research team.

  • National Input Model (NIM) – This model would incorporate a forecast of national residential fixed investment from the Bureau of Economic Analysis National Income and Product Accounts into the “Housing, Shelter, Rent of Primary Residence” component of the Gross Rent Index. The NIM did not produce as good results for the “Housing, Fuels and Utilities” component of the Gross Rent Index.
  • Pure Time Series (PTS) – For forecasting the “Housing, Fuels and Utilities” component of the Gross Rent Index, the PTS model—using previous values of local fuel and utilities index—produced the best results in certain areas.
  • Local Input Model (LIM) – A Local Input Model where forecasts are based on exogeneous variables (i.e., variables whose value is determined outside the model) such as local building permit data and employment data for the “Housing, Shelter, Rent of Primary Residence” and electricity prices for “Housing, Fuels and Utilities” components.

While the research team recommended that HUD use the National Input Model for primary residence rental calculation and Pure Time Series model for the forecast of the fuels and utilities, HUD would like to choose to use a different model depending on the location, in the hope that a particular model for a particular location will provide the most accurate forecast. The Department will include the model specification it uses to calculate local trend factors for each area in the online Fair Market Rent Documentation System.

Changes to Small Area FMR Methodology
Currently, when calculating small area FMRs (FMRs calculated over zip code geographies), where zip code level estimates are not available, HUD assigns a small area FMR based on the estimate of the gross rent for the county. This has the effect of producing small area FMRs based on much larger geographies, which are not accurate for the zip code over which the small area FMR is produced.

The Department is proposing to change this. In those areas where there are not zip code level estimates—i.e., zip code tabulation areas (ZCTA) do not have reliable data—HUD will see if the ZCTA is bordered by ZCTAs with reliable data. If half of these neighboring ZCTAs have reliable data, then HUD will use the weighted average as the basis for the small area FMR estimate.

Comments will be due in 30 days after the date of publication. The Department is interested in receiving comments on evaluating the accuracy of local trend factors and alternatives for assessing the best local forecast model to select.

FMRs produced with these methodological changes can be found here (when posted).
HUD’s report to Congress titled “Proposals to Update the Fair Market Rent Formula” can be found here.
HUD’s multi-disciplinary team’s research can be found here (when posted).
NAHRO’s comments on the FY 2019 FMRs can be found here.
The prepublication copy of this notice can be found here.
The version of this notice published in the Federal Register can be found here (when posted).

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