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«reNtal HousiNg Policy iN tHe uNited states Volume 13, Number 2 • 2011 U.S. Department of Housing and Urban Development | Office of Policy ...»

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30 percent AMI Affordable Unit = 30–50 percent AMI Affordable Unit = Vacant housing units that are for rent or rented, but not occupied, are assigned a utility payment through a hot deck allocation based on Census Division, structure type (mobile homes, single family, or multifamily), and number of bedrooms.6 The rental housing affordability level is adjusted using the standard bedroom adjustment that is applied for HUD sponsored programs.7 This analysis

uses six mutually exclusive categories of rental housing affordability:

1. Extremely Low-Rent Unit: (Unsubsidized) Gross rent affordable to households at 30 percent of AMI.

2. Very Low-Rent Unit: (Unsubsidized) Gross rent affordable only to households at 50 percent of AMI.

3. Low- to Moderate-Rent Unit: (Unsubsidized) Gross rent affordable only to households at 80 percent of AMI.

4. Moderate- to High-Rent Unit: (Unsubsidized) Gross rent affordable only to households at 120 percent of AMI.

5. Extremely High-Rent Unit: (Unsubsidized) Gross rent affordable only to households above 120 percent of AMI.

Although no consensus has been reached regarding how to measure affordability, convention among government officials, mortgage lenders, and property managers has been to gauge affordability based on rent-to-income ratios. Glaeser and Gyourko (2008) have suggested an alternate standard based on the convergence (or divergence) of marginal cost (construction cost) and price. This approach is subject to significant measurement challenges for rental housing because new rental production is low and variation in operating expenses is difficult to capture empirically. Similarly, some in academia have advocated for a residual income approach to measuring housing affordability; this is a desirable approach, but some data limitations present a challenge to adopting such a measure.

Hotdeck imputation randomly selects a value for missing variables among similar cases with no missing variables. This method preserves the distribution of the variable. In this instance, utility payments are allocated based on structure type, number of bedrooms, tenure, and census division using the hotdeckvar command in Stata. See appendix exhibit A-2 for details.

See appendix exhibit A-1 for the bedroom number adjustments.

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6. Nonmarket-Rent Unit: (Subsidized) Units self-reporting rental housing assistance, with no cash rent, or rent $5 per month.8 Although the total rental housing stock grew from 2007 to 2009, the number of rental units in the three most affordable rental housing stock segments actually shrunk (exhibit 14). The number of unsubsidized rental housing units that are affordable to households earning less than 30 percent of AMI decreased by an estimated 650,000 units. The number of nonmarket rent units—those reporting subsidy or offering de minimis rents—decreased by approximately 522,000. The number of very low-rent units also decreased; however, this reduction was not statistically significant.

Contrasting the contraction of the lowest rental housing stock segments was an apparent swelling of the moderate rent units. Rental housing units that are affordable to renters at 80 percent of AMI grew by more than 1.2 million units, and the number of rental housing units affordable at 120 percent of AMI increased by nearly 600,000 units—both statistically significant increases.

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Although efforts have been made to improve rental-assistance reporting in the AHS, historically it has been shown to be unreliable (Shroder, 1996).

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nationally representative, however: the AHS representative of U.S. housing stock, and the ACS representative of U.S. population and household statistics. In addition, both surveys collect data on household income and both contract and gross rent levels, which makes both surveys suitable for use in a rental housing affordability analysis. The advantages of the AHS are the detailed housing variables (including questions about rent subsidies) and its longitudinal design. The ACS is the key resource for local data on demographic and economic characteristics, and has the advantage of very large sample sizes (more than 20 times as large as the AHS) and it is conducted annually (opposed to biannually as with the AHS).

Although the AHS microdata files include data on local HUD income limits, the ACS microdata contains no such information. Developing a comparable file requires adding in additional income limit data. IPUMS provides geographic identifiers for a number of metropolitan areas based on 2000 Census Geography. Using the ACS microdata from IPUMS along with HUD published income limits from 2007 and 2009, it is possible to construct a data file with the rental housing affordability variables found in the AHS Housing Affordability Data Systems (HADS) files that were originally developed for the Millennial Housing Commission. Constructing these HADS ACS files allows for greater comparability with previous HUD housing affordability research and consistency with HUD program definitions and regulations.

With a few exceptions, HUD income limits are unique to counties and metropolitan areas. The county identifiers in the IPUMS data enable easy matching of HUD income limits to the microdata observations for counties that collectively contain nearly 70 percent of U.S. households. The implication is that it is possible to construct a data file that applies the most granular income limit data to a significant majority of sample observations using publicly available microdata. For the remainder of observations, HUD’s state-level income limits are applied to the sample rental housing units. Renters are categorized based on their income relative to the HUD AMI with adjustments for household size.9 Rental housing units are categorized based on the same HUD-published income limits, except in rural areas where the AHS may have the exact county-specific income limits, and the ACS file features the state income. The same bedroom- and person-size adjustments are made for the ACS data as are made in the AHS HADS data. Also the imputation of utilities in vacant rental housing units is similar in both (see appendix B for details).

Initial tabulations of the renter population by income category suggest that the 2007 and 2009 ACS and the 2007 and 2009 AHS yield similar national estimates. Exhibit 15 shows the estimate of renter households earning less than 30 percent of AMI, 30 to 50 percent of AMI, and 50 to 80 percent of AMI. With the exception of the low-income count in 2009, the ACS and AHS counts generally differ by 1 to 3 percent.

This result is encouraging; it affirms that the number of renter households with incomes less than 30 percent of AMI and between 30 and 50 percent of AMI increased amidst the worst economic downturn in recent history. Trend differences within the housing stock are larger, however. Because the ACS does not ask about rental housing assistance, it is not possible to compare the nonmarket rent category. Therefore, nonmarket rental housing units are included in both ACS and AHS tabulations See appendix exhibit A-1 for the household size adjustments.

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in exhibit 15 for ease of comparison. These nonmarket rental housing units are categorized based on gross rent, noncash rental housing units are captured in the extremely low-rent category, and rental housing units reporting subsidy are placed in the appropriate rental housing affordability category. Exhibit 16 shows comparison between the 2007 and 2009 ACS and AHS rental housing unit counts by affordability category.

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by roughly 0.5 million units. Both samples suggest an increase in the moderately affordable rental housing stock (50 to 80 percent of AMI) of nearly 1 million units. Although the ACS shows increases in the size of the affordable rental housing stock, this appears primarily driven by an overall increase in the total rental housing stock. Exhibit 17 shows the share of affordable rental housing units within the total rental housing stock. As a percentage of the total rental housing stock, the number of 30 percent of AMI and 30 to 50 percent of AMI affordable units actually decreased.

Percentages are arguably less useful if the concern is rental housing affordability, because additional affordable rental housing supply should ease overall affordability stresses regardless of its share of the overall distribution.

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Summary From 2007 to 2009, the ACS and AHS show large growth in the number of affordable rental housing units for renters with low- to moderate-incomes (affordable to households at 80 percent of AMI), and substantial increases in the number of extremely low-income renters. For the most affordable rental housing stock segments the data is mixed. During a period of rising rental housing vacancy rates, the AHS suggests a shrinking of the affordable rental housing stock. Categorizing rental housing units based on rents relative to local incomes, means that falling incomes could reduce the 86 Rental Housing Policy in the United States Rental Housing Affordability Dynamics, 1990–2009 local rental housing affordability threshold causing the number of units appearing as unaffordable to increase without a commensurate increase in rents. Appendix C explores the sources of the AHS increase in rental housing affordability, and suggests that the loss of affordability was largely driven by rent increases. The conflicting rental housing affordability trends in the ACS and AHS cannot be easily explained. Important differences in the assessment of occupancy and vacancy rates between the two surveys complicate comparisons. The inconsistency in trends across data sources underscores the need for more robust and granular data on rental housing, and additional public guidance from the Census Bureau regarding comparisons of housing estimates across surveys.

Affordable Supply Gap and Rent Burdens This section examines rental housing affordability using two approaches: the affordable rental housing supply gap and changes in household rent burdens. The first subsection describes the affordable rental housing supply gap at the national level before and during the recession, the second subsection estimates the supply gap at the metropolitan level, and the final section explores the change in rent burden for low-income renters.

Affordable Supply Gap at the National Level To provide a more complete picture of rental housing affordability at both a national and metropolitan level, the analysis relies heavily on the Census Bureau’s ACS PUMS. Relatively few representative data sources exist that allow for national and cross-metropolitan comparisons of renter incomes and rents. With the introduction of the ACS and IPUMS data from the Minnesota Population Center, it is possible to analyze cross-sectional differences in rental housing market conditions across large metropolitan areas because of the robust sample sizes.

Exhibit 18 shows the national estimates based on 2007 ACS microdata. The affordable supply gap variables are in the last two rows. The ACS tabulations suggest that under optimal sorting—where all the lowest rent units are filled with the lowest income renters—roughly 82 affordable rental housing units exist for households at 30 percent of AMI for every 100 renter households that were at or below 30 percent of AMI. This method may understate the severity of rental housing affordability, because units are classified as affordable if they have gross rents affordable at the top of each income threshold. Furthermore, optimal sorting is only a conceptual construct; an extremely low-rent

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unit in rural Arkansas is not a reasonable housing option for an extremely low-income household in San Francisco. In addition, higher income households are more likely to be selected over lower income tenants when competing for the same affordable unit, so affordable units occupied by higher income households may not be truly available to low-income households. When the availability dimension is applied—where available is defined as vacant or occupied by a household at or below the income threshold—only 43 affordable and available rental housing units exist per 100 extremely low-income renters (30 percent of AMI). Rental housing units with rents affordable at 30 percent of AMI have such low contract rents that the amount is likely to narrowly cover the landlord’s operating expenses in many housing markets, which requires a significant share of the rents to be subsidized. Although it is not possible to identify rental assistance in the ACS data, tabulations of the 2007 AHS find that 35 percent of rental housing units at this affordability level are subsidized. For renter households earning 30 to 50 percent of AMI, only 76 affordable and available rental housing units exist per 100 renters. Renter households at 80 percent of AMI have far more affordable rental options, but this analysis does not capture the physical adequacy or the neighborhood quality associated with these affordable rental housing units.

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Affordable Supply Gap at the Metropolitan Level The divergent trends in rents described in the Rent Trends section should lead to different rental housing affordability levels at the subnational level. The results of the metropolitan level analysis appear in exhibit 20. Some of the metropolitan areas listed are not fully identified in the public use microdata; as a result, population estimates are slightly lower when using the PUMS data than published census estimates. In addition, with a single-year sample, a nontrivial amount of sampling error exists.

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