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«A Journal of Policy Development and Research HoPe VI Volume 12, Number 1 • 2010 U.S. Department of Housing and Urban Development Office of Policy ...»

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In general, increasing vacancy rates occur where home foreclosure rates are high. Some exceptions occur, most notably in Las Vegas, North Las Vegas, and Whitney, where the foreclosure rate is high but the residential vacancy rate is still comparatively low. Also of interest and warranting further examination are the concentrations of vacancies and foreclosures around Nellis Air Force Base. A military base is often a source of both employment and housing for a community (be it on-base or off-base housing). Any changes to or fluctuations in that military installation can have compounding effects on a community’s housing stock and exacerbate a housing crisis in terms of foreclosures and vacancies, as is occurring in Las Vegas.

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The mapping of foreclosure rates and vacancy rates can provide a starting point for studying the interrelationship between vacancy and foreclosure. More in-depth analysis is needed to understand the direct relationship between foreclosure rates and vacancy rates, which leads or lags the other, and the unique determinants of distress in Las Vegas.

Cityscape 155Renner and Wolf

156 Graphic Detail Impact A regulatory impact analysis must accompany every economically significant federal rule or regulation. The Office of Policy Development and Research performs this analysis for all economically significant rules of the U.S. Department of Housing and Urban Development. An impact analysis is a forecast of the annual benefits and costs accruing to all parties, including the taxpayers, from a given regulation. Modeling these benefits and costs involves use of past research findings, application of economic principles, empirical investigation, and professional judgment.

The Impact of Formula Allocation Discretion in the Housing Trust Fund Todd Richardson Barry Steffen U.S. Department of Housing and Urban Development This article reflects the views of the authors and does not necessarily reflect the views of the U.S. Department of Housing and Urban Development.

Abstract

The federal Housing Trust Fund (HTF) was created through the Housing and Economic Recovery Act of 2008, which also required the U.S. Department of Housing and Urban Development (HUD) to establish a formula for allocating housing subsidies to states and Insular Areas (American Samoa, Guam, the Northern Marianas Islands, and the Virgin Islands) on the basis of need. HUD’s Office of Policy Development and Research conducted a regulatory impact analysis of the Department’s proposed formula rule, assuming a hypothetical congressional appropriation of $1 billion for the HTF. The analysis summarized the Department’s approach to weighting various statutory factors of housing need and recognized distributional implications for states. The primary impact was determined to be a transfer from the federal government to states in an amount equal to the appropriation. A number of economic factors are not considered in this determination, but it is not clear that the data or capacity exists to examine such factors. This article updates the impact analysis using recent data and incorporates several corrections.

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Summary of the Housing Trust Fund The Housing and Economic Recovery Act (HERA) of 2008 authorized the Housing Trust Fund (HTF) by adding Section 1338 to the Federal Housing Enterprises Financial Safety and Soundness Act of 1992 (12 U.S.C. 4501 et seq.) (FHEFSSA). The law provides that the purpose of the HTF is to provide grants to states for two uses: (1) to increase and preserve the supply of rental housing for extremely low-income (ELI) and very low-income (VLI) families, including homeless families;

and (2) to increase homeownership for ELI and VLI families. A beneficial feature of the HTF program comes from the attention its authors paid to a common critique of construction subsidy programs—that the subsidies merely crowd out unsubsidized affordable housing and thus fail in some measure to reduce housing need (see Khadduri, Burnett, and Rodda, 2003, for literature review).

One way to read the legislation is that the law effectively directs the Department of Housing and Urban Development (HUD) to target the HTF to those places where crowding out is least likely to occur. Section 1338(c) directs HUD to establish by regulation a formula for allocating affordable housing funds by state to ELI and VLI households.

The statute provides that the HTF primarily should assist ELI households; that is, households with incomes that do not exceed 30 percent of the Area Median Income (AMI), with adjustments for family size. The law states that not less than 75 percent of the funds must be used to increase or preserve rental housing for ELI households or those living below the poverty line. The remaining 25 percent must serve VLI households; that is, households with incomes that do not exceed 50 percent of the AMI. No more than 10 percent of the funds may be used to increase homeownership and up to 10 percent of the funds may be used to pay for administrative costs.

Although Congress has not appropriated funds for the HTF to date, FHEFSSA requires HUD to issue regulations for allocating the funds according to the statutory formula within 12 months of its enactment, which occurred on July 30, 2008. HUD published the proposed regulations for formula allocation in the Federal Register on December 4, 2009.1 The economic impact of the HTF consists of a transfer from the taxpayer, through state governments, to ELI and VLI families. By expanding and preserving the supply of housing and lowering financial barriers to homeownership, the HTF will reduce the housing costs of ELI and VLI families and thus raise the consumer surplus of the program’s beneficiaries.





Proposed Allocation Formula of the Housing Trust Fund The HTF formula is based on Sec. 1338(c)(3) of FHEFSSA, as amended by HERA. The law provides that allocations for the 50 states, the District of Columbia, the Commonwealth of Puerto Rico, and the Insular Areas are to be based on four housing needs factors and a construction cost adjustment factor. The data from readily available standardized data sources for the Insular Areas, http://www.thefederalregister.com/d.p/2009-12-04-E9-28984 (accessed January 27, 2010).

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however, differ from those available from those sources for the 50 states, the Commonwealth of Puerto Rico, and the District of Columbia. Therefore, a separate allocation process for Insular Areas had to be proposed and is explained below. Except for the Insular Areas, each of the four factors is expressed as a ratio of the state relative to the nation. A statutory minimum of $3,000,000 is allocated to each of the 50 states and the District of Columbia.

HUD announced that it would allocate HTF moneys using the following process.

(i) Determine allocations to Insular Areas based on the proportion of renters who reside in those areas relative to the sum of all renters in Insular Areas, the United States, and the Commonwealth of Puerto Rico.

(ii) Determine allocations to the 50 states, the District of Columbia, and the Commonwealth of

Puerto Rico, using the statutory formula, with these steps:

(1) Estimate the relative level of housing needs using the statutory housing needs factors as

interpreted by HUD:

Factor 1: Shortage of ELI rental units. The ratio of the shortage of standard rental units that are both affordable and available to ELI renter households in each state compared with the aggregate shortage of standard rental units that are both affordable and available to ELI renter households in all the states.

HUD measured the shortage as the mathematical difference between the number of ELI renter households and the number of ELI-affordable rental units that either are currently occupied by ELI households or are vacant and available at affordable rents.2 (Affordable rent refers to rent that is not in excess of 30 percent of household income.) Factor 2: Shortage of VLI rental units. The ratio of the shortage of standard rental units that are both affordable and available to VLI renter households in each state to the aggregate shortage of standard rental units that are both affordable and available to VLI renter households in all the states.

For this factor as well, HUD calculated the shortage as the mathematical difference between the number of renter households with the specified income and the number of affordable rental units that either are currently occupied by households in this income range or are vacant and available at rents affordable at this income range. To avoid double counting the ELI shortages measured by Factor 1, HUD restricted the households covered by this factor to those with incomes of 30 to 50 percent of AMI, the upper end of the VLI range.3 Note that HUD conceivably could have interpreted “shortage” as the ratio, rather than the difference, between the estimated numbers of households and of units. No evidence exists indicating that this was Congress’s intent. Factors 1 and 2 would have become ratios of ratios under this method.

Factor 2 also excludes vacant units that are offered at rents affordable to ELI households, even though such units are available and would be affordable to those with incomes within 30 to 50 percent of AMI. The exclusion prevents these units from being double-counted toward reducing shortages both for the ELI in Factor 1 and the VLI in Factor 2.

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(2) Weight the four housing needs factors, assigning a weight of 50.0 percent to Factor 1,

12.5 percent to Factor 2, 25.0 percent to Factor 3, and 12.5 percent to Factor 4. The two factors addressing needs of ELI households, Factors 1 and 3, thus have a combined weight of 75 percent in keeping with statutory targeting of funds.

(3) Determine initial allocations by multiplying the amount of appropriation remaining after the Insular Areas’ allocation by the weighted factors.

(4) Determine cost-adjusted initial allocations by multiplying initial allocations by a

construction cost adjustment factor that is developed as follows:

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(iii) Determine final state allocations by increasing cost-adjusted initial allocations to a statutory minimum of $3,000,000, where necessary, and reallocating the remaining funds in proportion to cost-adjusted initial allocations.

We have used a special tabulation of American Community Survey (ACS) data5 to develop sample HTF allocations for states and Insular Areas, based on the above method and assuming a hypothetical $1 billion appropriation (exhibit 1). In addition to using more current data, the estimates Construction cost adjustments in this article are calculated relative to the mean of the 50 states, the District of Columbia, and the Commonwealth of Puerto Rico. Puerto Rico was excluded in the official impact analysis.

The special tabulation is called the Comprehensive Housing Affordability Strategy (CHAS) data; it was created to help HUD’s community development grantees comply with the analytical requirements of creating their Consolidated Plans. The new CHAS uses ACS data averaged across 2005-through-2007 surveys. See http://www.huduser.org/portal/datasets/cp.html (accessed January 29, 2010).

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The regulatory impact analysis that HUD originally submitted to the Office of Management and Budget used a CHAS tabulation of 2000 Census data. In the course of updating the analysis with the new CHAS data, the authors discovered that several components of housing need were inadvertently omitted from Factor 2 in the official submission. The omission (variables a10c19r, a10c20r, a10c21r) caused the estimated state shortages of very low-income units to be biased upward because VLI renter households were counted toward the shortage even if their rents were affordable to households with incomes of 30 to 50 percent of AMI.

In addition, the updated estimates in this article incorporate a correction in the calculation process, whereby estimates of affordable housing shortages are reset to zero if states have negative values (that is, have available units exceeding renters).

The authors judged that this adjustment would comply with the statute’s rules of construction (subsections (f)(3)(b), (f)(4) (b)), which provide that negative shortages imply “no shortage.” The adjustment had a small effect on Factor 2 values, as it applied to two states when using the 2000 CHAS data and one state when using the new CHAS data.

Cityscape 161Richardson and Steffen

Data Inadequacy and Insular Areas Allocations HERA provides that the HTF will provide allocations to the Insular Areas: American Samoa, Guam, the Northern Marianas Islands, and the Virgin Islands. HUD determined, however, that the data needed to make allocations to these areas using the four formula factors do not exist in detail comparable to the 50 states, the District of Columbia, and the Commonwealth of Puerto Rico.

In particular, neither the long-form decennial census nor the American Community Survey data would enable HUD to determine the number of households in ELI and VLI categories and the number of housing units affordable to these households in these income categories.8 HUD resolved the data limitation by adopting a more basic assessment of housing need in Insular Areas compared with the entire country: the percentage of renters residing in Insular Areas relative to the sum of all renters in Insular Areas, the United States, and the Commonwealth of Puerto Rico.

The small shares of renters residing in Insular Areas (0.01 percent in American Samoa, 0.06 percent in Guam, 0.03 percent in the Northern Marianas, and 0.06 percent in the Virgin Islands) make the Insular Area allocations insignificant for the purposes of this rule. Aggregate allocations for Insular Areas total $1.487 million for a hypothetical $1.0 billion appropriation. For comparison purposes, the Insular Areas receive $3.65 million out of the $1.825 billion fiscal year (FY) 2009 HOME Investment Partnerships Program appropriation.

Assessing Effects of HUD’s Discretionary Choices in Defining the Allocation Formula In developing the HTF allocation formula, HUD tested several alternatives to determine to what extent the resulting economic outcomes are sensitive to modest discretionary choices. None of the discretionary choices have any effect on Insular Areas.



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