Costs and Utilization in the Housing Choice
Voucher Program (August 2003, 107 p.)
HUD, Congress, voucher program managers, researchers and
housing advocacy groups have focused on voucher utilization
and the related issues of success rates and program costs
for several years. Because under-utilization of vouchers results
in fewer families receiving housing assistance each year than
could be served with available resources, HUD would like to
make all possible efforts to maximize the utilization of vouchers
allocated to local programs. Understanding the drivers of
utilization can help voucher program administrators determine
whether controllable factors (e.g., PHA policies and practices)
or uncontrollable factors (e.g., market conditions or waiting
list characteristics) are at work when allocations are not
fully used. They can then take appropriate actions to improve
utilization when needed and when the factors affecting utilization
are under their control. Similarly, understanding drivers
of program subsidy costs can help program operators and policy
makers develop more accurate budget projections and can help
them understand potential trade-offs—for example, between
the numbers of families served on the one hand and the types
of families served and the quality of the housing they rent
on the other.
This study is intended to provide insights into the factors
that affect Housing Choice Voucher (HCV) program utilization
rates and costs in a sample of sites nationwide. The data
for the study were derived from existing computerized HUD
files, other secondary data sources, and primary data collected
on site at a sample of 48 PHAs. The bulk of the information
was gathered during on-site interviews with voucher program
staff as part of one- to two-day visits we made to each of
the study sites between December 2001 and April 2002. While
on site, we discussed aspects of each PHA’s local housing
market, participant characteristics and PHA policies, to assess
their impacts on subsidy costs and voucher utilization. In
addition to interviewing key PHA staff in person, we spoke
by telephone with local HUD staff, landlords, participants,
and community representatives regarding the programs. A sample
of participant files was also reviewed on site to determine
the time required for each of the several activities that
lead to getting a voucher under lease and to assess the completeness
of the files.
The sample was selected purposively to include PHAs with
high and low utilization rates and PHAs with high and low
costs across a range of program sizes and locations. A subset
of 28 of the PHAs were selected as pairs. A pair was defined
as two PHAs that served either the same or similar housing
markets and had at least a 10-point difference in the utilization
rate. By looking at pairs, we hoped to separate the factors
affecting utilization from the more general market-related
factors.
The sample was purposive rather than random, so we cannot
derive precise national estimates of the impacts of various
factors on program costs and utilization. While the results
from this study cannot be generalized to the entire universe
of PHAs, they should provide HUD with sufficient information
to support program decision-making and help identify areas
for technical assistance that can improve utilization rates
and assist PHAs in using their increased flexibility to optimize
local programs.
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