The Impact of the Low-Income Housing Tax Credit on Housing Supply and Affordability

• In Event: The Low-Income Tax Credit at 40: Implementation and Impacts

Abstract

The Low-Income Housing Tax Credit (LIHTC) is the largest federal subsidy for production of affordable rental housing in the United States. Since LIHTC attracts private investment into the housing market, and since it is part of the tax code, it has provided a consistent and predictable source of funding for affordable housing development for almost four decades. Yet, with an annual cost of about $8 billion in tax credits, LIHTC is a costly program. LIHTC has an annual cost of about $8 billion. If LIHTC development takes the place of market-rate housing, it may not increase total housing supply and its effect on affordability in the long-run may be small. This study evaluates LIHTC’s impact on housing supply and affordability, with an emphasis on how LIHTC developments interact with private-market construction and how effects vary across the affordability spectrum and neighboring areas. The analysis is designed to answer three questions: 1) Does LIHTC increase the overall supply of housing and the overall supply of rental housing in the areas in which it is built? 2) Does LIHTC affect the number of rental housing units affordable to people with extremely low, very low, low, and moderate incomes? and 3) Does LIHTC affect the supply and affordability of rental housing in neighborhoods contiguous to the ones in which they are built? 

We develop causal estimates of the impact of LIHTC on housing supply by exploiting the rules governing the allocation of credits at different subsidy levels. Properties located in Difficult Development Areas (DDAs) or Qualified Census Tracts (QCTs) are eligible for a "basis boost," which incentivizes developers to invest in areas where development is more costly (DDAs) and areas that are more economically distressed (QCTs). In these locations, developers can claim LIHTC for 130% of the project's eligible basis (the total amount of costs that qualify for the credit), instead of the standard 100%, effectively increasing the available credits by up to 30%.We use a both instrumental variables regressions and fuzzy regression discontinuity designs to identify local average treatment effects (LATEs) at the QCT and DDA margins. 

Data come primarily from the National Housing Preservation Database (address-level LIHTC property records, 1987–2024), HUD’s CHAS custom tabulations (affordability by AMI band, 2007–2018), and five-year American Community Survey estimates (total housing units, 2005–2009 through 2018–2022). The study documents data limitations—CHAS rounding rules and ACS multiyear averaging—and outlines mitigation strategies, including use of larger geographies and, where necessary, USPS address counts to improve precision on total-unit measures. Robustness checks include McCrary’s density test to validate RD assumptions and alternative specifications with and without controls to assess precision versus identification risk. 

Although prior literature has identified heterogeneous neighborhood impacts of LIHTC—on property values, demographic composition, and in some cases crowd-out of unsubsidized rental construction—this paper uniquely targets supply effects across affordability tiers and explicitly models spatial spillovers. The analysis aims to reconcile trade-offs between short-term affordability created by LIHTC and potential longer-run market responses, and to quantify the net addition of affordable units per dollar of subsidy.

Author

• Christina Plerhoples Stacy, Urban Institute
  Presenting Author