Developing More Accurate Reasonable Rent Estimates in the U.S. Housing Choice Voucher Program

  • David P. Varady University of Cincinnati
  • Xinhao Wang University of Cincinnati
  • Jay Mittal University of Cincinnati
Keywords: Housing, Reasonable Rent, Voucher, Regression


If the U.S. Department of Housing and Urban Development's (HUD's) Housing

Choice Voucher program (HCV) is to be successful, it is important that the rents charged by property owners are reasonable; otherwise the effect could be to inflate costs in the housing market as a whole. This paper describes a cost-effective approach that local public housing authorities in the United States could use to develop reasonable rent estimates. The methodology involves (1) cluster analysis to combine similar census block groups, and (2) regression analysis to predict market rent based on cluster location, number of bedrooms, building age, and building type. In the paper we demonstrate the superiority of this methodology to the tabular housing market region methodology currently being used by the Cincinnati Metropolitan Housing Authority. Our clusters - which contain block groups not necessarily spatially linked - are relatively homogeneous and therefore correspond relatively closely to the housing submarkets utilized by householders in making their mobility and locational choices.


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