Can more housing supply solve the affordability crisis? Evidence from a neighborhood choice model
Elliot Anenberg and
Edward Kung
Regional Science and Urban Economics, 2020, vol. 80, issue C
Abstract:
We estimate a neighborhood choice model using 2014 American Community Survey data to investigate the degree to which new housing supply can improve housing affordability. In the model, equilibrium rental rates are determined so that the number of households choosing each neighborhood is equal to the number of housing units in each neighborhood. We use the estimated model to simulate how rental rates would respond to an exogenous increase in the number of housing units in a neighborhood. We find that the rent elasticity is low, and thus marginal reductions in supply constraints alone are unlikely to meaningfully reduce rent burdens. The reason for this result appears to be that rental rates are more closely determined by the level of amenities in a neighborhood—as in a Rosen-Roback spatial equilibrium framework—than by the supply of housing.
Keywords: Housing affordability; Housing supply; Neighborhood choice (search for similar items in EconPapers)
JEL-codes: R21 R31 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166046217304283
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:80:y:2020:i:c:s0166046217304283
DOI: 10.1016/j.regsciurbeco.2018.04.012
Access Statistics for this article
Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou
More articles in Regional Science and Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().