The Poverty Concentration Implications of Housing Subsidies: A Cellular Automata Thought Experiment
AbstractLooking at data from HUD’s low income housing tax credit database from 1987 to 2001, we examine how the US tax credit program has concentrated poverty in neighborhoods by offering advantages to developing low income housing projects in low income census tracts. We then use a simple Cellular Automata model to explore how alternative programs structures could impact economic diversity and poverty concentration. This model suggests that many widely dispersed fixed location affordable housing projects increase local economic diversity over alternative housing allocation rules. If policymakers wish align the Low Income Housing Tax Credit program with the goal of promoting economic diversity in our neighborhoods, they should restructure the bonus to reward to projects in areas without a concentration of subsidized housing.
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Bibliographic InfoPaper provided by EconWPA in its series Urban/Regional with number 0505009.
Length: 17 pages
Date of creation: 22 May 2005
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Note: Type of Document - pdf; pages: 17
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low income housing tax credit; Residential Location; Simulation; segregation; cellular automata;
Find related papers by JEL classification:
- R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
- R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
- R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Production Analysis, and Firm Location - - - Housing Supply and Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-05-29 (All new papers)
- NEP-CMP-2005-05-29 (Computational Economics)
- NEP-GEO-2005-05-29 (Economic Geography)
- NEP-URE-2005-05-29 (Urban & Real Estate Economics)
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- Lang, Bree J., 2012. "Location incentives in the low-income housing tax credit: Are qualified census tracts necessary?," Journal of Housing Economics, Elsevier, vol. 21(2), pages 142-150.
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