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The Poverty Concentration Implications of Housing Subsidies: A Cellular Automata Thought Experiment


  • Kevin Jewell


Looking 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.

Suggested Citation

  • Kevin Jewell, 2005. "The Poverty Concentration Implications of Housing Subsidies: A Cellular Automata Thought Experiment," Urban/Regional 0505009, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpur:0505009
    Note: Type of Document - pdf; pages: 17

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    Cited by:

    1. 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.

    More about this item


    low income housing tax credit; Residential Location; Simulation; segregation; cellular automata;

    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, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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