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Central City Revitalization: A Predictive Model

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  • David Melchert
  • Joel L. Naroff

Abstract

The object of this paper is to increase the understanding of the gentrification process by developing a set of representative indices that could be used to assess the likelihood of gentrification occurring in a central city neighborhood. Using Boston, Massachusetts as a representative city, economic, housing, social and amenity variables were collected from the 1970 U.S. Census. A sample of blocks that did and did not revitalize after 1970 was chosen. As the gentrification outcome was known with certainty, a logistic regression model was estimated. The estimated model quite accurately classified the neighborhoods into their respective grouping, resulting in a block‐level statistical model of housing revitalization.

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  • David Melchert & Joel L. Naroff, 1987. "Central City Revitalization: A Predictive Model," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 15(1), pages 664-683, March.
    • Handle: RePEc:bla:reesec:v:15:y:1987:i:1:p:664-683
    DOI: 10.1111/1540-6229.00409
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    Cited by:

    1. Helms, Andrew C., 2003. "Understanding gentrification: an empirical analysis of the determinants of urban housing renovation," Journal of Urban Economics, Elsevier, vol. 54(3), pages 474-498, November.
    2. Jonathan Reades & Jordan De Souza & Phil Hubbard, 2019. "Understanding urban gentrification through machine learning," Urban Studies, Urban Studies Journal Limited, vol. 56(5), pages 922-942, April.
    3. Munneke, Henry J. & Womack, Kiplan S., 2015. "Neighborhood renewal: The decision to renovate or tear down," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 99-115.

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