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Indicators of candidates for gentrification: a spatial framework

Author

Listed:
  • Ingemar Bengtsson
  • Fredrik Kopsch

Abstract

Purpose - The purpose of this paper is to establish measurable factors that can be used as early indicators of which neighborhoods are most likely to undergo a process of gentrification in a reasonably near future. Design/methodology/approach - Using 1990 data on key demographic variables for 128 neighborhoods in Stockholm, Sweden a model that allows both for testing of spatial clustering and for spatial spillovers between neighborhoods is estimated. It is hypothesized not only that gentrification depends on inter-neighborhood characteristics but also that gentrified neighborhoods will cluster and preferably be located in proximity to existing high income neighborhoods. Findings - The findings confirm the stated hypotheses. Among the results, it is shown that neighborhoods that gentrified between 1990 and 2012 were more likely to have been poor in 1990 and located closer to the CBD, they were also more likely to be close to neighborhoods with lower proportions of low income residents. It is also found that gentrified neighborhoods tend to cluster over space. Originality/value - Much of the previous literature on gentrification has concerned the actual driving forces behind gentrifying neighborhoods. This paper is more concerned with indicators that can be used to spot neighborhoods that are likely to undergo a gentrification process in the future. Such information can be valuable for real estate developers in the private sector, as it may lead to more successful investments. It may also be useful for city developers at the municipal organization.

Suggested Citation

  • Ingemar Bengtsson & Fredrik Kopsch, 2019. "Indicators of candidates for gentrification: a spatial framework," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 12(4), pages 736-745, April.
  • Handle: RePEc:eme:ijhmap:ijhma-06-2018-0038
    DOI: 10.1108/IJHMA-06-2018-0038
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    More about this item

    Keywords

    Sweden; Clustering; Gentrification; Educational growth; Neighbourhood analysis; Spatial spillover; R15; R21; R23;
    All these keywords.

    JEL classification:

    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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