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Heterogeneous Households and Market Segmentation in a Hedonic Framework

Author

Listed:
  • Martijn Droes
  • Martin Hoesli
  • Steven C. Bourassa

Abstract

This paper explores Rosen’s (1974) suggestion that within the hedonic framework there are natural tendencies toward market segmentation. We show that market segmentation can be estimated on the basis of an augmented hedonic model in which marginal prices are separated by household characteristics into different classes. The classes can either be exogenously defined or endogenously determined based on an unsupervised machine learning algorithm or a latent class formulation. We illustrate the usefulness of these methods using American Housing Survey data for Louisville and show that there are distinct housing market segments within the Louisville metropolitan area based on income and family structure.

Suggested Citation

  • Martijn Droes & Martin Hoesli & Steven C. Bourassa, 2019. "Heterogeneous Households and Market Segmentation in a Hedonic Framework," ERES eres2019_218, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2019_218
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    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2019-218
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    More about this item

    Keywords

    Hedonic Model; heterogeneous households; latent class; Machine Learning; Market Segmentation;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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