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Big Data Accessibility Measures And Urban Land Valuation

Author

Listed:
  • Steven C. Bourassa
  • Martin Hoesli
  • Louis Merlin
  • John Renne

Abstract

Big data applications are attracting increasing interest on the part of urban researchers. One such application is the use of accessibility indexes based on travel data aggregated from personal devices, such as cell phones, in hedonic price models. This paper evaluates the benefits of using big data employment accessibility indexes in the context of urban property valuation. The study compares big data indexes with traditional measures of accessibility based on straight-line distances to key locations and indexes derived from regional travel demand models used by local transportation planning agencies. Controls for geographic submarkets is also used as a means for measuring the value of location. Using residential property transactions from the Miami, Florida, metropolitan area, the study concludes that the traditional straight-line distances and especially the geographic submarkets perform better than the big data and travel demand model measures.

Suggested Citation

  • Steven C. Bourassa & Martin Hoesli & Louis Merlin & John Renne, 2019. "Big Data Accessibility Measures And Urban Land Valuation," AfRES 2019-060, African Real Estate Society (AfRES).
    • Handle: RePEc:afr:wpaper:2019-060
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    More about this item

    Keywords

    accessibility indexes; Big data; Hedonic Models; Property Valuation; travel demand models;
    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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