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A Problem with Distance Variables and Alternatives for Their Use

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  • Michael C. Farmer
  • Syed Fuad
  • Kusum J. Naithani
  • Donald J. Lacombe

Abstract

Researchers commonly use distance variables to: (i) estimate the direct influence of a landmark on an outcome of interest, such as a neighborhood park on home price; or (ii) control for omitted spatial influences that affect predictions of key policy variables. While both uses continue, the use of distance as a control, such as distance to Central Business District (CBD), is now more common. Using distance to a given position such as CBD is added to multivariate analysis as a method to capture all remaining, or omitted spatial effects that influence the dependent variable. We show that there is a latent and inherent identification problem with the distance variable; and we show that this extends to the use of distance as a control. These biases affect more than the distance variable. They generate inconsistent estimates for all other spatially distributed variables in a model. We then introduce an alternative control that captures unmodeled influences that vary across space, and we show that this fully stabilizes all model parameter estimates and measures of model efficiency.

Suggested Citation

  • Michael C. Farmer & Syed Fuad & Kusum J. Naithani & Donald J. Lacombe, 2025. "A Problem with Distance Variables and Alternatives for Their Use," Journal of Real Estate Research, Taylor & Francis Journals, vol. 47(3), pages 299-321, July.
    • Handle: RePEc:taf:rjerxx:v:47:y:2025:i:3:p:299-321
    DOI: 10.1080/08965803.2024.2325244
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