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Bayesian and Frequentist Approaches to Hedonic Modeling in a Geo-Statistical Framework

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  • Ghosh, Gaurav S.
  • Carriazo, Fernando

Abstract

We compare Least Squares, Maximum Likelihood and Bayesian approaches to estimation in a Hedonic context. The approaches are compared from theoretical and practical perspectives and from the viewpoint of a policy maker or urban planner. The approaches are applied to data on the property market in Bogota, Colombia. We find that no approach is unambiguously better than the others and recommend that choice of estimation technique should be predicated upon the characteristics of the policy problem at hand.

Suggested Citation

  • Ghosh, Gaurav S. & Carriazo, Fernando, 2007. "Bayesian and Frequentist Approaches to Hedonic Modeling in a Geo-Statistical Framework," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9916, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea07:9916
    DOI: 10.22004/ag.econ.9916
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    Cited by:

    1. Anthony C Constantinou & Norman Fenton, 2017. "The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-30, June.

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    Keywords

    Research Methods/ Statistical Methods;

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