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

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.

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