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BAYESIAN MODEL AVERAGING IN THE CONTEXT OF SPATIAL HEDONIC PRICING: AN APPLICATION TO FARMLAND VALUES

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Abstract:

ABSTRACT Specification uncertainty arises in spatial hedonic pricing models because economic theory provides no guide in choosing the spatial weighting matrix and explanatory variables. Our objective in this paper is to investigate whether we can resolve uncertainty in the application of a spatial hedonic pricing model. We employ Bayesian Model Averaging in combination with Markov Chain, Monte Carlo Model Composition. The proposed methodology provides inclusion probabilities for explanatory variables and weighting matrices. These probabilities provide a clear indication of which explanatory variables and weighting matrices are most relevant, but they are case specific.

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1467-9787.2010.00699.x

Affiliations: 1: Environmental Economics and Natural Resources group, Wageningen University, Bode 129, Postbus 8130, 6700 EW Wageningen, The Netherlands. 2: School of Business, Trinity Western University, 7600 Clover Road, Langley, BC V2Y 1Y1, Canada. 3: Department of Economics, University of Victoria, P.O. Box 1700 STN CSC, Victoria, BC V8W 2Y2, Canada.

Publication date: August 1, 2011

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