Bayesian Model Averaging in the Context of Spatial Hedonic Pricing: An Application to Farmland Values

18 Pages Posted: 27 Jul 2011

See all articles by Geerte Cotteleer

Geerte Cotteleer

affiliation not provided to SSRN

Tracy Stobbe

Trinity Western University

G. Cornelis van Kooten

University of Victoria - Economics

Date Written: August 2011

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.

Suggested Citation

Cotteleer, Geerte and Stobbe, Tracy and van Kooten, G. Cornelis, Bayesian Model Averaging in the Context of Spatial Hedonic Pricing: An Application to Farmland Values (August 2011). Journal of Regional Science, Vol. 51, Issue 3, pp. 540-557, 2011. Available at SSRN: https://ssrn.com/abstract=1895916 or http://dx.doi.org/10.1111/j.1467-9787.2010.00699.x

Geerte Cotteleer

affiliation not provided to SSRN ( email )

Tracy Stobbe

Trinity Western University ( email )

G. Cornelis Van Kooten (Contact Author)

University of Victoria - Economics ( email )

Victoria V8W Y2Y, BC
Canada

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