An Introduction to Bayesian Inference in Spatial Econometrics

18 Pages Posted: 22 Aug 2008

See all articles by Donald J. Lacombe

Donald J. Lacombe

West Virginia University - Regional Research Institute

Date Written: July 24, 2008

Abstract

This tutorial is designed to introduce readers to Bayesian variants of the standard SAR and SEM models that are the most widely used and applied models in spatial econometrics. Particular attention is paid to the mathematical derivations required to obtain the full conditional distributions required for Gibbs sampling. The models are derived using diffuse as well as natural conjugate priors for the parameters.

Keywords: Bayesian paradigm, Bayesian spatial econometrics

JEL Classification: C11, C21

Suggested Citation

Lacombe, Donald J., An Introduction to Bayesian Inference in Spatial Econometrics (July 24, 2008). Available at SSRN: https://ssrn.com/abstract=1244261 or http://dx.doi.org/10.2139/ssrn.1244261

Donald J. Lacombe (Contact Author)

West Virginia University - Regional Research Institute ( email )

P.O. Box 6825
Morgantown, WV 26506-6825
United States
1-304-293-8543 (Phone)
1-304-293-6699 (Fax)

HOME PAGE: http://community.wvu.edu/~djl041/

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