  In economic development, there are often regions that share similar economic
characteristics, and economic models on such regions tend to have similar
covariate effects. In this paper, we propose a Bayesian clustered regression
for spatially dependent data in order to detect clusters in the covariate
effects. Our proposed method is based on the Dirichlet process which provides a
probabilistic framework for simultaneous inference of the number of clusters
and the clustering configurations. The usage of our method is illustrated both
in simulation studies and an application to a housing cost dataset of Georgia.

Econometrics;Computation