Bayesian Clustered Coefficients Regression with Auxiliary Covariates\n Assistant Random Effects

In regional economics research, a problem of interest is to detect\nsimilarities between regions, and estimate their shared coefficients in\neconomics models. In this article, we propose a mixture of finite mixtures\n(MFM) clustered regression model with auxiliary covariates that account for\nsimilarities in demographic or economic characteristics over a spatial domain.\nOur Bayesian construction provides both inference for number of clusters and\nclustering configurations, and estimation for parameters for each cluster.\nEmpirical performance of the proposed model is illustrated through simulation\nexperiments, and further applied to a study of influential factors for monthly\nhousing cost in Georgia.\n