"13930","6","archive","5",,,"disk0/00/01/39/30","2016-11-14 08:09:12","2021-08-27 17:41:38","2016-11-14 08:09:12","article",,,"show","","","1",,,"Piribauer","P.","","",,"","",,,,,"","","Bayesian Variable Selection in Spatial Autoregressive Models","pub","","","prog_pop","determinants of economic growth; Markov chain Monte Carlo methods; model uncertainty; Spatial autoregressive model; variable selection",,"This paper compares the performance of Bayesian variable selection approaches for spatial autoregressive models. It presents two alternative approaches that can be implemented using Gibbs sampling methods in a straightforward way and which allow one to deal with the problem of model uncertainty in spatial autoregressive models in a flexible and computationally efficient way. A simulation study shows that the variable selection approaches tend to outperform existing Bayesian model averaging techniques in terms of both in-sample predictive performance and computational efficiency. The alternative approaches are compared in an empirical application using data on economic growth for European NUTS-2 regions.","2016-10-01","published","Routledge","10.1080/17421772.2016.1227468",,,,,,"",,,,,"",,,,,"",,,,,"","",,"",,,,,,,"58","none",,,,"Spatial Economic Analysis","11","4",,"457-479",,,,,,,,,,,"TRUE",,"1742-1772",,,,,,"","","","",,"","",,,,,,,"",,,,,"FALSE","no",,"info:eu-repo/semantics/article",
"13930",,,,,,,,,,,,,,,,,,,"Crespo Cuaresma","J.","","","1838",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,