Production technology and agglomeration for Japanese prefectures during 1991–2000**This paper was formerly entitled “Spatial agglomeration and spillover analysis for Japanese prefectures during 1991–2000†. We would like to acknowledge John Geweke; Ivan Jeliazkov; Yasuhiro Omori; Ruey Tsay; anonymous referees for their helpful comments and suggestions. We are also grateful to the seminar/conference participants at the Valencia/ISBA 8th World Meeting on Bayesian Statistics in Benidorm (Alicante), 61st European Meeting of the Econometric Society in Vienna, Joint Statistical Meetings 2006 in Seattle, 2006 Japanese Economic Association Autumn Meeting at Osaka City University, and International Workshop on Bayesian Statistics and Applied Econometrics at Tohoku University. The research for this work was supported by KAKENHI and was conducted while Kazuhiko Kakamu was staying at the Institute for Advanced Studies. He gratefully acknowledges the hospitality of the school

We analyse the seemingly unrelated regression (SUR) models with spatial dependencies from a Bayesian point of view and estimate the parameters of the models using a Markov chain Monte Carlo (MCMC) method. Further, we analyse the production technology and the economics of agglomeration in Japanese prefectures from 1991 to 2000, simultaneously taking into account spatial and serial correlation. Model comparison is done via log†marginal likelihoods, and it is found that the spatial error SUR model is the best model and that the economics of agglomeration and spatial heterogeneity decreased over this decade.