Bayesian Econometric Methods

Preface; 1. The subjective interpretation of probability; 2. Bayesian inference; 3. Point estimation; 4. Frequentist properties of Bayesian estimators; 5. Interval estimation; 6. Hypothesis testing; 7. Prediction; 8. Choice of prior; 9. Asymptotic Bayes; 10. The linear regression model; 11. Basics of Bayesian computation; 12. Hierarchical models; 13. The linear regression model with general covariance matrix; 14. Latent variable models; 15. Mixture models; 16. Bayesian model averaging and selection; 17. Some stationary time series models; 18. Some nonstationary time series models; Appendix; Index.

Gary Koop is Professor of Economics at the University of Strathclyde. He has published numerous articles in Bayesian econometrics and statistics in journals such as Journal of Econometrics, Journal of the American Statistical Association and the Journal of Business and Economic Statistics. He is an associate editor for several journals, including the Journal of Econometrics and the Journal of Applied Econometrics. He is the author of the books Bayesian Econometrics, Analysis of Economic Data and Analysis of Financial Data. Dale J. Poirier is Professor of Economics at the University of California, Irvine. He is a Fellow of the Econometric Society, the American Statistical Association, and the Journal of Econometrics. He has been on the Editorial Boards of the Journal of Econometrics, Econometric Theory, and was the founding editor of Econometric Reviews. His professional activities have been numerous, and he has held elected positions in the American Statistical Association and the International Society for Bayesian Analysis. Previous books include Intermediate Statistics and Econometrics: A Comparative Approach and The Econometrics of Structural Change. Justin L. Tobias is Associate Professor of Economics, Iowa State University, and has also served as an Assistant/Associate Professor of Economics at the University of California, Irvine. Professor Tobias has authored numerous articles in leading journals, including the International Economic Review, the Journal of Applied Econometrics, the Journal of Business and Economic Statistics, the Journal of Econometrics, and the Review of Economics and Statistics.

'This is a very well written book on Bayesian econometrics with rigorous derivations and exercises. It will indeed be a book that is on the required reading list for an advanced course on Bayesian econometrics. The books by Poirier and Lancaster [Blackwell, 2004] do not have the nice set of exercises presented here.' Herman van Dijk, Erasmus University, Netherlands