Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians
on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art
in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.
John Geweke received his PhD in economics from the University of Minnesota. He has been Professor of economics/ statistics at the University of Wisconsin, Duke University, the University of Minnesota, and the University of Iowa. He is co-editor of Journal of Econometrics, past co-editor of Journal of Applied Econometrics, and past editor of Journal of Business and Economic Statistics. He has published widely in econometrics and statistics, with major contributions to the analysis of time series and Bayesian econometrics. Professor Geweke is an elected fellow of the Econometric Society and the American Statistical Association and a past President of the International Society for Bayesian Analysis. Gary Koop 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 Journal of Econometrics and Journal of Applied Econometrics. He is the author of Bayesian Econometrics, Bayesian Econometric Methods, Introduction to Econometrics, Analysis of Economic Data, and Analysis of Financial Data. Herman van Dijk received the Savage Prize for his PhD dissertation. His research interests are in Bayesian inference using simulation techniques, time series econometrics, and income distributions. He serves on the Editorial Board of major journals in econometrics. His publications consist of several books and more than 160 international scientific journal papers and reports.
PART I: PRINCIPLES ; PART II: METHODS ; PART III: APPLICATIONS