The Oxford Handbook of Bayesian Econometrics
- Geweke, John(Distinguished Research Professor, University of Technology Sydney; Research Professor, University of Colorado)Koop, Gary(Professor of Economics, University of Strathclyde)van Dijk, Herman(Director of Tinbergen Institute and Professor of Econometrics at Econometric Institute, Erasmus University, Rotterdam)
AbstractBayesian 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. Contributors to this volume - Greg Allenby, Ohio State University Gary Chamberlain, Harvard University Siddhartha Chib, Washington University in St Louis Marco Del Negro, Federal Reserve Bank of New York John Geweke, University of Technology Sydney Paolo Giordani, Swedish Central Bank. Jim Griffin, University of Kent Eric Jacquier, HEC Montreal Robert Kohn, University of New South Wales Gary Koop, University of Strathclyde Mingliang Li, State University of New York at Buffalo Michael Pitt, University of Warwick Dale J. Poirier, University of California, Irvine Nicholas G. Polson, Booth School of Business, University of Chicago Fernando Pontificia, Universidad Catolica de Chile Peter E. Rossi, UCLA Anderson School of Management Frank Schorfheide, University of Pennsylvania Mark F.J. Steel, University of Warwick Justin Tobias, Purdue University Herman van Dijk, Erasmus University Rotterdam
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- Luc Bauwens & Dimitris Korobilis, 2013. "Bayesian methods," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 16, pages 363-380 Edward Elgar Publishing.
- Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
- Hanck, Christoph & Prüser, Jan, 2016. "House prices and interest rates: Bayesian evidence from Germany," Ruhr Economic Papers 620, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
- Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Integrated Deviance Information Criterion for Latent Variable Models," Economics and Statistics Working Papers 6-2018, Singapore Management University, School of Economics.
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