The Oxford Handbook of Bayesian Econometrics
Editor
- Geweke, John(Distinguished Professor, Economics Discipline Group, University of Technology Sydney)Koop, Gary(Professor of Economics, University of Strathclyde)van Dijk, Herman(Professor of Econometrics, Econometric Institute, Erasmus University Rotterdam and Econometrics Department, VU University Amsterdam)
Abstract
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. 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 RotterdamSuggested Citation
- Geweke, John & Koop, Gary & van Dijk, Herman (ed.), 2013. "The Oxford Handbook of Bayesian Econometrics," OUP Catalogue, Oxford University Press, number 9780199681334.
Handle: RePEc:oxp:obooks:9780199681334
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Citations
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Cited by:
- Olga Korotkikh, 2020. "A Multi-Country BVAR Model for the External Sector," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 98-112, December.
- Barbara Rossi, 2019.
"Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them,"
Working Papers
1162, Barcelona School of Economics.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
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