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The Oxford Handbook of Bayesian Econometrics
Edited by John Geweke, Gary Koop, and Herman van Dijk
576 pages
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55 Figures, 22 Tables
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246x171mm
978-0-19-955908-4
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Hardback
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29 September 2011
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- Contributions from prominent Bayesians on the latest developments in their specific fields of expertise
- Covers a broad range of the methods and models used by Bayesian econometricians in a wide variety of fields, including macroeconomics, microeconomics, finance and marketing
- Bridges the gap from textbook to research and helps facilitate empirical work
- Many chapters include flexible or nonparametric models
- Organised into three parts: principles, methods, and applications
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.Readership: Econometricians, empirical economists, policymakers, researchers and graduate students.
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Edited by John Geweke, Distinguished Research Professor, University of Technology Sydney; Research Professor, University of Colorado, Gary Koop, Professor of Economics, University of Strathclyde, and Herman van Dijk, Director of Tinbergen Institute and Professor of Econometrics at Econometric Institute, Erasmus University, Rotterdam 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.
Contributors: 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 Católica 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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"This Handbook is an excellent piece of scholarly work that displays the full power of the Bayesian method." - Gael Martin
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John Geweke, Gary Koop, and Herman van Dijk: Introduction
Part I: Principles
1: Gary Chamberlain: Bayesian Aspects of Treatment Choice
2: Dale Poirier: Exchangeability, Representation Theorems, and Subjectivity
Part II: Methods
3: Paolo Giordani, Michael Pitt, and Robert Kohn: Bayesian Inference for Time Series State Space Models
4: Jim Griffin, Fernando Quintana, and Mark Steel: Flexible and Nonparametric Modelling
5: Siddhartha Chib: Introduction to Simulation and MCMC Methods
Part III: Applications
6: Mingliang Li and Justin Tobias: Bayesian Methods in Microeconometrics
7: Marco Del Negro and Frank Schorfheide: Bayesian Macroeconometrics
8: Peter Rossi and Greg Allenby: Bayesian Applications in Marketing
9: Eric Jacquier and Nicholas Polson: Bayesian Econometrics in Finance
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The specification in this catalogue, including without limitation price, format, extent, number of illustrations, and month of publication, was as accurate as possible at the time the catalogue was compiled. Occasionally, due to the nature of some contractual restrictions, we are unable to ship a specific product to a particular territory. Jacket images are provisional and liable to change before publication.
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