Bayesian Econometric Methods
Published on 20. August 2007
978-0-511-29242-2 (ISBN)
Description
This volume in the Econometric Exercises series contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises.
This volume in the Econometric Exercises series contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises.
This volume in the Econometric Exercises series contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises.
Reviews / Votes
'I am deeply impressed by this articulate, outstanding work. It has the same high level of precision as Poirier's 1995 text on intermediate statistics and econometrics for MIT Press. The authors have taken the time and effort to explain as much as possible. Chapter 14 on latent variable models is probably the most important chapter offering new work. The authors' explanations are extensive for each of their models, and a reader who is interested in just one of the models will not have to rely on the results from any of the other models.' Frank Kleibergen, Brown University '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'I am deeply impressed by this articulate, outstanding work. It has the same high level of precision as Poirier's 1995 text on intermediate statistics and econometrics for MIT Press. The authors have taken the time and effort to explain as much as possible. Chapter 14 on latent variable models is probably the most important chapter offering new work. The authors' explanations are extensive for each of their models, and a reader who is interested in just one of the models will not have to rely on the results from any of the other models.' Frank Kleibergen, Brown University
'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
More details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Publishing group
Cambridge University Press
Target group
College/higher education
Professional and scholarly
Illustrations
Worked examples or Exercises; 39 Tables, unspecified; 39 Plates, unspecified
File size
2,38 MB
ISBN-13
978-0-511-29242-2 (9780511292422)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Gary Koop | Dale J. Poirier | Justin L. Tobias
Bayesian Econometric Methods
Book
01/2007
Cambridge University Press
€50.75
Article exhausted; check for reprint
Gary Koop | Dale J. Poirier | Justin L. Tobias
Bayesian Econometric Methods
Book
01/2007
Cambridge University Press
€97.79
Article exhausted; check for reprint
Persons
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.
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.
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.
Content
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.
