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 is an excellent addition to a well conceived and motivated series. Written by three prolific and mature contributors to modern Bayesian econometrics, it is well organized, clear, concise, and comprehensive. Combined with its associated web site, which provides the related computer programs, it is complementary to currently available Bayesian econometrics texts and dramatically lowers the cost of learning and using modern Bayesian econometric methods.”
Pravin K. Trivedi, Indiana University
“Koop, Poirier and Tobias have constructed a set of exercises in Bayesian econometrics and exposited these and their solutions with the exceptional clarity and good sense that one associates with these authors. A number of these exercises are of interest in their own right and, taken together, they will all provide a valuable complement to the introductory texts in Bayesian econometrics that have recently appeared on the market.”
Anthony Lancaster, Brown University
“For the econometrician new to Bayesian methods, both the narrative and the exercises in this volume will expand conceptual horizons and establish new ways of thinking about econometrics. For the novice practitioner, the exercises provide an accessible bridge from theory to application. Experienced Bayesian practitioners will enjoy and benefit from testing their mettle on the wide selection of models treated in the book. Instructors at all levels will find material here that enhances classroom and computer laboratory experience.”
John Geweke, University of Iowa
“The book presents a concise and comprehensive narration of theory, computational techniques, and a range of applications related to Bayesian methods. Overall, this 350-page book covers a vast range of topics, presenting them in a clear and intuitive fashion that can help disseminate these techniques to a broad but technically savvy audience.”
Anirban Basu, Journal of the American Statistical Association
This book aims to teach Bayesian econometrics by providing a wide range of solved exercises. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics.
About the Author
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 Journal of Econometrics and 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, Journal of Applied Econometrics, Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics.
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