Bayesian Econometric Methods (Econometric Exercises) (Paperback)

Gary Koop (Author), Dale J. Poirier (Author), Justin L. Tobias (Author)

Editorial Reviews
Review
“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
Product Description
A new book in the Econometric Exercises series, this volume 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.




Product Details
·   Paperback: 380 pages
·   Publisher: Cambridge University Press (January 15, 2007)
·   Language: English
·   ISBN-10: 0521671736
·   ISBN-13: 978-0521671736

Contents

List of exercises ix

Preface to the series xv

Preface xix

1 The subjective interpretation of probability 1

2 Bayesian inference 11

3 Point estimation 29

4 Frequentist properties of Bayesian estimators 37

5 Interval estimation 51

6 Hypothesis testing 59

7 Prediction 71

8 Choiceofprior 79

9 Asymptotic Bayes 91

10 The linear regression model 107

11 Basics of Bayesian computation 117

11.1 Monte Carlo integration 119

11.2 Importance sampling 124

11.3 Gibbs sampling and the Metropolis–Hastings algorithm 128

11.4 Other (noniterative) methods for generating random variates 157

12 Hierarchical models 169

13 The linear regression model with general covariance matrix 191

14 Latent variable models 203

15 Mixture models 253

15.1 Some scale mixture of normals models 254

15.2 Other continuous and finite-mixture models 260

16 Bayesian model averaging and selection 281

16.1 Bayesian model averaging 282

16.2 Bayesian variable selection and marginal likelihood calculation 287

17 Some stationary time series models 297

18 Some nonstationary time series models 319

Appendix 335

Bibliography 343

Index 353