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Bayesian Econometric Methods
     

Bayesian Econometric Methods

by Gary Koop, Dale J. Poirier, Justin L. Tobias
 

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ISBN-10: 0521855713

ISBN-13: 9780521855716

Pub. Date: 08/28/2014

Publisher: Cambridge University Press

This book is a volume in the Econometric Exercises series. It teaches principles of Bayesian econometrics by posing a series of theoretical and applied questions, and providing detailed solutions to those questions. The text is primarily suitable for graduate study in econometrics, though it can be used for advanced undergraduate courses, and should generate interest

Overview

This book is a volume in the Econometric Exercises series. It teaches principles of Bayesian econometrics by posing a series of theoretical and applied questions, and providing detailed solutions to those questions. The text is primarily suitable for graduate study in econometrics, though it can be used for advanced undergraduate courses, and should generate interest from students in related fields, including finance, marketing, agricultural economics, business economics, and other disciplines that employ statistical methods. The book provides a detailed treatment of a wide array of models commonly employed by economists and statisticians, including linear regression-based models, hierarchical models, latent variable models, mixture models, and time series models. Basics of random variable generation and simulation via Markov Chain Monte Carlo (MCMC) methods are also provided. Finally, posterior simulators for each type of model are rigorously derived, and MATLAB computer programs for fitting these models (using both actual and generated data sets) are provided on the Web site accompanying the text.

About the Author:
Gary Koop is Professor of Economics at the University of Strathclyde

About the Author:
Dale J. Poirier is Professor of Economics at the University of California, Irvine

About the Author:
Justin L. Tobias is Associate Professor of Economics, Iowa State University

Product Details

ISBN-13:
9780521855716
Publisher:
Cambridge University Press
Publication date:
08/28/2014
Series:
Econometric Exercises Series
Pages:
380
Product dimensions:
6.85(w) x 9.76(h) x 1.02(d)

Related Subjects

Table of Contents

List of exercises     ix
Preface to the series     xv
Preface     xix
The subjective interpretation of probability     1
Bayesian inference     11
Point estimation     29
Frequentist properties of Bayesian estimators     37
Interval estimation     51
Hypothesis testing     59
Prediction     71
Choice of prior     79
Asymptotic Bayes     91
The linear regression model     107
Basics of Bayesian computation     117
Monte Carlo integration     119
Importance sampling     124
Gibbs sampling and the Metropolis-Hastings algorithm     128
Other (noniterative) methods for generating random variates     157
Hierarchical models     169
The linear regression model with general covariance matrix     191
Latent variable models     203
Mixture models     253
Some scale mixture of normals models     254
Other continuous and finite-mixture models     260
Bayesian model averaging and selection     281
Bayesian model averaging     282
Bayesian variable selection and marginal likelihoodcalculation     287
Some stationary time series models     297
Some nonstationary time series models     319
Appendix     335
Bibliography     343
Index     353

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