Bayesian Econometric Methods

Chan, Joshua/ Koop, Gary/ Poirier, Dale J./ Tobias, Justin L.

ISBN 10: 1108423388 / ISBN 13: 9781108423380

Published by Cambridge Univ Pr, 2019

About this Item

2nd edition. 480 pages. 9.75x7.00x1.25 inches. In Stock. Seller Inventory # x-1108423388

Bibliographic Details

Title: Bayesian Econometric Methods

Publisher: Cambridge Univ Pr

Publication Date: 2019

Binding: Hardcover

Condition: Brand New

Edition: 2nd Edition

About this title

Synopsis:

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying statistics, finance, marketing, and agricultural economics.

Book Description:

The second edition of Bayesian Econometric Methods illustrates Bayesian theory and application through a series of exercises, complete with solutions to those exercises and computer code. The book is suitable for graduate students in statistics, economics, finance and other disciplines.