Bayesian Econometric Methods

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

Series: Econometric Exercises

Subject categories
ISBNs
  • 9780521855716
  • 9780511292422
  • 9781107713895
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.
  • Cambridge University Press; January 2007
  • ISBN: 9780511292422
  • Read online, or download in secure PDF or secure ePub format
  • Title: Bayesian Econometric Methods
  • Series: Econometric Exercises
  • Author: Gary Koop; Dale J. Poirier; Justin L. Tobias
  • Imprint: Cambridge University Press
Subject categories
ISBNs
  • 9780521855716
  • 9780511292422
  • 9781107713895

In The Press

'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