Introduction to Modern Bayesian Econometrics / Edition 1

Introduction to Modern Bayesian Econometrics / Edition 1

by Tony Lancaster
     
 

About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.

In this new and

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Overview

About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.

In this new and expanding area, Tony Lancaster’s text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.

Product Details

ISBN-13:
9781405117203
Publisher:
Wiley
Publication date:
06/28/2004
Edition description:
New Edition
Pages:
416
Product dimensions:
9.69(w) x 7.44(h) x 0.85(d)

Related Subjects

Table of Contents

Preface
Introduction
1The Bayesian algorithm1
2Prediction and model criticism70
3Linear regression models112
4Bayesian calculations183
5Non-linear regression models227
6Randomized, controlled and observational data265
7Models for panel data277
8Instrumental variables311
9Some time series models342
App. 1A conversion manual259
App. 2Programming365
App. 3BUGS code375
References383
Index391

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