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In this new and expanding area, Tony Lancaster's text is the first comprehensive introduction to the Bayesian way of doing applied economics.
Uses clear explanations and practical illustrations and problems to present innovative, computer-intensive ways for applied economists to use the Bayesian method;
Emphasizes computation and the study of probability distributions by computer sampling;
Covers all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data;
Details causal inference and inference about structural econometric models;
Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software
Supported by online supplements, including Data Sets and Solutions to Problems, at www.blackwellpublishing.com/lancaster
“This book conveys the revolution in Bayesian statistics brought about by modern computing and simulation methods from a perspective that econometricians will find familiar. It works through the implications for econometric practice using practical examples and accessible computer software. Graduate students in economics will find it highly accessible. Practitioners steeped in classical econometric methods will find much that is new, exciting, and useful here as well.”
John Geweke, University of Iowa
“Lancaster′s text gives an impressive overview of the Bayesian point of view, and should prove a valuable resource to econometricians of all persuasions.” Werner Ploberger, University of Rochester
Introduction.
1. The Bayesian Algorithm.
2. Prediction and Model Checking.
3. Linear Regression.
4. Bayesian Calculations.
5. Nonlinear Regression Models.
6. Randomized, Controlled and Observational Data.
7. Models for Panel Data.
8. Instrumental Variables.
9. Some Time Series Models.
Appendix 1: A Conversion Manual.
Appendix 2: Programming.
Appendix 3: BUGS.
Index
Tony Lancaster is Herbert H. Goldberger Professor of Economics and Professor of Community Health at Brown University. He is the author of
The Econometric Analysis of Transition Data (1990), an Econometric Society Monograph.
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.