Introduction to Modern Bayesian Econometrics

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9781405117203: Introduction to Modern Bayesian Econometrics

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

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Book Description:

Almost two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events. While his method has extensive applications to the work of applied economists, it is only recent advances in computing that have made it possible to exploit the full power of the Bayesian way of doing applied economics.In this new and expanding area, Tony Lancasters 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.The Introduction emphasizes computation and the study of probability distributions by computer sampling, showing how these techniques can provide exact inferences about a wide range of econometric problems. Covering all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data, it also details causal inference and inference about structural econometric models. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.

From the Back Cover:

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.

"About this title" may belong to another edition of this title.

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