Items related to Introduction to Modern Bayesian Econometrics
Synopsis
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
"synopsis" may belong to another edition of this title.
About the Author
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.
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.
From the Inside Flap
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.
- PublisherWiley-Blackwell
- Publication date2004
- ISBN 10 1405117206
- ISBN 13 9781405117203
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages416
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Introduction to Modern Bayesian Econometrics
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Paperback. Condition: new. Paperback. In this new and expanding area, Tony Lancasters 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 * Provides a comprehensive introduction to the Bayesian way of doing applied economics * Emphasizes computation and the study of probability distributions by computer sampling * Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781405117203
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Introduction to Modern Bayesian Econometrics
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