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Introduction to Modern Bayesian Econometrics
 
 
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Introduction to Modern Bayesian Econometrics [Paperback]

Tony Lancaster (Author)
4.8 out of 5 stars  See all reviews (5 customer reviews)

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Book Description

1405117206 978-1405117203 June 28, 2004 1
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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Introduction to Modern Bayesian Econometrics + Bayesian Econometric Methods (Econometric Exercises) + Contemporary Bayesian Econometrics and Statistics (Wiley Series in Probability and Statistics)
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Editorial Reviews

Review

“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

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.

Product Details

  • Paperback: 416 pages
  • Publisher: Wiley-Blackwell; 1 edition (June 28, 2004)
  • Language: English
  • ISBN-10: 1405117206
  • ISBN-13: 978-1405117203
  • Product Dimensions: 9.5 x 6.7 x 0.9 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #258,545 in Books (See Top 100 in Books)

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Average Customer Review
4.8 out of 5 stars (5 customer reviews)
 
 
 
 
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12 of 14 people found the following review helpful:
5.0 out of 5 stars Great Book, March 19, 2006
This review is from: Introduction to Modern Bayesian Econometrics (Paperback)
If you are looking for a book for Bayesian estimation, this is the one. The first several chapters say it all about Bayesian methods. The rest of the book is applications. Very helpful reading for learning the method.
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2 of 2 people found the following review helpful:
5.0 out of 5 stars Best introductory Bayesian book, February 8, 2010
This review is from: Introduction to Modern Bayesian Econometrics (Paperback)
This is the best introductory Bayesian book for advanced undergraduate or first-year graduate students, especially in the social sciences. All concepts are explained in depth and illustrated with plenty of examples. I only wish that the publisher used a nicer-looking font for typesetting the book.
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3 of 4 people found the following review helpful:
5.0 out of 5 stars Very Good Start Point, April 25, 2008
This review is from: Introduction to Modern Bayesian Econometrics (Paperback)
This maybe the most straight forward and clearly presented introductory book to Bayesian Method in Econometrics.
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Inside This Book (learn more)
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An algorithm is a set of rules for doing a calculation. Read the first page
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Gibbs Sampler, Gibbs Sampling, New Jersey, Cambridge University Press, Journal of Applied Econometrics
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