Description

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

Introduction to Modern Bayesian Econometrics

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£34.99

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Paperback / softback by Tony Lancaster

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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... Read more

    Publisher: John Wiley and Sons Ltd
    Publication Date: 20/04/2004
    ISBN13: 9781405117203, 978-1405117203
    ISBN10: 1405117206

    Number of Pages: 416

    Non Fiction , Business, Finance & Law

    Description

    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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