Introduction to Modern Bayesian Econometrics

Introduction to Modern Bayesian Econometrics

By: Tony Lancaster (author)Paperback

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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

About 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.


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

Product Details

  • ISBN13: 9781405117203
  • Format: Paperback
  • Number Of Pages: 416
  • ID: 9781405117203
  • weight: 796
  • ISBN10: 1405117206

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