July 2003, ©2004
1. An Overview of Bayesian Econometrics.
2. The Normal Linear Regression Model with Natural Conjugate Prior and a Single Explanatory Variable.
3. The Normal Linear Regression Model with Natural Conjugate Prior and Many Explanatory Variables.
4. The Normal Linear Regression Model with Other Priors.
5. The Nonlinear Regression Model.
6. The Linear Regression Model with General Error Covariance Matrix.
7. The Linear Regression Model with Panel Data.
8. Introduction to Time Series: State Space Models.
9. Qualitative and Limited Dependent Variable Models.
10. Flexible Models: Nonparametric and Semi-Parametric Methods.
11. Bayesian Model Averaging.
12. Other Models, Methods and Issues.
Appendix A: Introduction to Matrix Algebra.
Appendix B: Introduction to Probability and Statistics.
Focuses on modelling and applications.
Provides a complete and up-to-date survey of techniques used in conducting Bayesian econometrics inference in practice.
Includes substantive coverage of computing which is crucial for the Bayesian econometrician. MATLAB computer code is provided on accompanying web site.