- the regression model (and variants applicable for use with panel data
- time series models
- models for qualitative or censored data
- nonparametric methods and Bayesian model averaging.
A website containing computer programs and data sets to help the student develop the computational skills of modern Bayesian econometrics can be found at: [external URL]
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.