A new book in the Econometric Exercises series, this volume
contains questions and answers to provide students with useful
practice, as they attempt to master Bayesian econometrics. In
addition to many theoretical exercises, this book contains
exercises designed to develop the computational tools used in
modern Bayesian econometrics. The latter half of the book contains
exercises that show how these theoretical and computational skills
are combined in practice, to carry out Bayesian inference in a wide
variety of models commonly used by econometricians. Aimed primarily
at advanced undergraduate and graduate students studying
econometrics, this book may also be useful for students studying
finance, marketing, agricultural economics, business economics or,
more generally, any field which uses statistics. The book also
comes equipped with a supporting website containing all the
relevant data sets and MATLAB computer programs for solving the
computational exercises.
目錄:
Preface
1. The subjective interpretation of probability
2. Bayesian inference
3. Point estimation
4. Frequentist properties of Bayesian estimators
5. Interval estimation
6. Hypothesis testing
7. Prediction
8. Choice of prior
9. Asymptotic Bayes
10. The linear regression model
11. Basics of Bayesian computation
12. Hierarchical models
13. The linear regression model with general covariance
matrix
14. Latent variable models
15. Mixture models
16. Bayesian model averaging and selection
17. Some stationary time series models
18. Some nonstationary time series models
Appendix
Index.