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Bayesian econometric methods

Joshua Chi Chun Chan (Author), Gary Koop (Author), Dale J. Poirier (Author), Justin L. Tobias (Author)
"The past two decades have seen econometrics grow into a vast discipline. Many different branches of the subject now happily coexist with one another. These branches interweave econometric theory and empirical applications and bring econometric method to bear on a myriad of economic issues"-- Provided by publisher
Print Book, English, 2020
Second Edition View all formats and editions
Cambridge University Press, Cambridge, United Kingdom, 2020
xxiii, 466 pages : illustrations ; 26 cm.
9781108423380, 9781108437493, 1108423388, 1108437494
ebook version :
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 random variate generation and posterior simulation; 12. Posterior simulation via Markov chain Monte Carlo; 13. Hierarchical models; 14. Latent variable models; 15. Mixture models; 16. Bayesian methods for model comparison, selection and big data; 17. Univariate time series methods; 18. State space and unobserved components models; 19. Time series models for volatility; 20. Multivariate time series methods; Appendix; Bibliography; Index.
Revised edition of Bayesian econometric methods, 2007