000			02755nam a22002537a 4500
999			_c2982 _d2982
005			20220715131437.0
008			220715b ||||| |||| 00| 0 eng d
020			_a9781108437493
082			_a330.01519542 _bCHA
100			_aChan, Joshua _97521
245			_aBayesian econometric methods
250			_a2nd
260			_bCambridge University Press _aNew York _c2020
300			_axxiii, 466 p.
365			_aGBP _b44.99
504			_aTable of Contents 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.
520			_aBayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying statistics, finance, marketing, and agricultural economics. Offers an update to the first edition by adding extensive coverage of macroeconomic models Provides additional exercises to aid researchers new to MCMC with understanding the methods MATLAB® computer programs are included on the website accompanying the text
650			_aBayesian statistical decision theory _91505
650			_aEconometrics _9845
700			_aKoop, Gary _97522
700			_aPoirier, , Dale J. _97523
700			_aTobias, Justin L. _97524
942			_2ddc _cBK