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Bayesian Econometric Methods
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This book is a volume in the Econometric Exercises series. It teaches principles of Bayesian econometrics by posing a series of theoretical and applied questions, and providing detailed solutions to those questions. This text is primarily suitable for graduate study in economet- rics, though it can be used for advanced undergraduate courses, and should generate interest from students in related fields, including finance, marketing, agricultural economics, busi- ness economics, and other disciplines that employ statistical methods. The book provides a detailed treatment of a wide array of models commonly employed by economists and statisticians, including linear regression-based models, hierarchical models, latent variable models, mixture models, and time series models. Basics of random variable generation and simulation via Markov Chain Monte Carlo (MCMC) methods are also provided. Finally, posterior simulators for each type of model are rigorously derived, and Matlab computer programs for fitting these models (using both actual and generated data sets) are provided on the Web site accompanying the text
Gary Koop, Dale J. Poirier, and Justin L. Tobias - Personal Name
1st Edtion
13 978-0-511-29482-2
NONE
Bayesian Econometric Methods
Economics
English
Cambridge University Press
2007
New York
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