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Bayesian 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
(R) 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.
Bayesian 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
(R) 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.
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