Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics)
Author: Luc Bauwens, Michel Lubrano, Jean-Francois Richard, Michele Lubrano
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ISBN: 0198773137
Publisher: Oxford Univ Pr on Demand (April, 2000)
Sales Rank: 302,023
Average Customer Rating: 4 out of 5
Customer Reviews
Rating: 4 out of 5
advanced text, good coverage, unique Bayesian perspective
This is a modern advanced text on econometrics emphasizing dynamic models including the ARCH/GARCH models that have practical application in finance. What makes it a little different than most texts is the Bayesian approach. The authors include coverage of MCMC methods which make the Bayesian approach more realistic. This book provides a very modern treatment of econometrics
Rating: 4 out of 5
Excellent introduction to Bayesian Time Series Econometrics
This is an outstanding introduction to the application of Bayesian statistics to the problems encountered in macroeconomics and finance. Bayesian inference it's becoming a critical tool for researchers and practitioners with an interest in empirical ecnomics and to date this is the first book on Bayesian time series econometrics. The sections on nonlinearities and on numerical integration are especially valuable. Having the book it is a must for researchers and professionals interested in modeling and forecasting the state of economy and financial markets. Similar Products
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