Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics) [Paperback]

Luc Bauwens (Author), Michel Lubrano (Author), Jean-Franï¿1/2ois Richard (Author)

Book Description

Publication Date: March 23, 2000 | ISBN-10: 0198773137 | ISBN-13: 978-0198773139

This book offers an up-to-date coverage of the basic principles and tools of Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations , and the long available analytical results of Bayesian inference for linear regression models.

About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

Editorial Reviews

Review

`it can serve as a useful textbook for advanced undergraduate or graduate courses in either time series analysis or econometrics.' Paul Goodwin, International Journal of Forecasting, 2000

`presents a comprehensive review of dynamic econometric models from a Bayesian perspective ... four insightful introductory chapters ... provide a valuable synthesis of current ideas and their application to parameter estimation.' Paul Goodwin, International Journa of Forecasting, 2000

About the Author

Luc Bauwens is currently Professor of Economics at the Universit� catholique de Louvain, where he has been co-director of the Center for Operations Research and Econometrics (CORE) from 1992 to 1998. He has previously been a lecturer at Ecole des Hautes Etudes en Sciences Sociales (EHESS), France, at Facult�s universitaires catholiques de Mons (FUCAM), Belgium, and a consultant at the World Bank, Washington DC. His research interests cover Bayesian inference, time series methods, simulation and numerical methods in econometrics, as well as empirical finance and international trade.

Michel Lubrano is Directeur de Recherche at CNRS, part of GREQAM in Marseille.

Jean-Fran�ois Richard is University Professor of Economics at the University of Pittsburgh.

Product Details

• Paperback: 366 pages
• Publisher: Oxford University Press, USA (March 23, 2000)
• Language: English
• ISBN-10: 0198773137
• ISBN-13: 978-0198773139
• Product Dimensions: 6.1 x 9.2 x 0.8 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #1,033,666 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

24 of 24 people found the following review helpful:

5.0 out of 5 stars another book on econometric time series with a Bayesian approach, February 6, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics) (Hardcover)

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

8 of 8 people found the following review helpful:

4.0 out of 5 stars Excellent introduction to Bayesian Time Series Econometrics, June 17, 2000

By 

Lorenzo Isla - See all my reviews

This review is from: Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics) (Paperback)

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.