Bayesian Inference in Dynamic Econometric Models by Jeanfranois Richard

Bayesian Inference in Dynamic Econometric Models by Jeanfranois Richard

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Summary

This work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods.

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Bayesian Inference in Dynamic Econometric Models by Jeanfranois Richard

This book contains an up-to-date coverage of the last twenty years advances in 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 (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
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 *
Luc Bauwens is currently Professor of Economics at the Université 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 Facultés 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-François Richard is University Professor of Economics at the University of Pittsburgh.
SKU Unavailable
ISBN 13 9780198773139
ISBN 10 0198773137
Title Bayesian Inference in Dynamic Econometric Models
Author Luc Bauwens
Series Advanced Texts In Econometrics
Condition Unavailable
Binding Type Paperback
Publisher Oxford University Press
Year published 2000-01-06
Number of pages 366
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.