Bayesian Inference in Dynamic Econometric Models

Author:   Luc Bauwens ,  etc. ,  Michel Lubrano ,  Jean-Francois Richard (University Professor of Economics, University of Pittsburgh, USA)
Publisher:   Oxford University Press
ISBN:  

9780198773122


Pages:   366
Publication Date:   01 December 1999
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Bayesian Inference in Dynamic Econometric Models


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Full Product Details

Author:   Luc Bauwens ,  etc. ,  Michel Lubrano ,  Jean-Francois Richard (University Professor of Economics, University of Pittsburgh, USA)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Dimensions:   Width: 16.30cm , Height: 2.40cm , Length: 24.20cm
Weight:   0.673kg
ISBN:  

9780198773122


ISBN 10:   0198773129
Pages:   366
Publication Date:   01 December 1999
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Decision Theory and Bayesian Inference ; Chapter 2: Bayesian Statistics and Linear Regression ; Chapter 3: Methods of Numerical Integration ; Chapter 4: Prior Densities for the Regression Model ; Chapter 5: Dynamic Regression Models ; Chapter 6: Bayesian Unit Roots ; Chapter 7: Heteroskedasticity and ARCH ; Chapter 8: Nonlinear Tome Series Models ; Chapter 9: Systems of Equations ; Appendix A: Probability Distributions ; Appendix B: Generating Random Numbers

Reviews

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 applications to parameter estimation 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 applications to parameter estimation * Paul Goodwin, International Journal of Forecasting, 2000 * 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 *


Author Information

Luc Bauwens is currently Professor of Economics at the Universite 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 Facultes 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-Francois Richard is University Professor of Economics at the University of Pittsburgh.

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