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Bayesian Inference in Dynamic Econometric Models by Jean-Francois Richard, Michel Lubrano, Luc Bauwens (Paperback, 2000)
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About this product
Product Information
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.Product Identifiers
PublisherOxford University Press
ISBN-139780198773139
eBay Product ID (ePID)95213742
Product Key Features
Number of Pages366 Pages
Publication NameBayesian Inference in Dynamic Econometric Models
LanguageEnglish
SubjectEconomics, Computer Science, Mathematics
Publication Year2000
TypeTextbook
AuthorJean-Francois Richard, Michel Lubrano, Luc Bauwens
FormatPaperback
Dimensions
Item Height235 mm
Item Weight536 g
Item Width155 mm
Additional Product Features
Country/Region of ManufactureUnited Kingdom
Title_AuthorLuc Bauwens, Jean-Francois Richard, Michel Lubrano
Series TitleAdvanced Texts in Econometrics
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