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Bayesian Inference in Dynamic Econometric Models$
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Luc Bauwens, Michel Lubrano, and Jean-François Richard

Print publication date: 2000

Print ISBN-13: 9780198773122

Published to Oxford Scholarship Online: September 2011

DOI: 10.1093/acprof:oso/9780198773122.001.0001

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Heteroscedasticity and ARCH

Heteroscedasticity and ARCH

(p.197) 7 Heteroscedasticity and ARCH
Bayesian Inference in Dynamic Econometric Models

Luc Bauwens

Michel Lubrano

Jean-François Richard

Oxford University Press

This chapter examines the importance of heteroscedasticity and the autoregressive conditional heteroscedasticity (ARCH) model in econometric analysis, particularly in the Bayesian inference approach. It discusses the case of functional heteroscedasticity and proposes a general method for detecting heteroscedasticity. It explains that neglecting heteroscedasticity may result in a posterior distribution for the regression coefficients which is different from what it is when the heteroscedasticity is taken into account.

Keywords:   heteroscedasticity, ARCH model, econometric analysis, Bayesian inference, regression coefficients

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