Heteroscedasticity and ARCH
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
Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .