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.
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