Testing for Strong Serial Correlation and Dynamic Conditional Heteroskedasticity in Multiple Regression

P M Robinson

doi:10.1093/oso/9780199257294.003.0009

Testing for Strong Serial Correlation and Dynamic Conditional Heteroskedasticity in Multiple Regression

P M Robinson

https://doi.org/10.1093/oso/9780199257294.003.0009

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Publication Date: Jun 26, 2003

#Testing For Serial Correlation #Dynamic Conditional Heteroskedasticity + Show 8 more

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Abstract

Abstract Most of the many diagnostic tests for serial correlation (SC) and dynamic conditional heteroskedasticity (DCH) of regression disturbances have good asymptotic local power against finite autoregressive (AR) or moving average (MA) alternatives. In testing for SC, statistics typically depend on finitely many, p, least squares (LS) residual sample autocorrelations.

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