Tail dependence of OLS

Jochem Oorschot, Chen Zhou

Research output: Contribution to journalArticleAcademic


This paper shows that if the errors in a multiple regression model are heavy-tailed, the ordinary least squares (OLS) estimators for the regression coefficients are tail-dependent. The tail dependence arises, because the OLS estimators are stochastic linear combinations of heavy-tailed random variables. Moreover, tail dependence also exists between the fitted sum of squares (FSS) and the residual sum of squares (RSS), because they are stochastic quadratic combinations of heavy-tailed random variables.

Original languageEnglish
JournalEconometric Theory
Publication statusPublished - 2 Jul 2021

Bibliographical note

Publisher Copyright:
© The Author(s), 2021. Published by Cambridge University Press.


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