TAIL DEPENDENCE OF OLS

Jochem Oorschot and Chen Zhou ()

Econometric Theory, 2022, vol. 38, issue 2, 273-300

Abstract: 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.

Date: 2022
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