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.
Original language | English |
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Pages (from-to) | 273-300 |
Number of pages | 28 |
Journal | Econometric Theory |
Volume | 38 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2 Jul 2021 |
Bibliographical note
Publisher Copyright:© The Author(s), 2021. Published by Cambridge University Press.