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Contribution Details

Type Working Paper
Scope Discipline-based scholarship
Title Neglected heterogeneity, Simpson’s paradox, and the anatomy of least squares
Organization Unit
Authors
  • Rainer Winkelmann
Language
  • English
Institution University of Zurich
Series Name Working paper series / Department of Economics
Number 426
ISSN 1664-7041
Number of Pages 20
Date 2023
Abstract Text When a sample combines data from two or more groups, multivariate regression yields a matrix-weighted average of the group-specific coefficient vectors. However, it is possible that the weighted average of a specific coefficient falls outside the range of the group-specific coefficients, and it may even have a different sign compared to both group-level coefficients, a manifestation of Simpson's paradox. The result of the combined regression is then prone to misinterpretation. The purpose of this paper is to raise awareness of this problem and to state conditions under which such non-convex weighting or sign reversal can arise, for a model with two regressors and two groups. Two illustrative examples, an investment equation estimated with panel data, and a cross-sectional earnings equation for men and women, highlight the relevance of these findings for applied work.
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Keywords Covariance-weighting, heterogeneity spillover, non-convex average, average treatment effect
Additional Information Revised version ; Former title: Neglected heterogeneity and the algebra of least squares