Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/275662 
Autor:innen: 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
Working Paper No. 426
Versionsangabe: 
Revised version, July 2023
Verlag: 
University of Zurich, Department of Economics, Zurich
Zusammenfassung: 
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.
Schlagwörter: 
Covariance-weighting
heterogeneity spillover
non-convex average
average treatment effect
JEL: 
C21
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
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