Arbeitspapier

Neglected heterogeneity and the algebra of least squares

This paper explores an algebraic relationship between two types of coefficients for a regression with several predictors and an additive binary group variable. In a general regression, the regression coefficients are allowed to be group-specific, the restricted regression imposes constant coefficients. The key result is that the restricted coefficients imposing homogeneity are not necessarily a convex average of the unrestricted coefficients obtained from the more general regression. In the context of treatment effect estimation with several treatment arms and grouplevel controls, this means that the estimated effect of a specific treatment can be non-zero, and statistically significant, even if the estimated unrestricted effects are zero in each group.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 426

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Thema
Ordinary least squares
subsample heterogeneity
variance-weighting
average treatment effect

Ereignis
Geistige Schöpfung
(wer)
Winkelmann, Rainer
Ereignis
Veröffentlichung
(wer)
University of Zurich, Department of Economics
(wo)
Zurich
(wann)
2023

DOI
doi:10.5167/uzh-229123
Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Winkelmann, Rainer
  • University of Zurich, Department of Economics

Entstanden

  • 2023

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