Bounding Sets for Treatment Effects with Proportional Selection

Authors

Deepankar Basu, Department of Economics, UMass AmherstFollow

Working Paper Number

2021-10

Publication Date

2021

Abstract

In linear econometric models with proportional selection on unobservables, omitted variable bias in estimated treatment effects are roots of a cubic equation involving estimated parameters from a short and intermediate regression, the former excluding and the latter including all observable controls. The roots of the cubic are functions of δ, the degree of proportional selection on unobservables, and R_max, the R-squared in a hypothetical long regression that includes the unobservable confounder and all observable controls. In this paper a simple method is proposed to compute roots of the cubic over meaningful regions of the δ-R_max plane and use the roots to construct bounding sets for the true treatment effect. The proposed method is illustrated with both a simulated and an observational data set.

DOI

https://doi.org/10.7275/22680948

License

UMass Amherst Open Access Policy

Recommended Citation

Basu, Deepankar, "Bounding Sets for Treatment Effects with Proportional Selection" (2021). Economics Department Working Paper Series. 307.
https://doi.org/10.7275/22680948