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Assessing Sensitivity to Unconfoundedness: Estimation and Inference

Publication ,  Journal Article
Masten, MA; Poirier, A; Zhang, L
Published in: Journal of Business and Economic Statistics
January 1, 2023

This article provides a set of methods for quantifying the robustness of treatment effects estimated using the unconfoundedness assumption. Specifically, we estimate and do inference on bounds for various treatment effect parameters, like the Average Treatment Effect (ATE) and the average effect of treatment on the treated (ATT), under nonparametric relaxations of the unconfoundedness assumption indexed by a scalar sensitivity parameter c. These relaxations allow for limited selection on unobservables, depending on the value of c. For large enough c, these bounds equal the no assumptions bounds. Using a nonstandard bootstrap method, we show how to construct confidence bands for these bound functions which are uniform over all values of c. We illustrate these methods with an empirical application to the National Supported Work Demonstration program. We implement these methods in the companion Stata module tesensitivity for easy use in practice.

Duke Scholars

Published In

Journal of Business and Economic Statistics

DOI

EISSN

1537-2707

ISSN

0735-0015

Publication Date

January 1, 2023

Related Subject Headings

  • Econometrics
  • 15 Commerce, Management, Tourism and Services
  • 14 Economics
  • 01 Mathematical Sciences
 

Citation

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Masten, M. A., Poirier, A., & Zhang, L. (2023). Assessing Sensitivity to Unconfoundedness: Estimation and Inference. Journal of Business and Economic Statistics. https://doi.org/10.1080/07350015.2023.2183212
Masten, M. A., A. Poirier, and L. Zhang. “Assessing Sensitivity to Unconfoundedness: Estimation and Inference.” Journal of Business and Economic Statistics, January 1, 2023. https://doi.org/10.1080/07350015.2023.2183212.
Masten MA, Poirier A, Zhang L. Assessing Sensitivity to Unconfoundedness: Estimation and Inference. Journal of Business and Economic Statistics. 2023 Jan 1;
Masten, M. A., et al. “Assessing Sensitivity to Unconfoundedness: Estimation and Inference.” Journal of Business and Economic Statistics, Jan. 2023. Scopus, doi:10.1080/07350015.2023.2183212.
Masten MA, Poirier A, Zhang L. Assessing Sensitivity to Unconfoundedness: Estimation and Inference. Journal of Business and Economic Statistics. 2023 Jan 1;

Published In

Journal of Business and Economic Statistics

DOI

EISSN

1537-2707

ISSN

0735-0015

Publication Date

January 1, 2023

Related Subject Headings

  • Econometrics
  • 15 Commerce, Management, Tourism and Services
  • 14 Economics
  • 01 Mathematical Sciences