Identifying treatment effects in the presence of confounded types

Desire Kedagni

Journal of Econometrics, 2023, vol. 234, issue 2, 479-511

Abstract: In this paper, I consider identification of treatment effects when the treatment is endogenous. The use of instrumental variables is a popular solution to deal with endogeneity, but this may give misleading answers when the instrument is invalid. I show that when an (unobserved) instrument is invalid due to correlation with the first stage unobserved heterogeneity, a proxy for the instrument helps partially identify not only the local average treatment effect, but also the entire potential outcomes distributions for compliers. I exploit the fact that the distribution of the observed outcome in each group defined by the treatment and the instrument is a mixture of the distributions of interest. I write the identified set in the form of conditional moment inequalities, and provide an easily implementable inference procedure. Under some tail restrictions, the potential outcomes distributions are point-identified for compliers. Finally, I illustrate my methodology on data from the National Longitudinal Survey of Young Men to estimate returns to college using college proximity as a proxy for the instrument low college cost. I find that a college degree increases the average hourly wage of the compliers by 15%–30%.

Keywords: Potential outcome; Instrumental variable; LATE; Compliers; Mixture models (search for similar items in EconPapers)
JEL-codes: C14 C21 C25 C26 (search for similar items in EconPapers)
Date: 2023
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Related works:
Working Paper: Identifying treatment effects in the presence of confounded types (2021)
Working Paper: Identifying Treatment Effects in the Presence of Confounded Types (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:234:y:2023:i:2:p:479-511

DOI: 10.1016/j.jeconom.2021.01.012

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