Identifying treatment effects in the presence of confounded types

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Journal of Econometrics




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 the instrument is invalid due to correlation with the first stage unobserved heterogeneity, a second (also possibly invalid) instrument allows to 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 (testable) 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 (potential) instrument. I find that a college degree increases the average hourly wage of the compliers by 38-79%.

JEL Classification

C14, C21, C25, C26


This is a working paper of an article published as Kédagni, Désiré. "Identifying treatment effects in the presence of confounded types." Journal of Econometrics (2021). doi:10.1016/j.jeconom.2021.01.012. Posted with permission.

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Elsevier B.V.



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