Identifying Marginal Treatment Effects in the Presence of Sample Selection

Otavio Bartalotti, Desire Kedagni and Vitor Possebom

No 14428, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This article presents identification results for the marginal treatment effect (MTE) when there is sample selection. We show that the MTE is partially identified for individuals who are always observed regardless of treatment, and derive uniformly sharp bounds on this parameter under three increasingly restrictive sets of assumptions. The first result imposes standard MTE assumptions with an unrestricted sample selection mechanism. The second set of conditions imposes monotonicity of the sample selection variable with respect to treatment, considerably shrinking the identified set. Finally, we incorporate a stochastic dominance assumption which tightens the lower bound for the MTE. Our analysis extends to discrete instruments. The results rely on a mixture reformulation of the problem where the mixture weights are identified, extending Lee's (2009) trimming procedure to the MTE context. We propose estimators for the bounds derived and use data made available by Deb, Munkin, and Trivedi (2006) to empirically illustrate the usefulness of our approach.

Keywords: sample selection; instrumental variable; marginal treatment eect; partial identication; principal stratication; program evaluation; mixture models (search for similar items in EconPapers)
JEL-codes: C14 C31 C35 (search for similar items in EconPapers)
Pages: 94 pages
Date: 2021-05
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Identifying marginal treatment effects in the presence of sample selection (2023)
Working Paper: Identifying Marginal Treatment Effects in the Presence of Sample Selection (2021)
Working Paper: Identifying Marginal Treatment Effects in the Presence of Sample Selection (2019)
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