Identifying marginal treatment effects in the presence of sample selection

Otavio Bartalotti, Desire Kedagni and Vitor Possebom

Journal of Econometrics, 2023, vol. 234, issue 2, 565-584

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 et al. (2006) to empirically illustrate the usefulness of our approach.

Keywords: Sample selection; Instrumental variable; Marginal treatment effect; Partial identification; Program evaluation (search for similar items in EconPapers)
JEL-codes: C14 C31 C35 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407621002797
Full text for ScienceDirect subscribers only

Related works:
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 (2021)
Working Paper: Identifying Marginal Treatment Effects in the Presence of Sample Selection (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:234:y:2023:i:2:p:565-584

DOI: 10.1016/j.jeconom.2021.11.011

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().