Heterogeneous treatment effects: Instrumental variables without monotonicity?

Tobias Klein

Journal of Econometrics, 2010, vol. 155, issue 2, 99-116

Abstract: Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify a local average treatment effect parameter using instrumental variables. More recently, Heckman and Vytlacil (1999) suggested the estimation of a variety of treatment effect parameters using a local version of their approach. We investigate the sensitivity of the respective estimates to random departures from monotonicity. Approximations to the respective bias terms are derived. In an empirical application the bias is calculated and bias corrected estimates are obtained. The accuracy of the approximation is investigated in a Monte Carlo study.

Keywords: Program; evaluation; Heterogeneity; Identification; Dummy; endogenous; variable; Selection; on; unobservables; Instrumental; variables; Monotonicity; Nonseparable; index; selection; model (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (39)

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Related works:
Working Paper: Heterogeneous Treatment Effects: Instrumental Variables without Monotonicity? (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:155:y:2010:i:2:p:99-116

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