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Heterogeneous Treatment Effects : Instrumental Variables Without Monotonicity?

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  • Klein, T.J.

    (Tilburg University, Center For Economic Research)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Klein, T.J., 2008. "Heterogeneous Treatment Effects : Instrumental Variables Without Monotonicity?," Discussion Paper 2008-45, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:e015611a-6b97-4cd5-8dc8-7818c6c5e39e
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Program evaluation; heterogeneity; identification; dummy endogenous variable; selection on unobservables; instrumental variables; monotonicity; nonseparable index selection model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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