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Sharp Bounds On Treatment Effects In A Binary Triangular System

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  • Ismael MOURIFIÉ

Abstract

This paper considers the evaluation of the average treatment e ffect (ATE) in a triangular system with binary dependent variables. I impose a threshold crossing model on both endogenous regressor and the outcome. No parametric functional form or distributional assumptions are imposed. Shaikh and Vytlacil (2011, SV) proposed bounds on ATE which are sharp only under a restrictive condition on the support of the covariates and the instruments, which rules out a wide range of models and many relevant applications. In some cases, when SV's support condition fails, their bounds retrieve the same empirical content as the model with unrestricted endogenous regressor. In this setting, I provide a methodology which allows to construct sharp bounds on the ATE by efficiently using variation on covariates without imposing support restrictions.

Suggested Citation

  • Ismael MOURIFIÉ, 2013. "Sharp Bounds On Treatment Effects In A Binary Triangular System," Working Papers tecipa-498, University of Toronto, Department of Economics.
    • Handle: RePEc:tor:tecipa:tecipa-498
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    Cited by:

    1. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2018. "Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters," Econometrica, Econometric Society, vol. 86(5), pages 1589-1619, September.
    2. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    3. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.
    4. Lina Zhang & David T. Frazier & Don S. Poskitt & Xueyan Zhao, 2020. "Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 34/20, Monash University, Department of Econometrics and Business Statistics.

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    More about this item

    Keywords

    partial identification; threshold crossing model; triangular system; average treatment effect; endogeneity; program social evaluation.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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