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What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?

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  • Andrew Chesher
  • Adam M. Rosen

Abstract

We compare nonparametric instrumental variables (IV) models with linear models and 2SLS methods when dependent variables are discrete. A 2SLS method can deliver a consistent estimator of a Local Average Treatment Effect but is not informative about other treatment effect parameters. The IV models set identify a range of interesting structural and treatment effect parameters. We give set identification results for a counterfactual probability and an Average Treatment Effect in a IV binary threshold crossing model. We illustrate using data on female employment and family size (employed by Joshua Angrist and William Evans (1998)) and compare with their LATE estimates.

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  • Andrew Chesher & Adam M. Rosen, 2013. "What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?," American Economic Review, American Economic Association, vol. 103(3), pages 557-562, May.
    • Handle: RePEc:aea:aecrev:v:103:y:2013:i:3:p:557-62
    Note: DOI: 10.1257/aer.103.3.557
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    References listed on IDEAS

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    1. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, September.
    2. Arthur Lewbel & Yingying Dong & Thomas Tao Yang, 2012. "Comparing features of convenient estimators for binary choice models with endogenous regressors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(3), pages 809-829, August.
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    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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