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Instrumental Variables for Binary Treatments with Heterogeneous Treatment Effects: A Simple Exposition

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  • Alan Manning

Abstract

This note provides a simple exposition of what IV can and cannot estimate in a model with abinary treatment variable and heterogeneous treatment effects. It shows how linear IV is amisspecification of functional form and the reason why linear IV estimates for this model willalways depend on the instrument used is because of this misspecification. It shows that if onecan estimate the correct functional form (non-linear IV) then the treatment effects areindependent of the instrument used. However, the data may not be rich enough in practice tobe able to identify these treatment effects without strong distributional assumptions. In thiscase, one will have to settle for estimates of treatment effects that are instrument-dependent.

Suggested Citation

  • Alan Manning, 2004. "Instrumental Variables for Binary Treatments with Heterogeneous Treatment Effects: A Simple Exposition," CEP Discussion Papers dp0619, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp0619
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    References listed on IDEAS

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    1. Angrist, J.D. & Imbens, G.W., 1991. "Sources of Identifying Information in Evaluation Models," Harvard Institute of Economic Research Working Papers 1568, Harvard - Institute of Economic Research.
    2. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    3. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    4. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc.
    5. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
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    Cited by:

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    2. Kondylis, Florence, 2007. "Conflict-induced displacement and labour market outcomes: evidence from post-war Bosnia and Herzegovina," LSE Research Online Documents on Economics 19670, London School of Economics and Political Science, LSE Library.
    3. Rohini Pande & Christopher Udry, 2005. "Institutions and Development:A View from Below," Working Papers 928, Economic Growth Center, Yale University.
    4. Kondylis, Florence, 2010. "Conflict displacement and labor market outcomes in post-war Bosnia and Herzegovina," Journal of Development Economics, Elsevier, vol. 93(2), pages 235-248, November.
    5. Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793.
    6. Alakent, Ekin & Goktan, M. Sinan & Khoury, Theodore A., 2020. "Is venture capital socially responsible? Exploring the imprinting effect of VC funding on CSR practices," Journal of Business Venturing, Elsevier, vol. 35(3).
    7. Dong, Yingying, 2010. "Kept back to get ahead? Kindergarten retention and academic performance," European Economic Review, Elsevier, vol. 54(2), pages 219-236, February.

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    More about this item

    Keywords

    Instrumental Variables; treatment effects; identification;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    NEP fields

    This paper has been announced in the following NEP Reports:

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