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

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  • Manning Alan

Abstract

This note provides a simple exposition of what IV can and cannot estimate in a model with binary treatment variable and heterogenous treatment effects. It shows how linear IV is essentially a misspecification of functional form and the reason why linear IV estimates will generally depend on the instrument used is because of this misspecification. It shows that if one can estimate the correct functional form then the treatment effects are independent of the instruments used. However, the data may not be rich enough in practice to be able to identify these treatments effects without strong distributional assumptions. In this case, one will have to settle for estimations of treatment effects that are instrument-dependent.

Suggested Citation

  • Manning Alan, 2004. "Instrumental Variables for Binary Treatments with Heterogenous Treatment Effects: A Simple Exposition," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 3(1), pages 1-12, July.
    • Handle: RePEc:bpj:bejeap:v:contributions.3:y:2004:i:1:n:9
    DOI: 10.2202/1538-0645.1273
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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.
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    3. 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.
    4. Rohini Pande & Christopher Udry, 2005. "Institutions and Development:A View from Below," Working Papers 928, Economic Growth Center, Yale University.
    5. 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).
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    7. 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.
    8. M. Christopher Auld, 2012. "Using Observational Data to Identify the Causal Effects of Health-related Behaviour," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 4, Edward Elgar Publishing.

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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

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