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Instrumental variables for binary treatments with heterogeneous 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 a binary treatment variable and heterogeneous treatment effects. It shows how linear IV is a misspecification of functional form and the reason why linear IV estimates for this model will always depend on the instrument used is because of this misspecification. It shows that if one can estimate the correct functional form (non-linear IV) then the treatment effects are independent of the instrument used. However, the data may not be rich enough in practice to be able to identify these treatment effects without strong distributional assumptions. In this case, one will have to settle for estimates of treatment effects that are instrument-dependent.

Suggested Citation

  • Manning, Alan, 2004. "Instrumental variables for binary treatments with heterogeneous treatment effects: a simple exposition," LSE Research Online Documents on Economics 19983, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:19983
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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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    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. 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.
    4. Pande, Rohini & Udry, Christopher R., 2005. "Institutions and Development: A View from Below," Center Discussion Papers 28468, Yale University, Economic Growth Center.
    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. 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.
    8. 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

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