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Too LATE for Natural Experiments: A Critique of Local Average Treatment Effects Using the Example of Angrist and Evans (1998)

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  • Öberg, Stefan

    () (Department of Economic History, School of Business, Economics and Law, Göteborg University)

Abstract

There has been a fundamental flaw in the conceptual design of many natural experiments used in the economics literature, particularly among studies aiming to estimate a local average treatment effect (LATE). When we use an instrumental variable (IV) to estimate a LATE, the IV only has an indirect effect on the treatment of interest. Such IVs do not work as intended and will produce severely biased and/or uninterpretable results. This comment demonstrates that the LATE does not work as previously thought and explains why using the natural experiment proposed by Angrist and Evans (1998) as the example.

Suggested Citation

  • Öberg, Stefan, 2019. "Too LATE for Natural Experiments: A Critique of Local Average Treatment Effects Using the Example of Angrist and Evans (1998)," Göteborg Papers in Economic History 25, University of Gothenburg, Department of Economic History.
    • Handle: RePEc:hhs:gunhis:0025
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    References listed on IDEAS

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    1. Åslund, Olof & Grönqvist, Hans, 2010. "Family size and child outcomes: Is there really no trade-off?," Labour Economics, Elsevier, vol. 17(1), pages 130-139, January.
    2. Rosenzweig, Mark R & Wolpin, Kenneth I, 1980. "Testing the Quantity-Quality Fertility Model: The Use of Twins as a Natural Experiment," Econometrica, Econometric Society, vol. 48(1), pages 227-240, January.
    3. Norling, Johannes, 2018. "Measuring heterogeneity in preferences over the sex of children," Journal of Development Economics, Elsevier, vol. 135(C), pages 199-221.
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    More about this item

    Keywords

    causal inference; natural experiment; local average treatment effect; complier average causal effect; instrumental variable;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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