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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, Unit for Economic History.
    • Handle: RePEc:hhs:gunhis:0025
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    References listed on IDEAS

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    1. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    2. 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.
    3. Öberg, Stefan, 2018. "Instrumental variables based on twin births are by definition not valid," Göteborg Papers in Economic History 23, University of Gothenburg, Unit for Economic History.
    4. 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.
    5. Öberg, Stefan, 2018. "Instrumental variables based on twin births are by definition not valid (v.3.0)," SocArXiv zux9s, Center for Open Science.
    6. Guido W. Imbens, 2010. "Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 399-423, June.
    7. Norling, Johannes, 2018. "Measuring heterogeneity in preferences over the sex of children," Journal of Development Economics, Elsevier, vol. 135(C), pages 199-221.
    8. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, Enero-Abr.
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    Cited by:

    1. Hamark, Jesper & Lapidus, John, 2022. "Unions, insurance and changing welfare states: The emergence of obligatory complementary income insurance in Sweden," Göteborg Papers in Economic History 29, University of Gothenburg, Unit for Economic History.
    2. Hamark, Jesper & Turner, Russell, 2021. "Wage distribution within the Swedish State Railways, 1877–1951: Material and methods," Göteborg Papers in Economic History 28, University of Gothenburg, Unit for Economic History.

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    More about this item

    Keywords

    causal inference; natural experiment; local average treatment effect; complier average causal effect; instrumental variable;
    All these keywords.

    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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