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A Random Shock Is Not Random Assignment

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  • Christoph Engel

    (Max Planck Institute for Research on Collective Goods)

Abstract

A random shock excludes reverse causality and reduces omitted variable bias. Yet a natural experiment does not identify random exposure to treatment, but the reaction to a random change from baseline to treatment. A lab experiment comparing higher certainty with higher severity of punishment for stealing (holding the expected value of the intervention constant) shows that the difference between the effects of a random shock and random assignment can be pronounced.

Suggested Citation

  • Christoph Engel, 2016. "A Random Shock Is Not Random Assignment," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2016_09, Max Planck Institute for Research on Collective Goods.
    • Handle: RePEc:mpg:wpaper:2016_09
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    References listed on IDEAS

    as
    1. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    2. Christoph Engel & Peter G. Moffatt, 2014. "dhreg, xtdhreg, and bootdhreg: Commands to implement double-hurdle regression," Stata Journal, StataCorp LP, vol. 14(4), pages 778-797, December.
    3. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-161, April.
    4. Charness, Gary, 2000. "Self-Serving Cheap Talk: A Test Of Aumann's Conjecture," Games and Economic Behavior, Elsevier, vol. 33(2), pages 177-194, November.
    5. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    6. Sekhon, Jasjeet S. & Titiunik, Rocã O, 2012. "When Natural Experiments Are Neither Natural nor Experiments," American Political Science Review, Cambridge University Press, vol. 106(1), pages 35-57, February.
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    Citations

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    Cited by:

    1. Christoph Engel, 2018. "Empirical Methods for the Law," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 174(1), pages 5-23, March.
    2. Christoph Engel & Keren Weinshall, 2020. "Manna from Heaven for Judges: Judges’ Reaction to a Quasi‐Random Reduction in Caseload," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(4), pages 722-751, December.
    3. Natalie Nitsche & Ansgar Hudde, 2022. "Countries embracing maternal employment opened schools sooner after Covid-19 lockdowns," MPIDR Working Papers WP-2022-008, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. Barati, Mehdi & Adams, Scott, 2019. "Enhanced penalties for carrying firearms illegally and their effects on crime," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 207-219.

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    More about this item

    Keywords

    identification; random exposure; random shock; natural experiment; certainty and severity of punishment;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law

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