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On minimizing the risk of bias in randomized controlled trials in economics

Author

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  • Eble,Alex
  • Boone,Peter
  • Elbourne,Diana

Abstract

Estimation of empirical relationships is prone to bias. Economists have carefully studied sources of bias in structural and quasi-experimental approaches, but the randomized control trial (RCT) has only begun to receive such scrutiny. This paper argues that several lessons from medicine, derived from analysis of thousands of RCTs establishing a clear link between certain practices and biased estimates, can be used to reduce the risk of bias in economics RCTs. It identifies the subset of these lessons applicable to economics and uses them to assess risk of bias in estimates from economics RCTs published between 2001 and 2011. In comparison to medical studies, most economics studies examined do not report important details on study design necessary to assess risk of bias. Many report practices that suggest risk of bias, though this does not necessarily mean bias resulted. The paper concludes with suggestions on how to remedy these issues.

Suggested Citation

  • Eble,Alex & Boone,Peter & Elbourne,Diana, 2016. "On minimizing the risk of bias in randomized controlled trials in economics," Policy Research Working Paper Series 7746, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7746
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    2. Jörg Peters & Jörg Langbein & Gareth Roberts, 2018. "Generalization in the Tropics – Development Policy, Randomized Controlled Trials, and External Validity," World Bank Research Observer, World Bank Group, vol. 33(1), pages 34-64.
    3. Orla Doyle, 2017. "The First 2,000 Days and Child Skills: Evidence from a Randomized Experiment of Home Visiting," Working Papers 201715, School of Economics, University College Dublin.
    4. Pascaline Dupas & Edward Miguel, 2016. "Impacts and Determinants of Health Levels in Low-Income Countries," NBER Working Papers 22235, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Industrial Economics; Economic Growth; Economic Theory&Research;

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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