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A simple approximation for evaluating external validity bias

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  • Andrews, Isaiah
  • Oster, Emily

Abstract

We develop a simple approximation that relates the total external validity bias in randomized trials to (i) bias from selection on observables and (ii) a measure for the role of treatment effect heterogeneity in driving selection into the experimental sample.

Suggested Citation

  • Andrews, Isaiah & Oster, Emily, 2019. "A simple approximation for evaluating external validity bias," Economics Letters, Elsevier, vol. 178(C), pages 58-62.
    • Handle: RePEc:eee:ecolet:v:178:y:2019:i:c:p:58-62
    DOI: 10.1016/j.econlet.2019.02.020
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    References listed on IDEAS

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    1. Rajeev Dehejia & Cristian Pop-Eleches & Cyrus Samii, 2021. "From Local to Global: External Validity in a Fertility Natural Experiment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 217-243, January.
    2. Robert B. Olsen & Larry L. Orr & Stephen H. Bell & Elizabeth A. Stuart, 2013. "External Validity in Policy Evaluations That Choose Sites Purposively," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 32(1), pages 107-121, January.
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    13. Meager, Rachael, 2019. "Understanding the average impact of microcredit expansions: a Bayesian hierarchical analysis of seven randomized experiments," LSE Research Online Documents on Economics 88190, London School of Economics and Political Science, LSE Library.
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    Cited by:

    1. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing Attrition Bias in Field Experiments," Working Papers 202218, University of California at Riverside, Department of Economics, revised Oct 2022.
    2. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2021. "The Effect of Social Media on Elections: Evidence from the United States," NBER Working Papers 28849, National Bureau of Economic Research, Inc.
    3. Takuya Ishihara & Toru Kitagawa, 2021. "Evidence Aggregation for Treatment Choice," Papers 2108.06473, arXiv.org.
    4. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2021. "The Effect of Social Media on Elections: Evidence from the United States," NBER Working Papers 28849, National Bureau of Economic Research, Inc.
    5. Colnet Bénédicte & Josse Julie & Varoquaux Gaël & Scornet Erwan, 2022. "Causal effect on a target population: A sensitivity analysis to handle missing covariates," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 372-414, January.
    6. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 202010, University of California at Riverside, Department of Economics, revised Mar 2020.
    7. Sebastian Gallegos & Pablo Celhay, 2020. "Early Skill Effects on Types of Parental Investments and Long-Run Outcomes," Working Papers 2020-014, Human Capital and Economic Opportunity Working Group.
    8. Susan Athey & Raj Chetty & Guido W. Imbens & Hyunseung Kang, 2019. "The Surrogate Index: Combining Short-Term Proxies to Estimate Long-Term Treatment Effects More Rapidly and Precisely," NBER Working Papers 26463, National Bureau of Economic Research, Inc.
    9. Daido Kido, 2022. "Distributionally Robust Policy Learning with Wasserstein Distance," Papers 2205.04637, arXiv.org, revised Aug 2022.
    10. Naoki Egami & Erin Hartman, 2021. "Covariate selection for generalizing experimental results: Application to a large‐scale development program in Uganda," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1524-1548, October.

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    More about this item

    Keywords

    External validity; Randomized trials;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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