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Assessing external validity

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  • Bo, Hao
  • Galiani, Sebastian

Abstract

In designing any causal study, steps must be taken to address both internal and external threats to its validity. Researchers tend to focus primarily on dealing with threats to internal validity. However, once they have conducted an internally valid analysis, that analysis yields an established set of findings for the specific case in question. As for the future usefulness of that result, however, what matters is its degree of external validity. In this paper we provide a formal, general exploration of the question of external validity and propose a simple and generally applicable method for evaluating the external validity of randomized controlled trials. Although our method applies only to RCTs, the issue of external validity is general and not restricted to RCTs, as shown in our formal analysis.

Suggested Citation

  • Bo, Hao & Galiani, Sebastian, 2021. "Assessing external validity," Research in Economics, Elsevier, vol. 75(3), pages 274-285.
  • Handle: RePEc:eee:reecon:v:75:y:2021:i:3:p:274-285
    DOI: 10.1016/j.rie.2021.06.005
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    1. Charles F. Manski, 2013. "Response to the Review of ‘Public Policy in an Uncertain World’," Economic Journal, Royal Economic Society, vol. 0, pages 412-415, August.
    2. Angus Deaton, 2010. "Instruments, Randomization, and Learning about Development," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 424-455, June.
    3. Cruces, Guillermo & Galiani, Sebastian, 2007. "Fertility and female labor supply in Latin America: New causal evidence," Labour Economics, Elsevier, vol. 14(3), pages 565-573, June.
    4. Marinho Bertanha & Guido W. Imbens, 2020. "External Validity in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 593-612, July.
    5. Galiani, Sebastián & Gertler, Paul J. & Undurraga, Raimundo & Cooper, Ryan & Martínez, Sebastián & Ross, Adam, 2017. "Shelter from the storm: Upgrading housing infrastructure in Latin American slums," Journal of Urban Economics, Elsevier, vol. 98(C), pages 187-213.
    6. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    7. Wolpin, Kenneth I., 2013. "The Limits of Inference without Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262019086, December.
    8. Rosenbaum, Paul R., 2010. "Design Sensitivity and Efficiency in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 692-702.
    9. Yingying Dong & Arthur Lewbel, 2015. "Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 1081-1092, December.
    10. 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.
    11. Rachael Meager, 2019. "Understanding the Average Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of Seven Randomized Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 11(1), pages 57-91, January.
    12. Paul Gertler & Manisha Shah & Maria Laura Alzua & Lisa Cameron & Sebastian Martinez & Sumeet Patil, 2015. "How Does Health Promotion Work? Evidence From The Dirty Business of Eliminating Open Defecation," NBER Working Papers 20997, National Bureau of Economic Research, Inc.
    13. Abhijit Banerjee & Dean Karlan & Jonathan Zinman, 2015. "Six Randomized Evaluations of Microcredit: Introduction and Further Steps," American Economic Journal: Applied Economics, American Economic Association, vol. 7(1), pages 1-21, January.
    14. 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.
    15. Manski, Charles F., 2013. "Public Policy in an Uncertain World: Analysis and Decisions," Economics Books, Harvard University Press, number 9780674066892, Spring.
    16. Joshua D. Angrist & Miikka Rokkanen, 2015. "Wanna Get Away? Regression Discontinuity Estimation of Exam School Effects Away From the Cutoff," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1331-1344, December.
    17. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    18. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.
    19. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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    Cited by:

    1. Azzam, Tarek & Bates, Michael D. & Fairris, David, 2022. "Do learning communities increase first year college retention? Evidence from a randomized control trial," Economics of Education Review, Elsevier, vol. 89(C).
    2. Matthias Thiemann, 2021. "La relation asymétrique des banques centrales au financement de marché : une évaluation des implications pour la stabilité financière à la lumière des évènements lés à la Covid," Post-Print hal-03622943, HAL.
    3. Bando, Rosangela & Galiani, Sebastian & Gertler, Paul, 2022. "Another brick on the wall: On the effects of non-contributory pensions on material and subjective well being," Journal of Economic Behavior & Organization, Elsevier, vol. 195(C), pages 16-26.
    4. Annie Duflo & Jessica Kiessel & Adrienne Lucas, 2020. "Experimental Evidence on Alternative Policies to Increase Learning at Scale," NBER Working Papers 27298, National Bureau of Economic Research, Inc.
    5. Antoine Deeb & Cl'ement de Chaisemartin, 2019. "Clustering and External Validity in Randomized Controlled Trials," Papers 1912.01052, arXiv.org, revised Dec 2022.
    6. Matthias Thiemann, 2021. "La relation asymétrique des banques centrales au financement de marché : une évaluation des implications pour la stabilité financière à la lumière des évènements lés à la Covid," SciencePo Working papers Main hal-03622943, HAL.

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    More about this item

    Keywords

    Internal validity; External validity; Randomized controlled trials;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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