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RCTs to Scale: Comprehensive Evidence From Two Nudge Units

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  • Stefano DellaVigna
  • Elizabeth Linos

Abstract

Nudge interventions have quickly expanded from academic studies to larger implementation in so‐called Nudge Units in governments. This provides an opportunity to compare interventions in research studies, versus at scale. We assemble a unique data set of 126 RCTs covering 23 million individuals, including all trials run by two of the largest Nudge Units in the United States. We compare these trials to a sample of nudge trials in academic journals from two recent meta‐analyses. In the Academic Journals papers, the average impact of a nudge is very large—an 8.7 percentage point take‐up effect, which is a 33.4% increase over the average control. In the Nudge Units sample, the average impact is still sizable and highly statistically significant, but smaller at 1.4 percentage points, an 8.0% increase. We document three dimensions which can account for the difference between these two estimates: (i) statistical power of the trials; (ii) characteristics of the interventions, such as topic area and behavioral channel; and (iii) selective publication. A meta‐analysis model incorporating these dimensions indicates that selective publication in the Academic Journals sample, exacerbated by low statistical power, explains about 70 percent of the difference in effect sizes between the two samples. Different nudge characteristics account for most of the residual difference.

Suggested Citation

  • Stefano DellaVigna & Elizabeth Linos, 2022. "RCTs to Scale: Comprehensive Evidence From Two Nudge Units," Econometrica, Econometric Society, vol. 90(1), pages 81-116, January.
  • Handle: RePEc:wly:emetrp:v:90:y:2022:i:1:p:81-116
    DOI: 10.3982/ECTA18709
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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. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    3. Stefano DellaVigna & Devin Pope, 2018. "What Motivates Effort? Evidence and Expert Forecasts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 1029-1069.
    4. David Card & Jochen Kluve & Andrea Weber, 2018. "What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations," Journal of the European Economic Association, European Economic Association, vol. 16(3), pages 894-931.
    5. Eva Vivalt, 2020. "How Much Can We Generalize From Impact Evaluations?," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3045-3089.
    6. 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.
    7. Bold, Tessa & Kimenyi, Mwangi & Mwabu, Germano & Ng’ang’a, Alice & Sandefur, Justin, 2018. "Experimental evidence on scaling up education reforms in Kenya," Journal of Public Economics, Elsevier, vol. 168(C), pages 1-20.
    8. Karthik Muralidharan & Paul Niehaus, 2017. "Experimentation at Scale," Journal of Economic Perspectives, American Economic Association, vol. 31(4), pages 103-124, Fall.
    9. Hunt Allcott, 2015. "Site Selection Bias in Program Evaluation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(3), pages 1117-1165.
    10. Abhijit V. Banerjee & Esther Duflo, 2009. "The Experimental Approach to Development Economics," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 151-178, May.
    11. Eva Vivalt, 0. "How Much Can We Generalize From Impact Evaluations?," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3045-3089.
    12. Hallsworth, Michael & List, John A. & Metcalfe, Robert D. & Vlaev, Ivo, 2017. "The behavioralist as tax collector: Using natural field experiments to enhance tax compliance," Journal of Public Economics, Elsevier, vol. 148(C), pages 14-31.
    13. Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, vol. 110(11), pages 3634-3660, November.
    14. Isaiah Andrews & Maximilian Kasy, 2019. "Identification of and Correction for Publication Bias," American Economic Review, American Economic Association, vol. 109(8), pages 2766-2794, August.
    15. Hummel, Dennis & Maedche, Alexander, 2019. "How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 80(C), pages 47-58.
    16. Jachimowicz, Jon M. & Duncan, Shannon & Weber, Elke U. & Johnson, Eric J., 2019. "When and why defaults influence decisions: a meta-analysis of default effects," Behavioural Public Policy, Cambridge University Press, vol. 3(2), pages 159-186, November.
    17. Erin Todd Bronchetti & Thomas S. Dee & David B. Hufman & Ellen Magenheim, 2013. "When a Nudge Isn’t Enough: Defaults and Saving Among Low-Income Tax Filers," National Tax Journal, National Tax Association;National Tax Journal, vol. 66(3), pages 609-634, September.
    18. 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.
    19. 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.
    20. Saurabh Bhargava & Dayanand Manoli, 2015. "Psychological Frictions and the Incomplete Take-Up of Social Benefits: Evidence from an IRS Field Experiment," American Economic Review, American Economic Association, vol. 105(11), pages 3489-3529, November.
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    More about this item

    JEL classification:

    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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