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Selecting the Most Effective Nudge: Evidence from a Large-Scale Experiment on Immunization

Author

Listed:
  • Abhijit Banerjee
  • Arun G. Chandrasekhar
  • Suresh Dalpath
  • Esther Duflo
  • John Floretta
  • Matthew O. Jackson
  • Harini Kannan
  • Francine N. Loza
  • Anirudh Sankar
  • Anna Schrimpf
  • Maheshwor Shrestha

Abstract

We evaluate a large-scale set of interventions to increase demand for immunization in Haryana, India. The policies under consideration include the two most frequently discussed tools—reminders and incentives—as well as an intervention inspired by the networks literature. We cross-randomize whether (a) individuals receive SMS reminders about upcoming vaccination drives; (b) individuals receive incentives for vaccinating their children; (c) influential individuals (information hubs, trusted individuals, or both) are asked to act as “ambassadors” receiving regular reminders to spread the word about immunization in their community. By taking into account different versions (or “dosages”) of each intervention, we obtain 75 unique policy combinations. We develop a new statistical technique—a smart pooling and pruning procedure—for finding a best policy from a large set, which also determines which policies are effective and the effect of the best policy. We proceed in two steps. First, we use a LASSO technique to collapse the data: we pool dosages of the same treatment if the data cannot reject that they had the same impact, and prune policies deemed ineffective. Second, using the remaining (pooled) policies, we estimate the effect of the best policy, accounting for the winner’s curse. The key outcomes are (i) the number of measles immunizations and (ii) the number of immunizations per dollar spent. The policy that has the largest impact (information hubs, SMS reminders, incentives that increase with each immunization) increases the number of immunizations by 44 % relative to the status quo. The most cost-effective policy (information hubs, SMS reminders, no incentives) increases the number of immunizations per dollar by 9.1%.

Suggested Citation

  • Abhijit Banerjee & Arun G. Chandrasekhar & Suresh Dalpath & Esther Duflo & John Floretta & Matthew O. Jackson & Harini Kannan & Francine N. Loza & Anirudh Sankar & Anna Schrimpf & Maheshwor Shrestha, 2021. "Selecting the Most Effective Nudge: Evidence from a Large-Scale Experiment on Immunization," NBER Working Papers 28726, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:28726
    Note: CH DAE DEV EH LS PE POL
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    1. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    Cited by:

    1. Raman Kachurka & Michał W. Krawczyk & Joanna Rachubik, 2021. "Persuasive messages will not raise COVID-19 vaccine acceptance. Evidence from a nation-wide online experiment," Working Papers 2021-07, Faculty of Economic Sciences, University of Warsaw.
    2. Amaral, Sofia & Dinarte-Diaz, Lelys & Dominguez, Patricio & Perez-Vincent, Santiago M., 2024. "Helping families help themselves: The (Un)intended impacts of a digital parenting program," Journal of Development Economics, Elsevier, vol. 166(C).
    3. Belmonte, A & Pickard, H, 2022. "Safe at Last? LATE Effects of a Mass Immunization Campaign on Households’ Economic Insecurity," CAGE Online Working Paper Series 604, Competitive Advantage in the Global Economy (CAGE).
    4. Athey, Susan & Bergstrom, Katy & Hadad, Vitor & Jamison, Julian C. & Ozler, Berk & Parisotto, Luca & Sama, Julius Dohbit, 2021. "Shared Decision-Making: Can Improved Counseling Increase Willingness to Pay for Modern Contraceptives?," Research Papers 3987, Stanford University, Graduate School of Business.
    5. Ahmed Mushfiq Mobarak & Edward Miguel, 2022. "The Economics of the COVID-19 Pandemic in Poor Countries," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 253-285, August.
    6. Derksen, Laura & Kerwin, Jason Theodore & Reynoso, Natalia Ordaz & Sterck, Olivier, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," SocArXiv y8gh7, Center for Open Science.
    7. Bahety, Girija & Bauhoff, Sebastian & Patel, Dev & Potter, James, 2021. "Texts don’t nudge: An adaptive trial to prevent the spread of COVID-19 in India," Journal of Development Economics, Elsevier, vol. 153(C).
    8. Charlotte Pelras & Andrea Renk, 2021. "Sterilizations and immunization in India: The Emergency experience (1975-1977)," DeFiPP Working Papers 2105, University of Namur, Development Finance and Public Policies.
    9. Maria Nareklishvili & Nicholas Polson & Vadim Sokolov, 2022. "Feature Selection for Personalized Policy Analysis," Papers 2301.00251, arXiv.org, revised Jul 2023.
    10. Bussolo, Maurizio & Sarma, Nayantara & Torre, Iván, 2023. "The links between COVID-19 vaccine acceptance and non-pharmaceutical interventions," Social Science & Medicine, Elsevier, vol. 320(C).
    11. Mylène Lagarde & Carlos Riumallo Herl, 2023. "Stronger together: Group incentives and the demand for prevention," Tinbergen Institute Discussion Papers 23-0010/V, Tinbergen Institute.
    12. Charlotte Pelras & Andrea Renk, 2022. "When Sterilizations Lower Immunizations: The Emergency Experience in India (1975-77)," DeFiPP Working Papers 2206, University of Namur, Development Finance and Public Policies.

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    More about this item

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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