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

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

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

  • Duflo, Esther & Banerjee, Abhijit & Floretta, John & Schrimpf, Anna & Sankar, Anirudh & Loza, Francine & Kannan, Harini & Jackson, Matthew O. & Chandrasekhar, Arun G. & Shrestha, Maheshwor & Dalpath, , 2021. "Selecting the Most Effective Nudge: Evidence from a Large-Scale Experiment on Immunization," CEPR Discussion Papers 16084, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:16084
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    Keywords

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    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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