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Take-up and Targeting: Experimental Evidence from SNAP

Author

Listed:
  • Finkelstein, Amy

    (MIT)

  • Notowidigdo, Matthew J.

    (Northwestern University)

Abstract

This paper develops a framework for evaluating the welfare impact of various interventions designed to increase take-up of social safety net programs in the presence of potential behavioral biases. We calibrate the key parameters using a randomized field experiment in which 30,000 elderly individuals not enrolled in – but likely eligible for – the Supplemental Nutrition Assistance Program (SNAP) are either provided with information that they are likely eligible, provided with this information and also offered assistance in applying, or are in a "status quo" control group. Only 6 percent of the control group enrolls in SNAP over the next 9 months, compared to 11 percent of the Information Only group and 18 percent of the Information Plus Assistance group. The individuals who apply or enroll in response to either intervention receive lower benefits and are less sick than the average enrollee in the control group. The results are consistent with the existence of optimization frictions that are greater for needier individuals, suggesting that the poor targeting properties of the interventions reduce their welfare gains.

Suggested Citation

  • Finkelstein, Amy & Notowidigdo, Matthew J., 2018. "Take-up and Targeting: Experimental Evidence from SNAP," IZA Discussion Papers 11558, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp11558
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    References listed on IDEAS

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    1. Rossin-Slater, Maya, 2013. "WIC in your neighborhood: New evidence on the impacts of geographic access to clinics," Journal of Public Economics, Elsevier, vol. 102(C), pages 51-69.
    2. Johannes Spinnewijn, 2015. "Unemployed But Optimistic: Optimal Insurance Design With Biased Beliefs," Journal of the European Economic Association, European Economic Association, vol. 13(1), pages 130-167, February.
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    Cited by:

    1. Friedrichsen, Jana & König, Tobias & Schmacker, Renke, 2018. "Social image concerns and welfare take-up," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 168, pages 174-192.
    2. Altmann, Steffen & Grunewald, Andreas & Radbruch, Jonas, 2019. "Passive Choices and Cognitive Spillovers," IZA Discussion Papers 12337, Institute of Labor Economics (IZA).
    3. Mason, Richard, 2019. "Digital enrollment architecture and retirement savings decisions: Evidence from the field," Other publications TiSEM 58639618-e34e-4b5c-8c8c-a, Tilburg University, School of Economics and Management.
    4. Böckerman, Petri & Kortelainen, Mika & Laine, Liisa T. & Nurminen, Mikko & Saxell, Tanja, 2019. "Digital Waste? Unintended Consequences of Health Information Technology," Working Papers 117, VATT Institute for Economic Research.
    5. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    6. Ethan M. J. Lieber & Lee M. Lockwood, 2019. "Targeting with In-Kind Transfers: Evidence from Medicaid Home Care," American Economic Review, American Economic Association, vol. 109(4), pages 1461-1485, April.
    7. Emanuel, Natalia & Ho, Helen, 2020. "Behavioral Biases and Legal Compliance: A Field Experiment," SocArXiv ztnmf, Center for Open Science.

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    More about this item

    Keywords

    SNAP; food stamps; take-up; targeting; welfare;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • 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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