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Neighborhood networks and program participation

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  • Grossman, Daniel
  • Khalil, Umair

Abstract

We investigate whether social interactions among pregnant women can lead to increased Medicaid participation within this population. Using geographically fine vital statistics data, we exploit variation in Medicaid use among recently pregnant mothers, within small neighborhoods, to study the impact on participation among currently pregnant women. Women are more likely to use Medicaid benefits while pregnant including prenatal care, when previously pregnant women on their census block also received similar benefits. Network effects are relatively larger for young first-time mothers as well as for women within neighborhoods with lower initial levels of welfare program knowledge.

Suggested Citation

  • Grossman, Daniel & Khalil, Umair, 2020. "Neighborhood networks and program participation," Journal of Health Economics, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:jhecon:v:70:y:2020:i:c:s0167629618306830
    DOI: 10.1016/j.jhealeco.2019.102257
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    3. Marinho Bertanha & Andrew H. McCallum & Alexis Payne & Nathan Seegert, 2022. "Bunching estimation of elasticities using Stata," Stata Journal, StataCorp LP, vol. 22(3), pages 597-624, September.
    4. Grigolon, Laura & Lasio, Laura, 2023. "Biased beliefs and stigma as barriers to treatment and innovation adoption," CEPR Discussion Papers 17938, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    Program participation; Peer effects; Networks; Medicaid;
    All these keywords.

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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