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Estimating causal effects of community health financing via principal stratification

Author

Listed:
  • Silvia Noirjean

    (University of Florence)

  • Mario Biggeri

    (University of Florence)

  • Laura Forastiere

    (Yale School of Public Health)

  • Fabrizia Mealli

    (University of Florence
    Florence Center for Data Science)

  • Maria Nannini

    (University of Florence
    ARCO - Action Research for CO-development, PIN - Polo Universitario Cittá di Prato)

Abstract

When a treatment cannot be enforced, but only encouraged, noncompliance naturally arises. In applied economics, the common empirical strategy for dealing with noncompliance is to rely on Instrumental Variables methods. When the effects are heterogeneous, these methods allow, under a set of assumptions, to identify the causal effect for Compliers, i.e., the subset of units whose treatment is affected by the encouragement. One of the identification assumptions is the Exclusion Restriction (ER), which essentially rules out the possibility of a causal effect for Never Takers, i.e., those whose treatment is not affected by the encouragement. In this paper, we show the consequences of violations of this assumption in the impact evaluation of an intervention implemented in Uganda, where targeted households were encouraged to join a community health financing (CHF) scheme through activities of sensitization. We conduct the analyses using Bayesian model-based principal stratification, first assuming and then relaxing the ER for Never Takers. This allows showing the positive impact of the intervention on the health costs of both Compliers and Never Takers. While the causal effects for the former could be due to the encouragement but also to the actual participation in the scheme, those for the latter are unequivocally attributable to the encouragement. This indicates that sensitization alone is extremely effective in reducing vulnerability against health costs. This finding is of paramount importance for policy-making, as it is much easier and more cost-effective to implement awareness-raising campaigns than CHF schemes.

Suggested Citation

  • Silvia Noirjean & Mario Biggeri & Laura Forastiere & Fabrizia Mealli & Maria Nannini, 2023. "Estimating causal effects of community health financing via principal stratification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1317-1350, October.
  • Handle: RePEc:spr:stmapp:v:32:y:2023:i:4:d:10.1007_s10260-023-00706-0
    DOI: 10.1007/s10260-023-00706-0
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    References listed on IDEAS

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