Who benefits from health insurance? Uncovering heterogeneous policy impacts using causal machine learning

By University of York - 2020-11-30

Description

CHE's latest Research Paper 173 written by Noemi Kreif, Andrew Mirelman, Rodrigo Moreno-Serra, Taufik Hidayat, Karla DiazOrdaz and Marc Suhrcke

Summary

  • To be able to target health policies more efficiently, policymakers require knowledge about which individuals benefit most from a particular programme.
  • Contrasting two health insurance schemes (subsidised and contributory) to no insurance, we find beneficial average impacts of enrolment in contributory health insurance on maternal health care utilisation and infant mortality.
  • For subsidised health insurance, however, both effects were smaller and not statistically significant.

 

Topics

  1. Management (0.1)
  2. Machine_Learning (0.1)
  3. UX (0.04)

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