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Dynamic linear models for policy monitoring. The case of maternal and neonatal mortality in Ghana

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  • Adebanji, Atinuke
  • Rios Insua, David
  • Ruggeri, Fabrizio

Abstract

Monitoring is a major step in policy analysis used to assess whether a policy is actually working as desired. We provide a general policy monitoring approach based on Bayesian forecasting models. These are employed to predict the evolution of relevant monitoring variables over time and support expected utility calculations to assess the efficiency of the policy. We illustrate the approach by monitoring the Free Maternal Health Care and MDG5 Acceleration Framework policies aimed to reduce maternal and neonatal mortality in Ghana, using dynamic linear models for forecasting purposes. Despite major investments, results at national level suggest no significant improvement in maternal and neonatal survival between pre- and post-policy periods. However, regional analyses show that gains have actually been attained in certain regions, suggesting possible directions for improvements nationwide.

Suggested Citation

  • Adebanji, Atinuke & Rios Insua, David & Ruggeri, Fabrizio, 2022. "Dynamic linear models for policy monitoring. The case of maternal and neonatal mortality in Ghana," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:soceps:v:83:y:2022:i:c:s0038012122001380
    DOI: 10.1016/j.seps.2022.101348
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    Cited by:

    1. Amit S. Malhan & Kiarash Sadeghi-R & Robert Pavur & Lou Pelton, 2024. "Healthcare information management and operational cost performance: empirical evidence," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(6), pages 963-977, August.

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