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

Atinuke Adebanji, David Rios Insua and Fabrizio Ruggeri

Socio-Economic Planning Sciences, 2022, vol. 83, issue C

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.

Keywords: Policy monitoring; Bayesian forecasting; Dynamic linear models; Millennium development goals; Maternal mortality; Neonatal mortality (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:83:y:2022:i:c:s0038012122001380

DOI: 10.1016/j.seps.2022.101348

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