Comparative Analysis of SFA and DEA Models: An Application to Health System Efficiency in SSA

Akanni Olayinka Lawanson, Jacob Novignon



The Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) are the two major approaches in estimating technical efficiency. However, the two approaches have different underlying assumption and present different efficiency estimates when used in similar situation. In this study we compare the two approaches with an application to health system efficiency across countries in Sub-Saharan Africa (SSA).


The study used cross section data for 45 countries in SSA, sourced from the World Bank world development indicators. Both the DEA and SFA were used to estimate health system efficiency using per capita health expenditure as input while under-five and infant mortality was used as health outcomes. Scatter and Kernel density plots were used to supplement the comparison of estimates from the two models.


The findings suggest that there exist disparities between estimates from the DEA and SFA models. Estimates from the SFA models were relatively higher than those from the DEA models. However, there was not much difference in the ranking of individual countries in terms of efficiency performance. The findings of the various model specifications show average health system efficiency scores of approximately 0.44 and 0.50 for the DEA specifications while 0.70 and 0.72 was estimated for the SFA specifications


The efficiency scores suggest that there is room for improvement in terms health system performance. The choice between the two models should be based on the availability of data and the limitations posed by the data requirements of each of the models.


DEA, SFA, health system efficiency, health expenditure, SSA

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