DEA و نموذجTobit قياس كفاءة الانفاق الصحي العمومي في أوروبا و تحليل تأثير الرقمنة عليها باستخدام منهجية

Abstract

This study aims to measure the technical efficiency of public health expenditure across a sample of eight European countries—Germany, France, Spain, Italy, Sweden, Denmark, Poland, and Hungary—over the period 2018–2023, while analyzing the impact of digitalization as well as economic and demographic factors on efficiency levels. The relevance of the study stems from the paradox between high levels of public health spending in Europe and persistent disparities in health system performance across countries, raising questions about the efficiency of public resource allocation. The study adopts a two-stage quantitative approach. In the first stage, Data Envelopment Analysis (DEA) is applied under both Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) assumptions to estimate relative technical efficiency, using public health expenditure per capita as the input variable, and Healthy Life Expectancy (HALE) and Infant Survival Rate (ISR) as outputs. In the second stage, a Tobit regression model is employed to identify the determinants of efficiency scores, including GDP per capita, population density, the Digital Public Services index (DESI/DPS), and a COVID-19 dummy variable. The results reveal significant heterogeneity in technical efficiency across countries, with Sweden consistently achieving full efficiency, while Denmark records the lowest performance. Tobit estimates indicate that GDP per capita and population density exert negative effects on efficiency. The digitalization index also shows a significant negative impact, suggesting a transitional stage in digital health transformation. In contrast, the COVID-19 variable does not exhibit a statistically significant direct effect on technical efficiency.