Influence of health sector financing on economic growth in Kenya (2000- 2020)

Abstract

Economic growth positively impacts population health, providing access to quality healthcare, environmental protection, clean water, and better preventative behavior. However, Kenya's declining growth rate affects health financing, causing many citizens to struggle with access to care due to rising medical costs. This study sought to analyse the influence of health sector financing on economic growth in Kenya. The study was guided by the following specific objectives: to determine the influence of public health financing; health insurance financing; households’ health financing and donors’ health financing on economic growth in Kenya. The study was guided by transactions Endogenous theory, Wagner’s theory and Solow-Swan Exogenous Growth Model. The study was conducted in Kenya. Data used in study was longitudinal data for twenty one years. The study period was from 2000 to 2020. A descriptive and inferential analysis performed where Auto-Regressive Distributive Lag (ARDL) model was used. Analyzed data were presented in the form of tables and discussions. From the analysis it was established that the public health financing coefficient was positive and statistically significant (a=0.1819, p= 0.012<0.05), indicating that one unit increase in public health financing could lead to 0.1819 units in economic growth in Kenya. The health insurance financing indicated a positive and statistically significant (b=0.2935; p = 0.028<0.05), implying that one unit increase in health insurance financing could result in 0.2935 units in economic growth in Kenya. The household health financing was positive and statistically significant (c=0.2958; p= 0.003<0.05), implying that for every one unit household health financing contributed to 0.2958 units to economic growth in Kenya. The donor health financing was positive and statistically significant (d1= 0.2573 p=0.017<0.05) in a short-run, implying that a unit increase in donor health financing initially contribute 0.2573 units in economic growth in Kenya. However, the long-run effect, donor health financing was negative and statistically significant (d2= 0.2982 p=0.0.014<0.05) implying one unit increase in donor financing could lead to a reduction of 0.2982 units in economic growth in Kenya. The study showed that adjusted R-squared was 0.9271, implying that the model explains approximately 92.71% of the variation in the economic growth in Kenya. The study concluded that public health financing, health insurance financing, and household health financing were positively related to economic growth in the long run in Kenya. Donor health financing, on the other hand had a positive and significant effect on economic growth while in the long run , the effect was negative and significant. The study recommends that there is need for enhancing domestic health financing sources like public health, health insurance, and household financing, and gradually shifting towards sustainable domestic financing sources. Policymakers should focus on strengthening these domestic sources of health financing to promote sustainable economic development. Future research should incorporate other macroeconomic, demographic, and institutional factors could provide a more comprehensive understanding of the determinants of economic growth.