Dynamic inference of healthcare expenditure on economic growth in Sub-Saharan Africa: a dynamic heterogenous panel data analysis

Abstract

PurposeThis article investigates the dynamic implication of healthcare expenditure on economic growth in the selected ten Sub-Saharan African countries over the period 2000–2018.Design/methodology/approachThe study methodology included dynamic heterogenous panel, using mean group and pooled mean group estimators. The investigation of the healthcare expenditure and economic growth nexus was achieved while controlling the effects of investment, savings, labor force and life expectancy via interaction terms.FindingsThe results from linear healthcare expenditure have a significant positive impact on economic growth, while the nonlinear estimates through the interaction terms between healthcare expenditure and investment have a negative statistically significant impact on growth. The marginal effect of healthcare expenditure evaluated at the minimum and maximum level of investment is positive, suggesting the impact of health expenditure on growth does not vary with the level of investments. This result responds to the primary objective of the article.Research limitations/implicationsIn policy terms, the impact of investment on healthcare is essential to addressing future health crises. The impact of coronavirus disease 2019 (COVID-19) can never be separated from the shortages or low prioritization of health against other sectors of the economy. The article also provides an insight to policymakers on the demand for policy reform that will boost and make the health sector attractive to both domestic and foreign direct investment.Originality/valueGiven the vulnerability of SSA to the health crisis, there are limited studies to examine this phenomenon and first to address the needed investment priorities to the health sector infrastructure in SSA.

Government expenditure on health and economic growth in Botswana

“…The positive effect of expenditure on health works through improved worker productivity since a health population adapts quickly, works longer and more efficiently (Aghion & Howitt, 1996, Gaies, 2022. This is supported by past studies (Liang, 2012, Lee et al, 2019, Erçelik, 2018, Raghupathi & Raghupathi, 2020, Sinha, 2021, Abdulqadir et al, 2022, Gaies, 2022 which show that an increase in health care expenditure accompanies economic growth. This is realised as better health care stabilizes life and contributes to improved worker productivity.…”

“…Moreover the conclusions from panel data are unrealiable due to omitted variables bias and the presence of unobserved country and year specific determinants of per capita health expenditures. Several studies employ panel data unit roots (see, e.g Sen, 2005, Piabuo & Tieguhong, 2017, Raghupathi & Raghupathi, 2020, Abdulqadir et al, 2022 and raise concerns that panel data estimations of the GDP and GEH relationship may be spurious. Whilst, using panel data has advantages over cross-sectional data; it has its own problems ranging from the presence of trending variables in the regressors, such as GDP and GEH to the problem of exchange rates (Zulfikar & STp, 2019).…”

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“…In order to combat the adverse health effects of pollution, carbon pricing devices must be used to remove and prohibit polluting enterprises from operating inside the nation. Improve the development of the green economy by integrating natural resources and ecosystems, regulating environmental institutions, and providing financial and technical resources for the implementation of pricing policies in the pollution sector of the economy are some of the objectives (Zhao et al 2022;Rahman et al 2022;Abdulqadir et al 2022). Table 8 shows the ARDL bounds testing estimates.…”

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“…The magnitude of the coefficient α 1 is expected to have a positive environmental signal while α 3 is to have a negative environmental signal. Building on the contemporary ARDL-centric literature to amplify the model with some modification (Abdulqadir, 2021; Abdulqadir et al , 2022).…”