Commentary: on the effects of health expenditure on infant mortality in sub-Saharan Africa: evidence from panel data analysis

Abstract

Background This commentary assesses critically the published article in the Health Economics Review. 2020; 10 (1), 1–9. It explains the effects of health expenditure on infant mortality in sub-Saharan Africa using a panel data analysis (i.e. random effects) over the year 2000–2015 extracted from the World Bank Development Indicators. The paper is well written and deserve careful attention. Main text The main reasons for inaccurate estimates observed in this paper are due to endogeneity issue with random effects panel estimators. It occurs when two or more variables simultaneously affect/cause each other. In this paper, the presence of endogeneity bias (i.e. education, health, health care expenditures and real GDP per capita variables) and its omitted variable bias leads to inaccurate estimates and conclusion. Random effects model require strict exogeneity of regressors. Moreover, frequentist/classic estimation (i.e. random effects) relies on sampling size and likelihood of the data in a specified model without considering other kinds of uncertainty. Conclusion This comment argues future studies on health expenditures versus health outcomes (i.e. infant, under-five and neonates mortality) to use either dynamic panel (i.e. system Generalized Method of Moments, GMM) to control endogeneity issues among health (infant or neonates mortality), GDP per capita, education and health expenditures variables or adopting Bayesian framework to adjust uncertainty (i.e. confounding, measurement errors and endogeneity of variables) within a range of probability distribution.

Can Health Human Capital Help the Sub-Saharan Africa Out of the Poverty Trap? An ARDL Model Approach

“…Health human capital (H) is measured by domestic general government health expenditure (% of GDP). Health expenditure is a major determinant of health outcomes ( 45 , 46 ).…”

“DELIVER AFRICA FROM DEBTS”: Good Governance Alone is not Enough to Save the Continent From Debt Onslaught

“…CPI (inflation rate) is used as an indicator of prices of goods and services in the economy. Since our data consists of a panel of 41 countries for 14 years, where N = 41 is much larger than T = 14, our model approach favors the Generalized Method of Moments (GMM) system estimator that applies a number of instruments to control endogeneity between economic growth, trade, and debt (see Byaro 2021aByaro , 2021b. Economic growth and government debt have causal links that requires an instrumental variable approach such as the GMM.…”

Effects of health expenditures on infant and child mortality rates: A dynamic panel data analysis of 37 African countries

“…Empirical results of studies on the effects of health investments on health outcomes, such as infant and child mortality, are mixed, casting some doubt on the effects of public expenditure in the health sector (Byaro, 2021; Gallet & Doucouliagos, 2017; Obrizan & Wehby, 2018). Indeed, these findings vary with different datasets and methods used especially for infant and maternal mortality rates (Owusu et al, 2021).…”

“…Indeed, these findings vary with different datasets and methods used especially for infant and maternal mortality rates (Owusu et al, 2021). According to Byaro (2021), most of the works focusing on African economies have used random/fixed effects estimators which produce inaccurate estimates owing to endogeneity issues (omitted variable bias, reverse causality, etc.) arising between health and its determinants.…”

“…arising between health and its determinants. Therefore, Byaro (2021) argues that future studies on health care consumption (i.e. health expenditure) vs. health status should use a dynamic panel (i.e., system generalized method of moments, GMM) to control endogeneity issues among health and its determinants.…”