Per capita income and public health expenditure: what makes good child health outcomes in Tanzania? a comparison of Frequentist and Bayesian approach (1995-2013)

Abstract

Using data for World Bank Development Indicators (2015) database from 1995 to 2013, this paper explores the impact of public health expenditure on national health outcomes in Tanzania while GDP per capita and improved sanitation facilities as explanatory variables were controlled for. Two national health outcomes indicators namely, infant and under-five mortality were used as dependent variables. With separate modeling approach, Frequentist and Bayesian based on time series and Markov Chain Monte Carlo (MCMC) respectively, empirical evidence shows that income, represented by real GDP per capita lower infant and under-five mortality in Tanzania. Under both methodological approach regardless of the sample size, we failed to support evidence that, public health expenditure and improved sanitation facilities had an impact on child health outcomes. Our results imply that, public health spending in Tanzania is poorly targeted to bring good child health outcomes. The paper draws attention to policy makers in Tanzania to focus either within public health spending composition or beyond to other close determinants of infant and under-five mortality.

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

“…To address the aforementioned weakness encountered in Kiross et al [ 4 ], the use of panel dynamic system Generalized method of moments (GMM) would be preferred to overcome endogeneity and its omitted variable bias present among health (infant or neonates mortality), real GDP per capita, education and health expenditures variables. Similarly, the use of Bayesian framework would be important for capturing the uncertainty of health expenditures (public and private) on infant mortality in Sub-Sahara Africa (See, [ 7 ]). The framework takes full account of uncertainties related to models, control confounding or unmeasured variables, and it uses decision making which is informed by both prior (i.e.…”

“…The effects of health expenditure on infant mortality in sub-Saharan Africa has been published in Health Economics Review, 10 (5) by Kiross et al [4], using macro data, relying on frequentist/classic methods. A study like this, among others preferred to use total health expenditure, public health expenditure and private health expenditure to explore its impact on life expectancy, infant mortality and under-five mortality, offering different conclusion (See, [1,[5][6][7][8][9]) with no consensus. The reasoning behind it is that, frequentist/classic estimation techniques depend entirely on sampling, and the likelihood of the data point given to the model without considering any kinds of uncertainty.…”

Government health expenditure and child health: empirical evidence from West African countries

“…These empirical studies and others (Novignon et al, 2012;Issa and Ouattara, 2012;Bingjie and Ronald, 2013;Musonda and Byaro, 2016;Hammers and Spears, 2016;Byaro, 2017;Barenberg et al, 2017;Abeka-Nkrumah et al, 2021) even though focused on examining the effect of health expenditure on health outcomes of children. The issue of how government health expenditure effect on child health differs comparing the short-run and long-run outcomes was not identified by these studies.…”

Economic growth and under-five malaria mortality in Tanzania mainland: from correlation analysis to causality

“…Factors such as child immunization, antenatal care providers, maternal education, skilled birth attendants and ever breastfeeding were associated with lower infant and under-five mortality in Tanzania (Byaro and Musonda, 2016). Economic development (GDP per capita) leads to improved child health outcomes (Byaro and Musonda, 2017). The indirect pathways that lead income to improved health outcomes include better nutrition, sanitation, housing, education and public health infrastructure (Bhargava et al, 2001;McGuire, 2006).…”

“…Therefore, there are many studies that show the relationship between per capita income and health outcomes (infant and under-five mortality). Most of these studies however, end with correlation and regression analysis: for instance (Byaro and Musonda, 2017;Deluna and Peralta, 2014;Nishiyama, 2011;McGuire, 2006;Filmer and Pritchett, 1999). This paper sets out to estimate the correlation between GDP per capita and under-five malaria mortality in Tanzania Mainland, to demonstrate their associations, and to test whether these relationships might be causal.…”