EFFECT OF NUTRITIONAL INTAKE ON ECONOMIC GROWTH : A PANEL ANALYSIS OF 15 SUB-SAHARAN COUNTRIES (2000-2020)

Abstract

Nutritionnal status and economic growth has been a topic of interest in recent years. According to the World Bank Group, undernutrition has significant economic costs in terms of lost national productivity and economic growth. The combined impact of better nutrition, when health, livelihoods, and productivity are all taken into account, represents an increase in investment. The objective of this study was to enlighten the effect of nutritionnal indicators on economic growth in sub-Saharan Africa using panel data analysis from 2000 to 2020. For this purpose data of average food energy supply and average protein supply as proxy of nutrition and GDP per capita as proxy of economic growth have been collected from 15 countries including Cameroon, Congo, Ethiopia, Gabon, Ghana, Kenya, Malawi, Mozambique, Nigeria, Rwanda, Senegal, South Africa, Uganda, Togo, and Tanzania. Considering the efficiency wage hypothesis, the anlysis investigated if the average amount of food energy available per person in a country affect their income or if the average amount of protein available per person in a country had an effect on their income. Another important focus of the study was to analyze the direction of the causality between nutritional indicators and GDP per capita probing if the average amount of food energy available per person in a country cause the GDP per capita to alter and if the average amount of protein available per person in a country cause the GDP per capita to fluctuate. The analysis was conducted using Panel cointegration, Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Dumitrescu-Hurlin causality test, all performed to capture the potential long-run and causal linkages among the three variables. To make efficient inference for the estimates, we checked for the panel unit root and co-integration relationship amongst the variables. The results showed a long run relationship between nutritionnal indicators and per capita income based on the efficiency wage hypothesis with the panel co-integration DOLS estimator showing that one-unit increase in log AverageFood and log AverageProtein is associated respectively with a 2.47 and a 1.69--unit increase in logGDPpercapita, all else being equal , respectively of the causality tests of Granger revealed evidence of long and short-run bidirectional causality between selected nutritional indicators and economic growth.