Abstract
According to the World Health Organization (2020), many parts of the world have demonstrated potentials for acute hunger and famine. Many countries in Sub-Saharan Africa (SSA) actively feature in this category due to geopolitical crises and other humanitarian challenges. Despite efforts by SSA governments, agricultural productivity continues to be inadequate in meeting nutritional needs across Africa. Thus, in the presence of economic expansion, vast land, and labor resources, this study investigates the role of mechanization as an important factor for increased agricultural productivity in SSA. Data on 25 SSA countries over 17 years are used. Empirical results from System Generalized Method of Moments show that among other variables, mechanization is a significant factor influencing agricultural productivity. Consequently, in light of the bid for higher agricultural productivity, government investment in mechanization becomes a priority. Also, apart from the fact that many African countries are at the point where more land must be brought under development to satisfy expanded market needs, larger investments in mechanization appear imperative.
Highlights
In the words of Maximo Torero (2014) of the International Food Policy Research Institute (IFPRI) on World Food Day, “Economic growth is only sustainable if all countries have food security
Higher productivity would occur, food security would be achieved, and dependence on food importation will be limited. To empirically confirm this view, this study investigates the impact of mechanization on agricultural productivity and on economic growth using a panel data analysis of 48 SubSaharan African countries
The Pearson correlation coefficient is a proportion of the quality and bearing of affiliation that exists between two variables and draws a line of best fit through the information of the two factors
Summary
This is a lot higher than the global average for the same period, and implies that 1 out of every 4 Sub-Saharan African is undernourished based on the FAO standard of 1800 Kcal intake per day These figures are projected to further increase to about 355 million people by the year 2050 (African Association for the Study of Regions [AASR], 2014). The GMM approach is robust to the pitfalls such as heteroscedasticity, autocorrelation, and endogeneity commonly associated with conventional panel methods; it provides reliable estimates for data series with time dimensions smaller than the number of cross-sections (N > T) and assumes that fixed individual effects may be arbitrarily distributed This aforementioned strength of the methodology adopted implies that the study results are robust and suitable for policy direction. According to Xie, You, Wielgosz, and Ringler (2014), SSA has a potential expandable area of 30 million ha for motor pumps, 24 million ha for treadle pumps, 22 million ha for small reservoirs, and 20 million ha for communal river diversions
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