Is Sub-Saharan Africa on the path to achieving regional convergence or divergence in digital agriculture?

  Context and background Despite its crucial contribution to eliminating poverty, addressing hunger, and boosting the agricultural potential of many Sub-Saharan African (SSA) countries, the successful implementation of digital agriculture has been severely constrained by a host of context-specific factors that have constrained the sustenance, sustainability and growth of the sector. Such context-specific issues have undoubtedly created patterns of inequalities that have limited the ability of SSA to effectively adopt digital technologies for enhancing agriculture - a situation that has and continues to lead to regional disparities and other forms of inequities limiting the achievement of equal and inclusive digital agriculture futures.  This paper posits that achieving regional equity in digital agriculture will require a comprehensive and systematic evaluation of available performance metrics, so that we have a sense of whether SSA is on the right path towards achieving regional ‘convergency’. Despite the existence of country-specific statistics at least at the regional level, there is a general dearth of such systematic evaluations to inform the ideal path that SSA countries should follow to achieve regional balance in digital agriculture.   Goal and Objectives: The primary focus of this paper is to make a comprehensive and systematic evaluation of the performance of 47 SSA in digital agriculture using time series data from year 2018 to 2020 provided by FAO in 2022. The paper specifically addresses the following research questions. Is Sub-Saharan Africa on the path to achieving regional convergence or divergence in digital agriculture? What agriculture technology adoption hurdles are limiting the progression of SSA countries on a path towards regional equity? Methodology: The study employs a two-step statistical approach that combines agglomerative Hierarchical Cluster Analysis (HCA) and the calculation of the Gini coefficient and its associated Lorenz curve estimation to analyze if any patterns of inequality exist in the adoption of Digital agriculture by 47 SSA counties.      Results: The analysis revealed that most SSA countries have registered meaningful but minimal progress towards adopting digital agriculture. Further analysis using agglomerative hierarchical cluster analysis statistics reveals that SSA countries are heading towards territorial inequalities in the adoption of digital agriculture. We see the number of common clusters of technology adoption increasing with time from an initial one common cluster in 2018, two clusters in 2019 and 3 clusters in 2020. Such patterns of territorial inequality are also complemented but the calculated Gini coefficient statistics and Lorenz curve estimations that portray a picture of moderate inequality among SSA countries. If SSA is to achieve regional convergence in digital agriculture, there is an urgent need to address structural issues limiting enhancement of digital infrastructure by promoting investments in digital infrastructure, human capital development, and research and development aligned to the continent’s needs among other interventions. .