Pragmatic investigation of the effect of green and low-carbon economies on food safety in Africa

This research examines the relationship between a green economy—defined as an economy that promotes sustainable development through low-carbon, resource-efficient, and socially inclusive practices—and food safety across 37 African countries from 2005 to 2020. Drawing on data from the Food and Agricultural Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and World Development Indicators, this study employs the generalized method of moments (GMM) approach to address endogeneity issues inherent in economic analyses. The findings indicate that a shift toward a greener economy significantly enhances food safety, with each one-point improvement in green economic indicators associated with a 0.24% increase in food safety levels. This underscores that as African economies reduce carbon footprints and adopt sustainable agricultural practices, they experience fewer food safety challenges, largely due to improved environmental health and reduced biodiversity loss. The study concludes that prioritizing green economic growth is essential for environmental sustainability and the agricultural sector’s stability. These insights emphasize the need for policymakers and stakeholders to implement green economy strategies that enhance both ecological resilience and food security, ultimately improving health and livelihood outcomes in African communities. This study stands apart from existing literature by uniquely focusing on the relationship between the green economy and food safety within the African context, which remains underexplored despite the continent’s pressing environmental and food security challenges. Utilizing a dynamic panel Generalized Method of Moments (GMM) model, the research rigorously addresses endogeneity concerns to provide robust insights into how environmental management and other green economy policies influence food safety outcomes across 37 African nations. This methodological approach enables more accurate capture of temporal dynamics and causal relationships, offering policymakers context-specific, evidence-based recommendations tailored to Africa's socio-economic and ecological realities.