(i) Structural transformation by which shares of agriculture in income and employment decline is the outcome of a development process that raises incomes and living standards.
(ii) However, the process is uneven as a result of which the decline in agriculture’s income share is faster than its decline in employment share. This results in a substantial disparity in worker productivity across sectors.
The unpredictable shifts in climatic patterns and limited adaptive capacity are adversely affecting agriculture and, in turn, the livelihoods of the Ugandan population (UBOS, 2024). To this end, the Government of Uganda, through the Ministry of Agriculture, working with other ministries, including the Ministries of Water and Environment, Energy, and Finance, has promoted the uptake of Climate-Smart Agriculture (CSA) (Zizinga et al., 2022).
Sustainable agriculture is becoming increasingly vital for food security and economic growth, particularly as the agricultural sector grapples with challenges posed by climate change. This study, grounded in the environmental innovation theory, resource‐based view, and dynamic capabilities approach, uses logistic and multinomial logistic regression models to evaluate the eco‐innovation behavior of agricultural firms in Chile. We focus on the impact of technology push, market pull, regulatory push or pull, and firm‐specific factors on eco‐innovations.
This chapter explores the economic effects of long-term droughts on agriculture and urban water supply sectors in Chile, with a particular focus on the ongoing megadrought that started in 2010. Using a comprehensive framework that incorporates Infrastructure Capacity (IC), the Amount of Water in Storage (AWS), and adaptation strategies, we offer a detailed analysis of resilience mechanisms and the economic impacts of drought conditions.
Establishing a clear link between prices of conventional and niche product versions can help address challenges associated with anticipating these prices and attenuate concerns related to thin market conditions. In that regard, we analyze the price dynamics, differentiating between agri-product quality and marketing channels. Special attention is devoted to exploring how this price relationship varies when affected by energy or climate-related shocks. Our methodology follows a panel vector autoregression model (PVAR), which we apply to 23 local market prices in Chile for 2014.M10–2019.M12.
EfD Tanzania researcher Dr. Innocensia John has dedicated her work to indigenous crops for years, emphasizing their role in nutrition, climate adaptation, and economic empowerment for smallholder
This research aims to investigate the potential of artificial intelligence (AI) applications in addressing the energy consumption and CO2 emissions challenges faced by countries in Sub-Saharan Africa (SSA) and their implications for economic growth. It employed a theoretical approach towards examining how AI mitigates CO2 emissions and optimizes energy use in SSA countries. It identified opportunities for AI integration to enhance energy efficiency, while reducing carbon footprints, and promoting sustainable economic development.
