Dynamic monitoring and modeling of the growth-poverty-inequality trilemma in the Nile River Basin with consistent night-time data (2000–2020)

Abstract

Aligning with UN Sustainable Development Goals (SDGs) 1 and 10, the ‘growth-poverty-inequality’ (GPI) nexus has become widely discussed in economic development research. It remains an important discourse regarding sustainable development. To monitor spatiotemporal economic development and analyse the GPI trilemma, especially in developing and undeveloped regions, a novel framework based on long-term, consistent night-time light (NTL) remote sensing (RS) data (2000–2020) was proposed and applied to the Nile River Basin. An optimized, multitemporal estimation strategy was developed for gross domestic product (GDP) estimation and spatialization. Then, the poverty map and inequality indices for the entire basin and each country were prepared. Combining GDP growth, the poverty map, inequality index, and other relevant economic statistics, the GPI nexus for the Nile River Basin was modelled. Findings suggest that the proposed framework can not only effectively map GPI dynamics but also accurately model the GPI nexus. We found that the economic development of countries in the Nile River Basin is characterised by widespread poverty and inequality and restricted spatial distribution. The spatiotemporal evolution patterns of GPI vary with upstream and downstream geographic locations. Regarding their interaction, study findings revealed that economic growth relieves poverty, whereas high inequality levels aggravate poverty. Moreover, high inequality dampens the positive effect of economic growth on poverty reduction. This study offers new insight into GPI trilemma modeling and analyses using NTL data, an economically viable alternative to mass field surveys that is especially relevant for developing and underdeveloped regions.