Empowering people, protecting the planet, promoting prosperity: A multidimensional approach to poverty and inequality dynamics in SAARC economies

Poverty is a complex and multifaceted issue that necessitates empirical investigation and informed policy solutions. This study examines the various factors that contributed to reducing poverty across seven SAARC countries (Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) from 2000 to 2022. The study employs sophisticated econometric approaches, including Fully Modified Ordinary Least Squares (FMOLS), Difference Generalized Method of Moments (GMM), and FMOLS with country-clustered standard errors to explain the processes of poverty alleviation. The empirical results reveal significant estimator variability. The FMOLS estimates that poverty is negatively connected to income difference, gender health inequities, access to clean fuel and technology, gender parity in education, and gender parity in the labor market. Based on Difference GMM, income inequality, gender parity in health and labor markets, agricultural value-added, and biodiversity loss all positively affect poverty dynamics, while institutional quality and clean energy availability continuously reduce poverty. According to FMOLS estimates with clustered standard errors, corruption control, domestic credit, clean fuel availability, and labor-market gender parity reduce poverty. In contrast, inequality and health-related gender disparities worsen it. Variance decomposition and causality show that governance quality, financial inclusion, and gender-based inequality continue to affect long-term poverty. The study promotes inclusive financial systems, gender-responsive development strategies, and governance improvements in accordance with SDGs 1, 5, 10, and 16. • Examines drivers of poverty reduction in SAARC economies • Assesses SDG 1, 5, 10, and 16 in poverty and inequality context • Uses FMOLS and GMM to ensure robust empirical results • Governance, finance, and agriculture show estimator-specific associations with poverty dynamics. • Inequality and weak gender policies increase poverty levels