Search results

This study aims to examine the influence of global and local structural factors on reducing poverty.

The research uses data spanning from 1996–2022 and uses the nonlinear autoregressive distributed lag model. This model allows for the assessment of the short and long-term effects of remittance inflow (RI) growth, control on corruption and employment rate (ER) on poverty reduction in India.

The research findings indicate that in the short run, an increase in international RIs, a higher control of corruption and a greater ERare associated with a decrease in poverty in India. Specifically, a positive change in RIs and control of corruption significantly reduces poverty, while an increase in the ERhas a substantial impact. However, in the long run, only a positive change in RIs and a higher control of corruption continue to significantly reduce poverty.

This study makes several significant contributions to the existing literature. First, it examines the simultaneous impact of three structural factors on poverty, offering insights into their combined long-term effects on the economy. Second, unlike previous studies, this research investigates the nonlinear effects on poverty, which is particularly relevant for developing nations. Lastly, this study aligns with the United Nations’ Sustainable Development Goal 1, which aims to end poverty in all its forms everywhere. The findings of this study are expected to assist Indian policymakers in formulating effective poverty eradication strategies and provide guidance for other developing nations facing similar challenges.