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Poverty: Definition, Factors, Measure, and Approach Nand Kishor Kumar; Man Bahadur Sunuwar
International Journal of Humanities, Education, and Social Sciences Vol 4 No 2 (2026): International Journal of Humanities, Education, and Social Sciences
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ijhess.v4i2.9137

Abstract

Poverty remains a complex and multidimensional phenomenon that cannot be effectively addressed through a single policy instrument or a purely income-based perspective. This study examines poverty as a structural and human development challenge and emphasizes the need for comprehensive and integrated solutions to reduce its incidence and improve overall well-being. The analysis highlights that effective poverty reduction depends on the interaction of inclusive economic growth, social protection, good governance, and the empowerment of marginalized groups. It further underscores that a balanced combination of income-based and human-centered approaches is essential for addressing the multiple dimensions of deprivation and for promoting sustainable development. The study concludes that poverty alleviation strategies must move beyond narrow monetary measures and adopt a more integrated framework that strengthens livelihoods, expands social inclusion, and enhances the quality of life for all.
Mathematical Analysis of the Impact of Climate Factors and Agricultural Practices on Rice Yield in Nepal: A Time Series Data Analysis Omkar Poudel; Nand Kishor Kumar; Pradeep Acharya; Deep Raj Sharma; Suresh Kumar Sahani
Journal of Multidisciplinary Science: MIKAILALSYS Vol 3 No 2 (2025): Journal of Multidisciplinary Science: MIKAILALSYS
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mikailalsys.v3i2.5725

Abstract

Rice is a staple food and a crucial element of Nepal’s agrarian economy; however, its yield is significantly affected by climatic factors such as rainfall and temperature, as well as agricultural practices like pesticide use. Understanding these dynamics is essential for sustaining productivity in the face of climate change. This study employs an Autoregressive Distributed Lag (ARDL) model to analyze 33 years of time-series data (1990–2022), focusing on key variables including rice yield, temperature, rainfall, and pesticide use, all derived from secondary data sources. Diagnostic tests confirmed normality (????=0.06), absence of serial correlation (????=0.58), and homoscedasticity (????=0.68), with stability validated through CUSUM and CUSUMSQ tests. The results indicate that temperature has a significant positive long-term impact on rice yield (????=2181.48, ????<0.05), suggesting that moderate warming can enhance productivity. Rainfall exerts a marginal positive effect (????=5.10, ????=0.05), while pesticide use shows a strong correlation with yield (????=17.70, ????<0.01). The Granger Causality Test identifies temperature (????=7.76, ????<0.01) and pesticide use (????=11.25, ????<0.01) as critical predictors of rice yield. These findings demonstrate that while temperature and pesticide use significantly affect rice yield, the impact of rainfall is diminished due to effective irrigation systems. Nevertheless, the heavy reliance on pesticides raises sustainability concerns, underscoring the necessity for integrated pest management and environmental safeguards. This study advocates for the adoption of climate-smart agricultural practices, enhancement of irrigation infrastructure, and promotion of sustainable pesticide management, offering actionable insights for policymakers to devise adaptive strategies that bolster resilience and productivity in Nepal’s rice sector.