Structural Analysis of Key Factors in Poverty Alleviation for Policy Development in Persistently Impoverished Provinces in Thailand

Phimlikid Kaewhanam¹Kathanyoo Kaewhanam^1*Eko Priyo Purnomo²Noppakun Thongmual³Ariya Pongsiri¹Thitima Norrapoke⁴

• ¹Department of Public Administration, Faculty of Liberal Arts, Kalasin University, Kalasin, Thailand
• ²Department of Government Affairs and Administration, Jusuf Kalla School of Government (JKSG), University MuhammadiyahYogyakarta (UMY), Indonesia. https://orcid.org/0000-0002-4840-1650, Yogyakarta, Indonesia
• ³Faculty of Sciences and Health Technology, Kalasin University, Kalasin, Thailand., kalasin, Thailand
• ⁴Assitant Professor in Animal Production Technology, Faculty of Agricultural Technology, Kalasin University, Kalasin, Thailand., Kalasin, Thailand

Poverty remains a persistent and complex development challenge in Thailand, especially in structurally disadvantaged provinces such as Kalasin. Despite multiple national development strategies, poverty rates in Kalasin have remained consistently high over the past decade. This study investigates the structural factors contributing to poverty alleviation in the province using the Sustainable Livelihood Framework (SLF) as the core theoretical lens. The analysis focuses on five forms of capital-human, physical, financial, natural, and social-and how their significance has shifted over time. A longitudinal quantitative approach was adopted using data from household surveys conducted in 2020 (n = 9,390), 2021 (n = 2,549), and 2023 (n = 1,949). Structural Equation Modeling (SEM) was employed to evaluate the interrelationships among these capitals and their impact on poverty outcomes.The findings reveal that financial capital played the most dominant role in 2020 and 2023, while social capital peaked in influence during 2021, likely reflecting the short-term benefits of communitybased support during times of social or economic stress. Human capital maintained a moderate and stable influence across all years, whereas physical capital consistently demonstrated the least contribution to poverty reduction. To ensure model robustness, the study incorporated confirmatory factor analysis (CFA), bootstrapping for bias correction, and multicollinearity diagnostics using VIF scores. The model achieved excellent fit across all years (e.g., RMSEA < 0.01, CFI and TLI > 0.98).This research contributes to the growing literature on poverty and livelihoods by offering a predictive model for capital investment prioritization in rural development. It highlights the need for policies that are both capability-enhancing and structurally responsive, tailored to the unique socioeconomic conditions of provinces like Kalasin. The study calls for an integrated policy approach that strengthens individual agency while addressing systemic barriers to sustainable poverty alleviation.