Effects of per capita GRDP, education, and social assistance on poverty
DOI:
https://doi.org/10.52300/jepp.v6i1.23400Keywords:
poverty, GRDP per capita, educational attainment, social assistance, panel dataAbstract
Poverty reduction requires understanding how regional economic development, education, and fiscal redistribution interact in disadvantaged areas. This study examines the associations of gross regional domestic product (GRDP) per capita, mean years of schooling, and realized social assistance expenditure with poverty rates in five regencies with the highest poverty rates in Lampung Province, Indonesia. Secondary panel data covering 2018–2024 were analyzed using a logarithmic fixed effects specification selected through Chow and Hausman tests, with White cross-section robust standard errors. GRDP per capita and mean years of schooling were negatively and significantly associated with poverty, with estimated elasticities of −1.067 and −1.607, respectively. Social assistance expenditure exhibited a positive but statistically insignificant coefficient, providing insufficient evidence of a poverty-reducing association within the observed period. The model, including regency fixed effects, explained approximately 91% of poverty variation. These findings support coordinated policies that expand productive economic opportunities, improve educational attainment, and strengthen assistance targeting and implementation. However, the observational design limits causal interpretation, and the findings remain specific to the selected regencies and period
Downloads
References
Badan Pusat Statistik Provinsi Lampung. (2024). Indeks pembangunan manusia (IPM UHH SP2010).
Badan Pusat Statistik Provinsi Lampung. (2025). Persentase penduduk miskin Provinsi Lampung September 2024, turun menjadi 10,62 persen.
Barr, N. (2020). The economics of the welfare state (6th ed.). Oxford University Press.
Brown, P., Lauder, H., & Cheung, S. Y. (2020). The death of human capital? Its failed promise and how to renew it in an age of disruption. Oxford University Press.
Ghozali, I. (2018). Aplikasi analisis multivariate dengan program IBM SPSS 25 (9th ed.). Badan Penerbit Universitas Diponegoro.
Gujarati, D. N., & Porter, D. C. (2013). Dasar-dasar ekonometrika (R. C. Mangunsong, Trans.; 5th ed., Vol. 1). Salemba Empat.
Najib Putri, R. H., & Yuliana, I. (2023). Pengaruh pertumbuhan ekonomi terhadap tingkat kemiskinan dengan pengangguran sebagai mediasi di Probolinggo. Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan, 5(6), 2691–2700.
Papachashvili, N., Roblek, V., Meško, M., & Podbregar, I. (2023). Welfare state on the theoretical crossroads: Analysis of the twenty-first-century studies. International Review of Sociology, 33(1), 23–38.
Psacharopoulos, G., & Patrinos, H. A. (2018). Returns to investment in education: A decennial review of the global literature. Education Economics, 26(5), 445–458.
Ramdani, S. A. (2024). Dampak belanja subsidi dan bantuan sosial dari APBD terhadap kesenjangan pendapatan di Indonesia. Jurnal Manajemen Perbendaharaan, 5(1), 57–77.
Ravallion, M. (2016). The economics of poverty: History, measurement, and policy. Oxford University Press.
Santoso, S. (2017). Menguasai statistik dengan SPSS 24. Elex Media Komputindo.
Todaro, M. P., & Smith, S. C. (2015). Economic development (12th ed.). Pearson.
Todaro, M. P., & Smith, S. C. (2020). Economic development (13th ed.). Pearson.
United Nations Development Programme. (2024). Human development report 2023/2024: Breaking the gridlock: Reimagining cooperation in a polarized world.
Widarjono, A. (2018). Ekonometrika: Pengantar dan aplikasinya disertai panduan EViews (5th ed.). UPP STIM YKPN.
