Analisis Ekonometrika Spasial dan Determinasi Struktural Kemiskinan di Provinsi Jawa Timur Tahun 2025
DOI:
https://doi.org/10.69836/ncrcs-sinesia.v2i2.268Keywords:
Poverty, Spatial Econometrics, OLS, LISA, Mean Years Schooling, East JavaAbstract
Penelitian ini bertujuan untuk menganalisis pola persebaran spasial kemiskinan serta mengidentifikasi faktor-faktor determinan struktural yang memengaruhinya di 38 kabupaten/kota Provinsi Jawa Timur pada tahun 2025. Variabel independen yang dianalisis meliputi Tingkat Pengangguran Terbuka (TPT), Rata-rata Lama Sekolah (RLS), Tingkat Partisipasi Angkatan Kerja (TPAK), dan persentase akses sanitasi layak. Metode analisis menggunakan pendekatan ekonometrika spasial, diawali dengan pembentukan matriks bobot spasial Queen Contiguity, pengujian Moran’s I Global, Local Indicators of Spatial Association (LISA), serta pengujian diagnostik Rao’s Score/Lagrange Multiplier (LM Test) untuk pemilihan model terbaik antara Ordinary Least Squares (OLS), Spatial Autoregressive (SAR), dan Spatial Error Model (SEM). Hasil pengujian Moran’s I Global dan LM Test menunjukkan tidak adanya autokorelasi spasial global yang signifikan, sehingga model OLS terbukti menjadi model yang paling parsimoni dan efisien. Meskipun demikian, analisis lokal LISA berhasil mengidentifikasi heterogenitas spasial dengan ditemukannya kluster hotspot (High-High) di Kabupaten Sampang dan spatial outlier (Low-High) di Kabupaten Malang. Secara parsial, Rata-rata Lama Sekolah (RLS) terbukti menjadi determinan utama yang berpengaruh negatif dan sangat signifikan terhadap kemiskinan, di mana peningkatan 1 tahun RLS diasumsikan mengurangi jumlah penduduk miskin sebesar 40,9 ribu jiwa. Temuan ini menegaskan bahwa intervensi penanganan kemiskinan di Jawa Timur memerlukan kombinasi antara peningkatan kapasitas modal manusia (human capital) secara masif dan kebijakan berbasis karakteristik wilayah (place-based policy) spesifik kawasan.
References
Adeleye, B. N., Gershon, O., Ogundipe, A., Owolabi, O., Ogunrinola, I., & Adediran, O. (2020). Comparative investigation of the growth-poverty-inequality trilemma in Sub-Saharan Africa and Latin American and Caribbean Countries. Heliyon, 6(12), e05631. https://doi.org/10.1016/j.heliyon.2020.e05631
Affandi, Purwaningsih, Y., Hakim, L., & Mulyaningsih, T. (2025). Interplay between poverty, poverty eradication and sustainable development: A semi-systematic literature review. Global Transitions, 7, 1–20. https://doi.org/10.1016/j.glt.2024.11.001
Álvarez-Gamboa, J., Cabrera-Barona, P., & Jácome-Estrella, H. (2021). Financial inclusion and multidimensional poverty in Ecuador: A spatial approach. World Development Perspectives, 22, 100311. https://doi.org/10.1016/j.wdp.2021.100311
Anderson, E., d’Orey, M. A. J., Duvendack, M., & Esposito, L. (2018). Does Government Spending Affect Income Poverty? A Meta-regression Analysis. World Development, 103, 60–71. https://doi.org/10.1016/j.worlddev.2017.10.006
Anselin, L. (1995). Local Indicators of Spatial Association—LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Benfica, R., & Henderson, H. (2020). The Effect of the Sectoral Composition of Economic Growth on Rural and Urban Poverty.
Fuseini, M. N., Enu-Kwesi, F., Abdulai, I. A., Sulemana, M., Aasoglenang, T. A., & Domapielle, M. K. (2024). Poverty in the global south: Does the geographical theory offer any new insight to understanding penury? Cogent Social Sciences, 10(1), 2321710. https://doi.org/10.1080/23311886.2024.2321710
Ghosh, R., & Mondal, P. (2026). Understanding Multidimensional Poverty Through the Lens of Local Determinants: A Micro-Level Perspective from Suri Sadar Sub-Division, Birbhum District, Eastern India. Geographies, 6(2), 49. https://doi.org/10.3390/geographies6020049
Guevara-Rosero, G. C., Vizuete-Salazar, Y., Loza-Aguirre, E., & Ramírez-Álvarez, J. (2026). Local Governments and Poverty and Spatial Spillovers of Poverty in Ecuador. Applied Research in Quality of Life, 21(1), 149–185. https://doi.org/10.1007/s11482-025-10454-w
Ifa, K., Viphindrartin, S., Santoso, E., & Priyono, T. H. (2024). Spatial dependence and poverty factors: A study of Pantura Regions in East Java Province, Indonesia. Journal of Infrastructure Policy and Development, 8(7), 4195. https://doi.org/10.24294/jipd.v8i7.4195
Liu, W., Li, J., & Zhao, R. (2020). Rural Public Expenditure and Poverty Alleviation in China: A Spatial Econometric Analysis. Journal of Agricultural Science, 12(6), 46. https://doi.org/10.5539/jas.v12n6p46
Mangara, T. H., Marlina, S., & Syaifudin, R. (2026). Dinamika interaksi spasial dalam ketimpangan pendapatan di Provinsi Banten. Journal of Economics Research and Policy Studies, 6(2), 757–774. https://doi.org/10.53088/jerps.v6i2.3127
Narro, A. R. N. (2020). Spatial Analysis of Poverty: The Case of Peru. Theoretical and Practical Research in the Economic Fields, 11(2), 95. https://doi.org/10.14505/tpref.v11.2(22).02
Olaoye, O., Ibukun, C. O., Razzak, M., & Mose, N. (2023). Poverty prevalence and negative spillovers in Sub-Saharan Africa: A focus on extreme and multidimensional poverty in the region. International Journal of Emerging Markets, 18(9), 2993–3021. https://doi.org/10.1108/IJOEM-01-2021-0028
Olaoye, O. O. (2023). Analysis of the prevalence of extreme poverty in Africa South of the Sahara: Do geographical proximity and corruption spillovers matter? Journal of Economic Studies, 50(3), 480–505. https://doi.org/10.1108/JES-07-2021-0322
Pantolla, H. G., & Atibagos-Nacion, N. (2023). Spatial Analysis of Poverty Incidence and Road Networks in Eastern Visayas Region, Philippines. Spatial Analysis, 152(4).
Rifdatul, I., Lillah, I., & Wijayaningrum, T. N. (2025). Pola Pengelompokan Spasial Kemiskinan di Provinsi.
Wardhana, D., Ihle, R., & Heijman, W. (2017). Agro-clusters and Rural Poverty: A Spatial Perspective for West Java. Bulletin of Indonesian Economic Studies, 53(2), 161–186. https://doi.org/10.1080/00074918.2017.1298722
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