Spatial dependence and poverty factors: A study of Pantura Regions in East Java Province, Indonesia

Khoirul Ifa, Sebastiana Viphindrartin, Edy Santoso, Teguh Hadi Priyono

Article ID: 4195
Vol 8, Issue 7, 2024

VIEWS - 235 (Abstract) 121 (PDF)

Abstract


Poverty is still a problem in various countries in the world, so eradicating poverty and hunger by 2030 is the backbone of the goals of the sustainable development agenda. Poverty, which is the main goal of the Millennium Development Goals (MDGs), is again the main goal in the Sustainable Development Goals (SDGs). This research aims to determine the spatial dependence of poverty in the Pantura Region of East Java Province and to determine the influence of economic growth, education, unemployment, natural resources, health and accessibility on poverty in the Pantura Region of East Java Province. This research uses a quantitative approach, with data analysis methods using Moran’s index analysis, and spatial panel regression by selecting the best model from four models, namely the spatial autoregressive model (SAR), the spatial error model (SEM), the spatial Durbin model (SDM), and spatial autoregressive combined (SAC) model. The research results show that there is spatial interaction between coastal areas through endogenous and exogenous interactions between independent variables. Based on the selection of the best model, the spatial Durbin model (SDM) was selected for the Pantura Region. Economic growth has a negative effect on poverty. Education has a negative effect on poverty. Unemployment has no effect on poverty. Natural resources have a positive effect on poverty. Health has no effect. Accessibility has a negative effect on poverty in the Pantura Region. This research provides a new and important contribution in understanding the spatial patterns of poverty and the factors that influence it in the Pantura Region, which is a strategic and vulnerable area in East Java. This research also faces several limitations and challenges, such as data quality, model assumptions, and spatial validity. Future research could expand this analysis using more complete data, more flexible models, and more sophisticated techniques.

Keywords


spatial dependence; poverty; Pantura Regions

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DOI: https://doi.org/10.24294/jipd.v8i7.4195

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