SIMULTANEOUS SPATIAL OF POVERTY AND HDI USING GS2SLS

Nur Jihan Salsabiila; Dwi Endah Kusrini; Nur Azizah; Destri Susilaningrum

doi:10.33758/mbi.v17i12.441

Authors

Nur Jihan Salsabiila Institut Teknologi Sepuluh Nopember
Dwi Endah Kusrini
Nur Azizah
Destri Susilaningrum

DOI:

https://doi.org/10.33758/mbi.v17i12.441

Keywords:

2SLS, GS2SLS, HDI, Poverty, SDGs

Abstract

The SDGs program encourages change towards sustainable development which makes poverty alleviation the main goal. Poverty is a person's inability to meet the minimum standard of living that hinders the welfare of an individual. The benchmark for welfare is the Human Development Index (HDI). It is suspected that there are spatial influences between regions because, in terms of territoriality, the province of East Java has similarities in the value of the percentage of poor people and HDI in nearby areas. Poverty and HDI and vice versa have a relationship that affects each other, so modeling is done with a system of simultaneous similarities. This work used a queen contiguity weight matrix and the Generalized Spatial Two Stage Least Squares (GS2SLS) approach to analyze spatial simultaneous equations. This method can cope with autocorrelation and heteroskedasticity. The data used are the percentage of poor people and HDI as well as variables from previous studies that are thought to significantly affect poverty and HDI in 38 Regencies/Cities of East Java in 2019. The results showed that there was a negative reciprocal relationship between the percentage of poor people and HDI. The spatial effect is positive and significant on the HDI variables with GS2SLS Spatial Autoregressive (SAR) modeling, while the percentage of poor people without spatial effects is so modeled with Two Stage Least Square (2SLS). HDI and GRDP growth rates significantly affect the percentage of poor people, while HDI is significantly influenced by the percentage of poor people and population density.

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