SPATIAL DURBIN MODEL OF UNEMPLOYMENT RATE IN CENTRAL JAVA
DOI:
https://doi.org/10.22487/27765660.2023.v3.i1.16423Keywords:
Classical Regression, Spatial Auto Regressive, Spatial Durbin Models, UnemploymentAbstract
Unemployment is a labor problem that is often faced by developing countries like Indonesia. The number of unemployed in Indonesia has fluctuated from year to year, including in Central Java Province. One of the efforts made to overcome this problem is to know the factors that influence unemployment. The region effect greatly affects the open unemployment rate. Modeling involving area effects is very precise, one of which is the Spatial Durbin Model (SDM). In this study, modeling of the open unemployment rate was carried out using a spatial approach in each district/city in Central Java. The models used in this study are Ordinary Last Square (OLS), Spatial Auto Regressive (SAR), Spatial Error Models (SEM), Spatial Durbin Model (SDM), Spatial Error Durbin Model (SDEM). The five methods were evaluated using the Akaike Information Criteria (AIC). The spatial weighting used in this study is Queen Contiguity. Based on the smallest AIC value (115.42), the best method in this study is HR. Meanwhile, the significant factors are the percentage of labor force participation rate (X1), the number of poor people (X4), the lag of economic growth, the lag of poverty, and the lag of the district/city minimum wage
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