Analisis Data Produk Domestik Regional Bruto Pulau Jawa Menggunakan Pendekatan Regresi Kuantil Spasial
Keywords:
Gross Regional Domestic Product, Instrumental Variable Quantile Regression, Spatial Autoregressive Quantile Regression, Two Stage Quantile RegressionAbstract
Gross Regional Domestic Product (GRDP) often shows spatial patterns. In a spatial perspective, spatial effects consist of of spatial dependence and spatial heterogeneity. To address the problems, this study uses spatial autoregressive quantile regression/SARQR model. SARQR is a method that combines Spatial Autoregressive (SAR) modeling with quantile regression. There are two methods that can be used to estimate the parameters of the SARQR model, namely Two Stage Quantile Regression (2SQR) and Instrumental Variable Quantile Regression (IVQR). The simulation results showed that IVQR method is better than 2SQR method. IVQR provides a smaller value and variance of bias. Furthermore, IVQR method is applied to Java’s GRDP data on 2019. The results showed that the number of workers significantly influences Java’s GRDP. The highest quantile verification skill score (QVSS) value is 0.713 when τ =0.75. It means that in the 75% quantile modeling, the model can describe the GRDP diversity of 71.3%.
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