Estimation of Factors Affecting Gross Regional Domestic Product Using Geographically Weighted Panel Regression (Case Study: Gross Regional Domestic Product in Central Java 2011-2015)
Gross Regional Domestic Product (GRDP) is a main indicator of the regional economic growth which may vary spatially according to geographical conditions of region. GRDP is also measured every year, so the time information should be taken into account in modeling GRDP. As the GRDP data consists of several region and it is measured series in time, panel data regression can be used to model the GRDP data. To overcome the spatial heterogeneity among region, the Geographical Weighted Regression (GWR) models can be implemented. The combination of panel data regression and GWR is known as Geographical Weighted Panel Regression (GWPR). In this paper, the data used was a secondary data taken from Central Bureau of Statistics Indonesia in 35 regions of Central Java province during 2011-2015. The response variable was the GRPD based on the constant price of the year 2010 meanwhile the explanatory variables were the number of labor, original local government revenue, regional minimum wage, and human development index. The result shows that GWPR model with adaptive bisquare had pseudo-R2 of 96.43 %. The significant factors affecting GRDP were dissimilar among regions, therefore the regions classified into five groups.
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