Spatial analysis of factors influencing Gross Regional Domestic Product (GRDP) in East Java: a spatial durbin error model analysis

Abstract

Regression analysis is not always a suitable solution if the analyzed data contains spatial effects. In overcoming the spatial effect on the data, a statistical method that can overcome it is needed. Spatial regression is a method used for data that has a location effect. One of the spatial regression model that can be used is the spatial Durbin error model. Spatial Durbin error model can overcome the spatial autocorrelation relationship in the independent variables and overcome the spatial error between regions. Spatial effects influence the rate of economic growth in an area, so it is different in each region. The quality of economic growth is an essential indicator in measuring the welfare of an area’s people. The Gross Regional Domestic Product (GRDP) can measure the rate of economic growth. Many factors affect the size of the GRDP, including the total workforce, the number of industries, the number of labour, general allocation funds, regional revenue, and regional expenditure. This study uses the Spatial Durbin Error Model to model GRDP and map the level of economic growth in 38 districts/cities in East Java.