Pemodelan Regresi Spasial Data Panel

Panel data is a combination of cross-section data and time-series data. The panel data regression can model the panel data. In its development, panel data regression has been developed to model spatial data, called panel data spatial regression. Spatial data is data that considers the empirical observations and considers the location factor of these observations. This study examines the spatial regression modeling of panel data and applies it to model the factors that influence the Human Development Index (HDI) of districts/cities in East Kalimantan Province from 2017 to 2020. HDI is a composite index that measures the average achievement in the three basic dimensions of human development that are considered very basic, namely life expectancy, knowledge, and a decent standard of living. HDI is one of the measuring tools considered to reflect the status of human development in a region and plays an essential role in improving the quality of human resources. The results show that the panel data spatial regression model suitable for modeling the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 is the Spatial Autoregressive Fixed Effect (SAR-FE) model. The rate of economic growth and the district/city minimum wage factors that significantly influence the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 based on the SAR-FE model is the rate of economic growth and the district/city minimum wage.   Keywords : Panel Data, Spatial Data, Panel Data Spatial Regression, SAR-FE, HDI