How Big Poverty in Central Java: Mixed Regressive-Spatial Autoregressive Models

Rezzy Eko Caraka (School of Mathematical Sciences Faculty of Science and Mathematics The National University of Malaysia)

Jurnal Ekonomi Kuantitatif Terapan
2018: Vol. 11, No.1, Februari 2018 (pp. 1-144)

Mixed Regressive-Spatial Autoregressive Models (MR-SAM) is one spatial model with an area approach that takes into account the spatial influence of lag on the dependent variable. The advantage of this model is we can know the location has spatial effect or not. In this paper uses MR-SAM to determine and analyze the factors that affect the category of the poor in Central Java. MR-SAM is one of parametric regression, before using the model we must fulfill assumptions. In a nutshell, at significant ?=5% number of poverty in central java can be explained (statistically significant) by GDP, number of people didn’t finish primary school, and number of people who didn’t finished high school.