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

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...

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Bibliographic Details
Main Author: Rezzy Eko Caraka
Format: Article
Language:English
Published: Universitas Udayana 2018-02-01
Series:Jurnal Ekonomi Kuantitatif Terapan
Online Access:https://ojs.unud.ac.id/index.php/jekt/article/view/37925
Description
Summary: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.
ISSN:2303-0186