Since 2014
How Big Poverty in Central Java: Mixed Regressive-Spatial Autoregressive Models
Jurnal Ekonomi Kuantitatif Terapan
View Archive Info| Field | Value | |
| Title |
How Big Poverty in Central Java: Mixed Regressive-Spatial Autoregressive Models
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| Creator |
Caraka, Rezzy Eko
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| Description |
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.
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| Publisher |
Universitas Udayana
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| Date |
2018-02-27
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
https://ojs.unud.ac.id/index.php/jekt/article/view/37925
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| Source |
Jurnal Ekonomi Kuantitatif Terapan; 2018: Vol. 11, No.1, Februari 2018 (pp. 1-144); 53-60
2303-0186 2301-8968 10.24843/JEKT.2018.v11.i01 |
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| Language |
eng
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| Relation |
https://ojs.unud.ac.id/index.php/jekt/article/view/37925/23992
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| Rights |
Copyright (c) 2018 Jurnal Ekonomi Kuantitatif Terapan
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