期刊名称：JEPI (Jurnal Ekonomi dan Pembangunan Indonesia)
印刷版ISSN：1411-5212
电子版ISSN：2406-9280
出版年度：2014
卷号：14
期号：2
页码：128-144
DOI：10.21002/jepi.v14i2.441
出版社：Department of Economics
摘要：Pro-poor growth program has not been effective reducing poverty in Papua because the government does not have complete information about the spatial variation of poverty-causing factors (spatial heterogeneity). Therefore, this study will analyze poverty-causing factors using Geographically Weighted Regression (GWR) model. This study finds that the influence of the cultivated land area, use of technical irrigation, source of drinking water, and the electrical infrastructure vary spatially. In additions, multivariate K-means clusteringshows that subdistricts are spatially clustered by geographical conditions. These results imply that poverty alleviation interventions should be dierent for different areas.
其他摘要：AbstractPro-poor growth program has not been effective reducing poverty in Papua because the government does not have complete information about the spatial variation of poverty-causing factors (spatial heterogeneity). Therefore, this study will analyze poverty-causing factors using Geographically Weighted Regression (GWR) model. This study finds that the influence of the cultivated land area, use of technical irrigation, source of drinking water, and the electrical infrastructure vary spatially. In additions, multivariate K-means clusteringshows that subdistricts are spatially clustered by geographical conditions. These results imply that poverty alleviation interventions should be dierent for different areas.
