Poverty Mapping in Romania

10.1596/k8686 ◽  
2016 ◽  
Author(s):  
Keyword(s):  
Poverty Mapping

scholarly journals Analisis Potensi Sektor Unggulan dan Pemetaan Kemiskinan Masyarakat di Wilayah Maminasata Sulawesi Selatan

2019 ◽  
Vol 5 (2) ◽  
pp. 85
Author(s):  
Citra Ayni Kamaruddin ◽  
Syamsu Alam
Keyword(s):  
Poor People ◽  
Economic Sectors ◽  
Location Quotient ◽  
Growth Ratio ◽  
South Sulawesi ◽  
Analysis Tools ◽  
Sector Analysis ◽  
High Level ◽  
Poverty Mapping ◽  
Typology Analysis

The purpose of this study is to map sectoral superior potential and changes in regional poverty levels in the Mamminasata region. The method used in this study is qualitative descriptive, using quantitative analysis tools, leading sector analysis tools such as Location Quotient (LQ), Growth Ratio Model (MRP), Overlay Analysis, and Klassen Typology. The results of the study show that there is still a high level of disparity in leading sectors in the Mamminasata region. The results of the analysis show that Makassar City has 12 leading sectors, Kab. Gowa, 7 leading sectors, Maros District 4 leading sector, and Takalar District 3 superior sector. While the results of the Klassen Typology analysis show that only Makassar City consistently shows 12 superior sectors in quadrant I (advanced and fast-growing sectors). While other regencies are only 3 sectors which are in quadrant I, other economic sectors are growing but depressed, there are also potential ones. In fact, Maros Regency and District. Takalar has 11 sectors that are still lagging behind. Based on the poverty mapping of districts / cities in the Mamminasata area, it shows that Makassar City and District. Gowa has an average number of poor people lower than South Sulawesi Province. Takalar Regency tends to be the same as South Sulawesi province, and there are paradoxical symptoms between GDP and poverty. Whereas Kab. Maros is above the poverty average of Prov. South Sulawesi. In aggregate poverty in the Mamminasata area declined during the study period. Makassar City, Kab. Gowa, Kab. Maros, even though the rate of growth declined, the number of poor people also declined. Whereas Takalar Regency has increased GDP but its poverty has also increased.

Pooling data in poverty mapping

2010 ◽  
Vol 108 (1) ◽  
pp. 77-80 ◽  
Author(s):  
Lei Pan
Keyword(s):  
Poverty Mapping

Poverty mapping in small areas under a twofold nested error regression model

2017 ◽  
Vol 180 (4) ◽  
pp. 1111-1136 ◽  
Author(s):  
Yolanda Marhuenda ◽  
Isabel Molina ◽  
Domingo Morales ◽  
J. N. K. Rao
Keyword(s):  
Regression Model ◽  
Small Areas ◽  
Poverty Mapping

Classification trees for poverty mapping

2017 ◽  
Vol 115 ◽  
pp. 53-66 ◽  
Author(s):  
Penny Bilton ◽  
Geoff Jones ◽  
Siva Ganesh ◽  
Steve Haslett
Keyword(s):  
Classification Trees ◽  
Poverty Mapping
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