dc.contributor.author |
Pawitan, Gandhi |
|
dc.date.accessioned |
2020-12-18T06:55:06Z |
|
dc.date.available |
2020-12-18T06:55:06Z |
|
dc.date.issued |
2010 |
|
dc.identifier.issn |
1309-8055 |
|
dc.identifier.other |
artsc524 |
|
dc.identifier.uri |
http://hdl.handle.net/123456789/11406 |
|
dc.description |
INTERNATIONAL JOURNAL OF ECONOMICS AND FINANCE STUDIES; Vol.2 No.1 2010. p. 25-33. |
en_US |
dc.description.abstract |
Poverty mapping is usually developed from some sources of data, such as from census and survey data. In some practical application, the poverty was measured usually by household income or expenditure of daily basic consumption.
Using different scales and zoning on a particular set of spatial data may leads to problems in interpreting the results. In practice, organizations publish statistics and maps at a particular area level. Minot and Baulch (2005a) discussed some consequences of using aggregated level data in poverty mapping, which may affect the validity of the output.
The key point of this paper is to compare spatial distribution of the poverty at two different scale, which is the province and district level. How the spatial distribution of the poverty at province level can be use to infer the distribution at the district level. The geographical weighted regression will be applied, and the poverty data of Vietnam will be used as an illustration. |
en_US |
dc.description.uri |
https://sobiad.org/ijefs-vol-2-issue-1-2-2010/ |
|
dc.language.iso |
en |
en_US |
dc.publisher |
The Social Sciences Research Society |
en_US |
dc.subject |
POVERTY |
en_US |
dc.subject |
MAPPING |
en_US |
dc.subject |
SPATIAL AUTOCORRELATION |
en_US |
dc.subject |
GEOGRAPHICAL WEIGHTED REGRESSION |
en_US |
dc.title |
Spatial Distribution of Poverty at Different Scales |
en_US |
dc.type |
Journal Articles |
en_US |