SPATIAL DISTRIBUTION OF POVERTY AT DIFFERENT SCALES

Yıl 2010, Cilt: 2 Sayı: 1, 25 - 33, 01.06.2010

Gandhi Pawıtan

Öz

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.

Anahtar Kelimeler

poverty, mapping, spatial autocorrelation, geographical weighted regression.

Kaynakça

• Anselin, L. (1988): Spatial Econometrics, Methods and Models. Dordrecht: Kluwer.
• Atkinson, A. (1987): On the measurement of poverty. Econometrica, 55(4), 749- 764.
• Atkinson, P. M., & Tate, N. J. (2000): Spatial scale problems and geostatistical solutions: A review. The Professional Geographer, 52(4), 607-623.
• Center For International Earth Science Information Network. (2006): Catalog of small area estimates of poverty and inequality. Columbia University.
• Demombynes, G., Elbers, C., Lanjouw, J., Lanjouw, P., Mistiaen, J., & Zler, B. (2002): Producing an improved geographic profile of poverty : Methodology and evidence from three developing countries (Discussion paper No. 2002/39). United Nation University and World Institute for
• Development Economics Research. Foster, J., Greer, J., & Thorbecke, E. (1984): Notes and comments a class of decomposable poverty measures. Econometrica, 52(3), 761-766.
• Fotheringham, A., Brundson, C., & Charlton, M. (2002): Geographically weighted regression, the analysis of spatially varying relationships. John Wiley & Sons.
• Gehlke, C. E., & Biehl, K. (1934): Certain effects of Grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association, (supplement), 169-170.
• Holt, D., Steel, D. G., & Tranmer, M. (1996): Area Homogeneity and the Modifiable Areal Unit Problem. Geographical System, 2, 83-101.
• Jolliffe, D. (2006): Poverty, prices, and place: How sensitive is the spatial distribution of poverty to cost of living adjustments? Economic Inquiry, 44(2), 296-310.
• Minot, N., & Baulch, B. (2005a): Poverty mapping with aggregate census data:What is the loss in precision? Review of Development Economics, 9(1), 524.
• Minot, N., & Baulch, B. (2005b): Spatial patterns of poverty in Vietnam and their implications for policy. Food Policy, 30, 461-475.
• Openshaw, S. (1984): Ecological Fallacies and the Analysis of Areal Census Data. Environment and Planning A, 6, 17-31.