In this paper we estimate various measures of poverty and inequality for small administrative units in a Transition Country — Albania — and we prepare the corresponding maps. Poverty and inequality maps — spatial descriptions of the distribution of poverty and inequality — are most useful to policymakers and researchers when they are finely disaggregated, i.e. when they represent small geographic units, such as cities, municipalities, regions or other administrative partitions of a country. We aim at performing poverty and inequality mapping primarily using data from a Population Census, in conjunction with an intensive small scale national sample survey. The methodology adopted, described in Elbers, Lanjouw and Lanjouw (2003), combines census and survey information to produce finely disaggregated maps. The basic idea is to estimate a linear regression model with local variance components using information from the smaller and richer sample data - in the case of Albania the Living Standard Measurement Study (LSMS) conducted in 2002 — in conjunction with aggregate information from the 2001 Population and Housing Census. The main findings of research are potentially very useful for policymakers. We find that in Albania there is considerable heterogeneity of poverty rates across administrative units. The particular spatial pattern of this heterogeneity has important policy implications for poverty alleviation programmes: at the highest level we observe a large spatial heterogeneity among Prefectures; this spatial heterogeneity is much less pronounced among Districts within the same Prefecture; however, it is pronounced again at the lowest level among Municipalities within the same District. What this means for the practitioner and the policymaker is that it is important to disaggregate down to the Commune level when analysing issues and planning interventions, as this will add substantially in terms of precision of the targeting of resources when compared to stopping at the District level

Neri, L., Ballini, F., & Betti, G. (2005). Poverty and inequality mapping in transition countries. STATISTICS IN TRANSITION, 7(1), 135-157.

Poverty and inequality mapping in transition countries

NERI, LAURA;BETTI, GIANNI
2005

Abstract

In this paper we estimate various measures of poverty and inequality for small administrative units in a Transition Country — Albania — and we prepare the corresponding maps. Poverty and inequality maps — spatial descriptions of the distribution of poverty and inequality — are most useful to policymakers and researchers when they are finely disaggregated, i.e. when they represent small geographic units, such as cities, municipalities, regions or other administrative partitions of a country. We aim at performing poverty and inequality mapping primarily using data from a Population Census, in conjunction with an intensive small scale national sample survey. The methodology adopted, described in Elbers, Lanjouw and Lanjouw (2003), combines census and survey information to produce finely disaggregated maps. The basic idea is to estimate a linear regression model with local variance components using information from the smaller and richer sample data - in the case of Albania the Living Standard Measurement Study (LSMS) conducted in 2002 — in conjunction with aggregate information from the 2001 Population and Housing Census. The main findings of research are potentially very useful for policymakers. We find that in Albania there is considerable heterogeneity of poverty rates across administrative units. The particular spatial pattern of this heterogeneity has important policy implications for poverty alleviation programmes: at the highest level we observe a large spatial heterogeneity among Prefectures; this spatial heterogeneity is much less pronounced among Districts within the same Prefecture; however, it is pronounced again at the lowest level among Municipalities within the same District. What this means for the practitioner and the policymaker is that it is important to disaggregate down to the Commune level when analysing issues and planning interventions, as this will add substantially in terms of precision of the targeting of resources when compared to stopping at the District level
Neri, L., Ballini, F., & Betti, G. (2005). Poverty and inequality mapping in transition countries. STATISTICS IN TRANSITION, 7(1), 135-157.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/9657
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