Romina Cavatassi (Agricultural and Development Economics Division, Food and Agriculture Organization) Benjamin Davis (Agricultural and Development Economics Division, Food and Agriculture Organization) Leslie Lipper (Agricultural and Development Economics Division, Food and Agriculture Organization)
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This paper presents the construction of a spatially explicit, nationally disaggregated measure of poverty over time in Costa Rica. The paper first describes the two possible methods considered for the construction of a poverty map: principal component analysis (PCA) versus small area estimation. Next, reasons for choosing PCA and a description of its application both at one point in time (1973) and over time are presented together with the resulting poverty maps. The methodology applied represents a methodological innovation in that the resulting poverty map is time variant rather than concentrated in a single moment in time. A comparison of the results obtainable using various techniques and a discussion on the relative merits of the various options available concludes the paper.
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Paper provided by Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA) in its series Working Papers with number
04-21.
Length: 29 pages Date of creation: 2004 Date of revision: Handle: RePEc:fao:wpaper:0421
Contact details of provider: Postal: Agricultural Sector in Economic Development Service FAO Viale delle Terme di Caracalla 00153 Rome Italy Phone: +39(6) 57051 Fax: +39 06 57055522 Email: Web page: http://www.fao.org/es/esa/ More information through EDIRC
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Find related papers by JEL classification: C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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