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The objective of measuring poverty is usually to make comparisons over time or between two or more groups. Comm on statistical inference methods are used to determine whether an apparent difference in measured poverty is statistically significant. Studies of relative poverty have long recognized that when the poverty line is calculated from sample survey data, both the variance of the poverty line and the variance of the welfare metric contribute to the variance of the poverty estimate. In contrast, studies using absolute poverty lines have ignored the poverty line variance, even when the poverty lines are estimated from sample survey data. Including the poverty line variance could either reduce or increase the precision of poverty estimates, depending on the s pecific characteristics of the data. This paper presents a general procedure for estimating the standard error of poverty measures when th e poverty line is estimated from survey data. Based on bootstrap methods, the approach can be used for a wide range of poverty measures and methods for estimating poverty lines. The method is applied to recent household survey data from Mozambique. When the sampling variance of the poverty line is taken into account, the estimated standard errors of the headcount and the poverty gap at the national level increase by 27 and 29 percent respectively.

Keywords: poverty measurement ; bootstrap ; Mozambique

Subject(s): Food Security and Poverty

Issue Date: 2006

Publication Type: Conference Paper/ Presentation

PURL Identifier: http://purl.umn.edu/25775

Total Pages: 16

JEL Codes: I32; C13; 012

Series Statement: Contributed Paper

Record appears in: International Association of Agricultural Economists (IAAE) > 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia





Autor: Simler, Kenneth R. ; Arndt, Channing

Fuente: http://ageconsearch.umn.edu/record/25775?ln=en



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