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Putting Robust Statistical Methods into Practice: Poverty Analysis in Tunisia

Ayadi, Mohamed
Matoussi, Mohamed Salah
Published in Swiss Journal of Economics and Statistics. 2001, vol. 3, no. 14, p. 463-482
Abstract Poverty analysis often results in the computation of poverty indexes based on so-called poverty lines which can be region speci…c poverty lines. The poverty lines are made of two components, namely the amount of income to satisfy the food and the non food needs. For both components, one needs to estimate quantities such as local prices or the consummers' average basket, and this is often done through a parametric model. The resulting estimates depend on the data at hand and on the type of estimators that are used. Classical estimators (and testing procedures) such as the maximumlikelihood estimator (MLE) or the least squares (LS) estimator are extremely sensitive to model deviations such as contamination in the data and hence are said not robust. The resulting analysis can therefore give a picture which is far from reality. Therefore a robust statistical approach to the estimation of the poverty lines is very important especially because these lines will serve to compute poverty indices. The main purpose of this paper is therefore to show how robust statistical procedure can be used in poverty analysis and the di¤erent picture on poverty comparisons they can give to the Tunisian case.
Keywords Poverty linesRobust estimationLocal pricesEvaluation of basic non food needsPoverty comparisons
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AYADI, Mohamed, MATOUSSI, Mohamed Salah, VICTORIA-FESER, Maria-Pia. Putting Robust Statistical Methods into Practice: Poverty Analysis in Tunisia. In: Swiss Journal of Economics and Statistics, 2001, vol. 3, n° 14, p. 463-482. https://archive-ouverte.unige.ch/unige:6453

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Deposited on : 2010-05-04

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