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Multidimensional approaches to poverty measurement: an empirical analysis of poverty in Belgium, France, Germany, Italy and Spain, based on the European panel

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  • Conchita D'Ambrosio
  • Joseph Deutsch
  • Jacques Silber

Abstract

This article has three goals. First, we wish to compare three multidimensional approaches to poverty and check to what extent they identify the same households as poor. Second, we aim at better understanding the determinants of poverty by estimating logit regressions with five categories of explanatory variables: size of the household, age of the head of the household, her gender, marital status and status at work. Third, we introduce a decomposition procedure proposed recently in the literature, the so-called Shapley decomposition, in order to determine the exact marginal impact of each of the categories of explanatory variables. Our empirical analysis is based on data made available by the European Community Household Panel (ECHP). We used its third wave and selected five countries: Belgium, France, Germany, Italy and Spain.

Suggested Citation

  • Conchita D'Ambrosio & Joseph Deutsch & Jacques Silber, 2009. "Multidimensional approaches to poverty measurement: an empirical analysis of poverty in Belgium, France, Germany, Italy and Spain, based on the European panel," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 951-961.
  • Handle: RePEc:taf:applec:v:43:y:2009:i:8:p:951-961
    DOI: 10.1080/00036840802600129
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    References listed on IDEAS

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    1. F. Chantreuil & A. Trannoy, 1999. "Inequality decomposition values : the trade-off between marginality and consistency," THEMA Working Papers 99-24, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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    Cited by:

    1. Ramani Gunatilaka & Duangkamon Chotikapanich, 2006. "Inequality Trends and Determinants in Sri Lanka 1980-2002: A Shapley Approach to Decomposition," Monash Econometrics and Business Statistics Working Papers 6/06, Monash University, Department of Econometrics and Business Statistics.
    2. Maasoumi, Esfandiar & Lugo, Maria, 2006. "The Information Basis of Multivariate Poverty Assessments," Departmental Working Papers 0603, Southern Methodist University, Department of Economics.
    3. Francesco Devicienti & Valentina Gualtieri, 2007. "The Dynamics and Persistence of Poverty: Evidence from Italy," LABORatorio R. Revelli Working Papers Series 63, LABORatorio R. Revelli, Centre for Employment Studies.
    4. Maria Ana Lugo & Esfandiar Maasoumi, 2008. "Multidimensional Poverty Measures from an Information Theory Perspective," Working Papers 85, ECINEQ, Society for the Study of Economic Inequality.
    5. Eisenhauer, Joseph G., 2011. "The rich, the poor, and the middle class: Thresholds and intensity indices," Research in Economics, Elsevier, vol. 65(4), pages 294-304, December.

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