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The Information Basis of Multivariate Poverty Assessments

  • Maasoumi, Esfandiar

    ()

    (SMU)

  • Lugo, Maria

    (University of Oxford)

Measures of multivariate well-being, such as poverty or inequality, are scalar functions of matrices of several attributes, m, associated with a number of individual or households, N. This entails inevitable “aggregation” and summarization over individuals as well as attributes. There is no escape from this. Such aggregation, in turn, implies a set of weights attached to each individual, and some normative decision on how they relate. The aggregation over the attributes also forces decisions about the weight to be given to each attribute and the relation between the attributes as, perhaps, substitutes or complements. We argue in favor of information theory aggregation methods which are explicit about such normative choices, and help place other methods in this realistic context. According to axiomatically well developed measures of divergence in information theory, our measures are “ideal” and other methods are therefore sub-optimal. The advocacy of the latter must be accompanied by well argued positions in support of special properties and other considerations which may be compelling in a given context or application.

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Paper provided by Southern Methodist University, Department of Economics in its series Departmental Working Papers with number 0603.

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Length: 26 pages
Date of creation: Jun 2006
Date of revision:
Handle: RePEc:smu:ecowpa:0603
Contact details of provider: Postal: Department of Economics, P.O. Box 750496, Southern Methodist University, Dallas, TX 75275-0496
Phone: 214-768-2715
Fax: 214-768-1821
Web page: http://www.smu.edu/economics

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  1. Kai-yuen Tsui, 2002. "Multidimensional poverty indices," Social Choice and Welfare, Springer, vol. 19(1), pages 69-93.
  2. Sami Bibi, 2004. "Comparing Multidimensional Poverty between Egypt and Tunisia," Cahiers de recherche 0416, CIRPEE.
  3. 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.
  4. Ebrahimi, Nader & Maasoumi, Esfandiar & Soofi, Ehsan S., 1999. "Ordering univariate distributions by entropy and variance," Journal of Econometrics, Elsevier, vol. 90(2), pages 317-336, June.
  5. A. Atkinson, 2003. "Multidimensional Deprivation: Contrasting Social Welfare and Counting Approaches," Journal of Economic Inequality, Springer, vol. 1(1), pages 51-65, April.
  6. Strauss, J. & Thomas, D., 1995. "Health, Nutrition and Economic development," Papers 95-23, RAND - Labor and Population Program.
  7. Joseph Deutsch & Jacques Silber, 2005. "Measuring Multidimensional Poverty: An Empirical Comparison Of Various Approaches," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(1), pages 145-174, 03.
  8. Maasoumi, Esfandiar, 1986. "The Measurement and Decomposition of Multi-dimensional Inequality," Econometrica, Econometric Society, vol. 54(4), pages 991-97, July.
  9. Sudhir Anand & Amartya Sen, 2000. "The Income Component of the Human Development Index," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 1(1), pages 83-106.
  10. François Bourguignon & Satya Chakravarty, 2003. "The Measurement of Multidimensional Poverty," Journal of Economic Inequality, Springer, vol. 1(1), pages 25-49, April.
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