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The Information Basis of Multivariate Poverty Assessments

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  • Maasoumi, Esfandiar

    () (SMU)

  • Lugo, Maria

    (University of Oxford)

Abstract

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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Bibliographic Info

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

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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. John Strauss & Duncan Thomas, 1998. "Health, Nutrition, and Economic Development," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 766-817, June.
  2. 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 and Francis Journals, vol. 43(8), pages 951-961.
  3. Kai-yuen Tsui, 2002. "Multidimensional poverty indices," Social Choice and Welfare, Springer, vol. 19(1), pages 69-93.
  4. François Bourguignon & Satya Chakravarty, 2003. "The Measurement of Multidimensional Poverty," Journal of Economic Inequality, Springer, vol. 1(1), pages 25-49, April.
  5. Sudhir Anand & Amartya Sen, 2000. "The Income Component of the Human Development Index," Journal of Human Development and Capabilities, Taylor and Francis Journals, vol. 1(1), pages 83-106.
  6. 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.
  7. Maasoumi, Esfandiar, 1986. "The Measurement and Decomposition of Multi-dimensional Inequality," Econometrica, Econometric Society, vol. 54(4), pages 991-97, July.
  8. A. Atkinson, 2003. "Multidimensional Deprivation: Contrasting Social Welfare and Counting Approaches," Journal of Economic Inequality, Springer, vol. 1(1), pages 51-65, April.
  9. Bourguignon, F. & Chakravarty, S.R., 1998. "A Family of Multidimensional Poverty Measures," DELTA Working Papers 98-03, DELTA (Ecole normale supérieure).
  10. 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.
  11. Sami Bibi, 2004. "Comparing Multidimensional Poverty between Egypt and Tunisia," Cahiers de recherche 0416, CIRPEE.
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Cited by:
  1. Merz, Joachim & Rathjen, Tim, 2011. "Intensity of Time and Income Interdependent Multidimensional Poverty: Well-Being and Minimum 2DGAP – German Evidence," IZA Discussion Papers 6022, Institute for the Study of Labor (IZA).
  2. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
  3. Awan, Masood Sarwar & Waqas, Muhammad & Aslam, Muhammad Amir, 2011. "Multidimensional Poverty in Pakistan: Case of Punjab Province," MPRA Paper 32875, University Library of Munich, Germany.
  4. M. Lasso de la Vega & Ana Urrutia, 2011. "Characterizing how to aggregate the individuals’ deprivations in a multidimensional framework," Journal of Economic Inequality, Springer, vol. 9(2), pages 183-194, June.
  5. Sabina Alkire, 2011. "Multidimensional Poverty and its Discontents," OPHI Working Papers ophiwp046, Queen Elizabeth House, University of Oxford.
  6. Francisco Ferreira & Maria Ana Lugo, 2012. "Multidimensional poverty analysis: Looking for a middle ground," Working Papers 251, ECINEQ, Society for the Study of Economic Inequality.
  7. Esfandiar Maasoumi & Jeffrey S. Racine, 2013. "Multidimensional Poverty Frontiers: Parametric Aggregators Based on Nonparametric Distributions," Department of Economics Working Papers 2013-07, McMaster University.
  8. Mª Casilda Lasso de la Vega & Ana Urrutia & Henar Diez, 2009. "The Bourguignon and Chakravarty multidimensional poverty family: A characterization," Working Papers 109, ECINEQ, Society for the Study of Economic Inequality.
  9. Stefanescu, Stefan V., 2011. "About the Accuracy of Gini Index for Measuring the Poverty," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 255-266, September.
  10. Christopher J. Bennett and Shabana Mitra, 2011. "Multidimensional Poverty: Measurement, Estimation, and Inference," OPHI Working Papers ophiwp047, Queen Elizabeth House, University of Oxford.
  11. Chakravarty, Satya R. & Deutsch, Joseph & Silber, Jacques, 2008. "On the Watts Multidimensional Poverty Index and its Decomposition," World Development, Elsevier, vol. 36(6), pages 1067-1077, June.
  12. Masood, Sarwar Awan & Muhammad, Waqas & Amir, Aslam, 2012. "Multidimensional Measurement of Poverty in Pakistan," MPRA Paper 41532, University Library of Munich, Germany.
  13. Masood, Sarwar & Muhammad, Waqas & Amir, Aslam, 2012. "Multidimensional Measurement of Poverty in Pakistan: Provincial Analysis," MPRA Paper 42119, University Library of Munich, Germany.
  14. Qi Li & Juan Lin & Jeffrey S. Racine, 2013. "Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions," Journal of Business & Economic Statistics, American Statistical Association, vol. 31(1), pages 57-65, January.
  15. Diego Battiston & Guillermo Cruces & Luis Felipe Lopez Calva & Maria Ana Lugo & Maria Emma Santos, 2009. "Income and Beyond: Multidimensional Poverty in six Latin American countries," CEDLAS, Working Papers 0090, CEDLAS, Universidad Nacional de La Plata.

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