Advertisement

The “Fuzzy Set” Approach to Multidimensional Poverty Analysis: Using the Shapley Decomposition to Analyze the Determinants of Poverty in Israel

  • Joseph Deutsch
  • Jacques Silber
Part of the Economic Studies in Inequality, Social Exclusion and Well-Being book series (EIAP, volume 3)

Keywords

Logit Regression Membership Function Poor Household Durable Good Poverty Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. Cerioli A, Zani S (1990) A Fuzzy Approach to the Measurement of Poverty. In: Dagum C, Zenga M (eds) Income and Wealth Distribution, Inequality and Poverty, Studies in Contemporary Economics. Springer, Berlin Heidelberg, New York, pp 272–284Google Scholar
  2. Chantreuil F, Trannoy A (1999) Inequality Decomposition Values: The Trade-Off Between Marginality and Consistency. THEMA Discussion Paper, Université de Cergy-PontoiseGoogle Scholar
  3. Cheli B, Ghellini G, Lemmi A, Pannuzi N (1994) Measuring Poverty in the Countries in Transition via TFR Method: The Case of Poland In 1990–1991. Statistics in Transition 1:585–636Google Scholar
  4. Cheli B, Lemmi A (1995) A “Totally” Fuzzy and Relative Approach to the Multidimensional Analysis of Poverty. Economic Notes 24:115–134Google Scholar
  5. Ragin CC (2000) Fuzzy-Set Social Science. The University of Chicago Press, ChicagoGoogle Scholar
  6. Sastre M, Trannoy A (2002) Shapley Inequality Decomposition by Factor Components: Some Methodological Issues. Joumal of Economics Supplement 9:51–89zbMATHGoogle Scholar
  7. Shorrocks AF (1999) Decomposition Procedures for Distributional Analysis: A Unified Framework Based on the Shapley Value. Mimeo, University of EssexGoogle Scholar
  8. Silber J (1999) Handbook on Income Inequality Measurement. Kluwer Academic Publishers, Dordrecht and BostonGoogle Scholar
  9. Sorin M (1999) Multidimensional Poverty Analysis. Using the Fuzzy Sets Theory. MA Thesis, Department of Economics, Bar-Ilan University, Ramat-Gan, IsraelGoogle Scholar
  10. Vero J (2002) Mesurer la pauvreté à partir des concepts de biens premiers, de réalisations primaires et de capabilités de base. Thèse de doctorat, Ecole des Hautes Etudes en Sciences Sociales, Groupement de Recherche en Economie Quantitative d’Aix-Marseille (GREQAM)Google Scholar
  11. Vero J, Werquin P (1997) Reexamining the Measurement of Poverty: How Do Young People in the Stage of Being Integrated in the Labor Force Manage (in French). Economie et Statistique 8–10:143–156Google Scholar
  12. Zadeh LA (1965) Fuzzy Sets. Information and Control 8:338–353zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Joseph Deutsch
    • 1
  • Jacques Silber
    • 1
  1. 1.Department of EconomicsBar-Ilan UniversityIsrael

Personalised recommendations