- Open Access
Poverty in Tunisia: A Fuzzy measurement approach
Swiss Journal of Economics and Statistics volume 146, pages 431–450 (2010)
Although poverty is widely recognised as a multidimensional phenomenon, we still believe that monetary aspect has a fundamental role and therefore deserves a special treatment. For this reason we propose an individual unidimensional measure according to a fuzzy approach that, unlike conventional methods, is consistent with the vague nature of poverty and preserves all the available statistical information. Referred to the overall population, we use an Information Theory approach to design unidimensional fuzzy collective index. The methodology proposed here is illustrated by means of the Tunisia case.
Berenger, V., and A. Verdier-Chouchane (2007), “Multidimensional Measures of Well-Being: Standard of Living and Quality of Life Across Countries”, World Development, 35 (7), pp. 1259–1276.
Betti, G., G. Cheli and R. Cambini (2004), “A Statistical Model for The Dynamics Between Two Fuzzy States: Theory and Application to Poverty Analysis”, Metron, 62 (3), pp. 391–411.
Bourguignon, F., and S. R. Chakravarty (2003), “The Measurement of Multidimensional Poverty”, Journal of Economic Inequality, 1 (1), pp. 25–49.
Cerioli, A., and S. Zani (1990), “A Fuzzy Approach to the Measurement of Poverty”, in: C. Dagum and M. Zenga, (eds), Income and Wealth Distribution, Inequality and Poverty, Studies in Contemporary, Economics, Springer Verlag, Berlin, pp. 272–284.
Cheli, B. and A. Lemmi. (1995), “Totally Fuzzy and Relative Approach to the Multidimensional Analysis of Poverty”, Economic Notes, 24, pp. 115–134.
Chiappero Martinetti, E. (2000), “A Multidimensional Assessment of Well-Being Based on Sen’s Functioning Approach”, Rivista Internazionale di Scienze Sociali, 108, pp. 207–239.
Chiappero Martinetti, E. (2006), “Capability Approach and Fuzzy Set Theory: Description, Aggregation and Inference Issues”, in A. Lemmi and G. Betti (eds), Fuzzy Set Approach to Multidimensional Poverty Measurement, Springer + Business Media, LLC, New-York, pp. 139–153.
Dagum, C., R. Gambassi and A. Lemmi (1992), “New Approaches to the Measurement of Poverty. In Poverty Measurement of Economics in Transition”, Polish Statistical Association & Central Statistical Office, Warsaw.
Foster, J., J. Greer and E. Thorbecke (1984), “A Class of Decomposable Poverty Measures”, Econometrica, 52, pp. 761–765.
INS (1990), Enquête sur le budget et la consommation des ménages en Tunisie, Tunisian Institute of Statistics, Ministère du plan, Tunis.
Kakwani, N., and J. Silber (2008), Quantitative Approaches to Multidimensional Poverty Measurement, Palgrave Macmillan.
Kaufmann, A., and M. M. Gupta (1991), Introduction to Fuzzy Arithmetic, International Thomson Computer Press.
Massoumi, E. (1993), “A Compendium to Information Theory in Economics and Econometrics”, Econometric Reviews, 12 (2), pp. 137–181.
Ragin, C. C. (2000), Fuzzy Set Social Science, The University of Chicago Press, Chicago.
Ravallion, M. (1994), Poverty Comparisons, Fundamentals of Pure and Applied Economics Series, Harwood Academic Press, New York.
Ravallion, M. and B. Bidani (1994), “How Robust is a Poverty Profile?”, The Word Bank Economic Review.
Schaich, E., and R. (1996), “Der Fuzzy-Set-Ansatz in der Armutsmessung”, Jahrbücher für Nationalökonomie and Statistik, 215, pp. 444–469.
Sen, A. K. (1976), “Poverty: An Ordinal Approach to Measurement”, Econometrica, 44, pp. 219–231.
Shorroks, A. F. and S. Subramanian (1994), “Fuzzy Poverty Indices”, mimeo, University of Essex.
Theil, H. (1967), Economics and Information Theory, Rand McNally & Company, Chicago.
Watts, H. W. (1967), “The Iso-Prop Index: An Approach to the Determination of Differential Poverty Income Thresholds”, The Journal of Human Resources, 2, pp. 3–18.
Zadeh, L. (1965), “Probability Theory and Fuzzy Logic are Complementary rather than Competitive”, Technometrics, 37, pp. 271–276.
Zheng, B. (1997), “Aggregate Poverty Measures”, Journal of Economic Surveys, 11, pp. 123–162.
The researchers wish to thank the anonymous reviewers for their comments and reviews including all the important points raised.
About this article
Cite this article
Belhadj, B., Matoussi, M.S. Poverty in Tunisia: A Fuzzy measurement approach. Swiss J Economics Statistics 146, 431–450 (2010). https://doi.org/10.1007/BF03399322
- fuzzy sets
- poverty line
- membership function
- information function