The multidimensional measurement of poverty: a fuzzy set approach


  • Michele Costa Alma Mater Studiorum - Università di Bologna
  • Luca De Angelis Alma Mater Studiorum - Università di Bologna



By using fuzzy set theory a multidimensional analysis of poverty of Italian households is performed on the basis of SHIW data. A set of composite indicators is constructed in order to analyze different dimensions of poverty. For each indicator is calculated an unidimensional poverty ratio, thus allowing a comparison among indicators on the dimensions of poverty. Finally, a multidimensional poverty ratio is obtained.


G. BETTI, B. CHELI, R. GAMBINI, (2004), A statistical model for the dynamics between two fuzzy states: theory and an application to poverty analysis, “Metron”, 62, pp. 391-411.

G. BETTI, V. VERMA, (1999), Measuring the degree of poverty in a dynamic and comparative context: a multidimensional approach using fuzzy set theory, “Proceedings ICCS-VI, Lahore, Pakistan”, 11, pp. 289-301.

F. BOURGUIGNON, S.R. CHAKRAVARTY, (2003), The measurement of multidimensional poverty, “Journal of Economic Inequality”, 1, pp. 25-49.

A. BRANDOLINI, L. CANNARI, (1994), Methodological appendix: the Bank of Italy’s survey of household income and wealth, in A. ANDO, L. GUISO, I. VISCO (eds.), Saving and the Accumulation of Wealth: Essays on Italian Household and Government Saving Behavior, Cambridge University Press, Cambridge, UK, pp. 369-386.

G. CARBONARO, (1985), Nota sulla scala di equivalenza, in COMMISSIONE DI INDAGINE SULLA POVERTÀ, Studi di base, Presidenza del Consiglio dei Ministri, Roma.

G. CARBONARO, (2002), Studi sulla povertà: problemi di misura e analisi comparative, Franco Angeli, Milano.

A. CERIOLI, S. ZANI, (1990), A fuzzy approach to the measurement of poverty, in C. DAGUM, M. ZENGA (eds.), Income and wealth distribution, inequality and poverty, Springer Verlag, Berlin, pp. 272-284.

B. CHELI, A. LEMMI, (1995), A totally fuzzy and relative approach to the multdimensional analysis of poverty, “Economic Notes”, 24, pp. 115-134.

B. CHELI, G. GHELLINI, A. LEMMI, N. PANNUZI, (1994), Measuring poverty in the countries in transition via TFR method: the case of Poland in 1990-1991, “Statistics in Transition”, 1, pp. 585-636.

M. COSTA, (2002), A multidimensional approach to the measurement of poverty, IRISS working paper n. 2002-05, CEPS/INSTEAD, Luxembourg.

C. DAGUM, (1989), Poverty as perceived by the Leyden evaluation project. A survey of Hagenaars’ contribution on the perception of poverty, Economic Notes, 1, pp. 99-110.

C. DAGUM, (1995a), Income inequality measures and social welfare functions: a unified approach, in C.

DAGUM, A. LEMMI (eds.), Income distribution, inequality and poverty, Research on Income Inequality, vol. 6, JAI Press, CN, USA, pp. 177-199.

C. DAGUM, (1995b), The scope and method of economics as a science, “Il Politico”, University of Pavia, 60, pp. 5-39.

C. DAGUM, (2001), Desigualdad del rédito y bienestar social, descomposiciòn, distancia direccional y distancia métrica entre distribuciones, “Estudios de Economìa Aplicada”, 17, pp. 2-52.

C. DAGUM, M. COSTA, (2004), A fuzzy approach to the measurement of poverty, in C. DAGUM, G. FERRARI (eds.), Income and wealth distribution, inequality and poverty, Springer Verlag, Berlin, pp. 272-284.

C. DAGUM, R. GAMBASSI, A. LEMMI (1992), New approaches to the measurement of poverty, Poverty Measurement for Economies in Transition in Eastern European Countries, Polish Statistical Association and Central Statistical Office, Warsaw, pp. 201-225.

J. DEUTSCH, J. SILBER, (2005), Measuring multidimensional poverty: an empirical comparison of various approaches, “Review of Income and Wealth”, 51, pp. 145-174.

D. DUBOIS, H. PRADE, (1980), Fuzzy sets and systems: theory and applications, Academic Press, Boston.

A.J.M. HAAGENARS, (1986), The perception of poverty, North Holland, Amsterdam.

N. KAKWANI, J. SILBER, (2008a), Introduction: multidimensional poverty analysis: conceptual issues, empirical illustrations and policy implications, “World Development”, 6, pp. 987-991.

N. KAKWANI, J. SILBER (eds.), (2008b), Quantitative approaches to multidimensional poverty measurement, Palgrave Macmillan, London.

A. LEMMI, G. BETTI (eds.), (2006), Fuzzy set approach to multidimensional poverty measurement, Springer, Berlin.

E.C. MARTINETTI, (1994), A new approach to the evaluation of well-being and poverty by fuzzy set theory, “Giornale degli economisti e annali di economia”, 53, pp. 367-388.

S. MUSSARD, M.N. PI ALPERIN, (2008), Inequalities in multidimensional poverty: evidence from Argentina, “Applied Economics Letters”, 15, pp. 759-765.

A.K. SEN, (1985), Commodities and capabilities, Elsevier, Amsterdam and reprinted in A.K. SEN, (1999), Commodities and Capabilities, Oxford University Press, New Delhi.

A.K. SEN, (1992), Inequality reexamined, Harvard University Press, Cambridge (MA).

H. SILVER, (1995), Reconceptualizing social disadvantage: three paradigms of social exclusion, in HG.

RODGERS, C. GORE, J.B. FIGUREREIDO (eds.), Social exclusion: rhetoric, reality, responses, International Labor Office, Geneva, pp. 57-80.

L.A. ZADEH, (1965), Fuzzy sets, “Information and Control”, 8, pp. 338-353.




How to Cite

Costa, M., & De Angelis, L. (2008). The multidimensional measurement of poverty: a fuzzy set approach. Statistica, 68(3/4), 303–319.