Most of the methods designed for the analysis of poverty share two main limitations: i) they are unidimensional, i.e. they refer to only one proxy of poverty, namely equivalent income or consumptionexpenditure; ii) they need to dichotomise the population into the poorand the non poorby means of the so called poverty line. This reductionism simplifies the analysis, but also wipes out all the complexity of this phenomenon which, on the contrary, should also be object of study. The Totally Fuzzy and Relative(TFR) approach proposed by Cheli and Lemmi (1995) allows us to overcome these limitations and to analyse poverty in a multidimensional perspective avoiding the use of arbitrary threshold values.In this paper we aimto remark how the binary distinction between the “poor” and “non poor”statesis too sharp, since deprivation is likely to occur by degrees. Starting from this consideration, we retrace and update the fuzzy sets approach for measuring multidimensional poverty, which leads to the Integrated Fuzzy and Relative method(Betti et al., 2006a, 2006b, 2008).

### From the TFR to the IFR approach for the multidimensional analysis of poverty and living conditions

#### Abstract

Most of the methods designed for the analysis of poverty share two main limitations: i) they are unidimensional, i.e. they refer to only one proxy of poverty, namely equivalent income or consumptionexpenditure; ii) they need to dichotomise the population into the poorand the non poorby means of the so called poverty line. This reductionism simplifies the analysis, but also wipes out all the complexity of this phenomenon which, on the contrary, should also be object of study. The Totally Fuzzy and Relative(TFR) approach proposed by Cheli and Lemmi (1995) allows us to overcome these limitations and to analyse poverty in a multidimensional perspective avoiding the use of arbitrary threshold values.In this paper we aimto remark how the binary distinction between the “poor” and “non poor”statesis too sharp, since deprivation is likely to occur by degrees. Starting from this consideration, we retrace and update the fuzzy sets approach for measuring multidimensional poverty, which leads to the Integrated Fuzzy and Relative method(Betti et al., 2006a, 2006b, 2008).
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Cheli, Bruno; Lemmi, Achille; Pannuzi, Nicoletta; Regoli, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: `https://hdl.handle.net/11568/1021264`
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