This paper proposes a comparison between uni- and multidimesional approaches to the measurement of poverty. Traditional uni-, fuzzy uni- and fuzzy multidimensional indicators are compared by means of a rank correlation analysis. The robustness of the comparison is ensured by a simulation study. Our results stress that unidimensional indicators provide partial information on the poverty condition.
M. Costa (2020). Multidimensional versus unidimensional poverty measurement. London : Pearson.
Multidimensional versus unidimensional poverty measurement
M. Costa
2020
Abstract
This paper proposes a comparison between uni- and multidimesional approaches to the measurement of poverty. Traditional uni-, fuzzy uni- and fuzzy multidimensional indicators are compared by means of a rank correlation analysis. The robustness of the comparison is ensured by a simulation study. Our results stress that unidimensional indicators provide partial information on the poverty condition.File in questo prodotto:
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