The paper suggests the use of the functional data analysis approach to study the evolution of well being indicators, visualizing their behaviour over time. Thus, an evolutionary wellbeing indicator is proposed by complement the original data with information concerning the first derivative. The second task is to provide an overall ranking of the countries over time using two functional tools: the area under the curve and functional depth, which return two distinct rankings. A simulation study is conducted to evaluate the effectiveness of the area in distinguishing groups of countries with different levels of well-being. The proposed method is employed on a real dataset concerning the human development index of European countries.

Fortuna, F., Naccarato, A., Terzi, S. (2022). Country rankings according to well-being evolution: composite indicators from a functional data analysis perspective. ANNALS OF OPERATIONS RESEARCH, 1-18 [10.1007/s10479-022-05072-w].

Country rankings according to well-being evolution: composite indicators from a functional data analysis perspective

Fortuna, Francesca
;
Naccarato, Alessia;Terzi, Silvia
2022-01-01

Abstract

The paper suggests the use of the functional data analysis approach to study the evolution of well being indicators, visualizing their behaviour over time. Thus, an evolutionary wellbeing indicator is proposed by complement the original data with information concerning the first derivative. The second task is to provide an overall ranking of the countries over time using two functional tools: the area under the curve and functional depth, which return two distinct rankings. A simulation study is conducted to evaluate the effectiveness of the area in distinguishing groups of countries with different levels of well-being. The proposed method is employed on a real dataset concerning the human development index of European countries.
2022
Fortuna, F., Naccarato, A., Terzi, S. (2022). Country rankings according to well-being evolution: composite indicators from a functional data analysis perspective. ANNALS OF OPERATIONS RESEARCH, 1-18 [10.1007/s10479-022-05072-w].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/422812
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