Composite indicators convert information about different facets of a given phenomenon into a single figure. Unavoidably, the “conversion process” involves a high level of arbitrariness, which, in general, makes the results not robust. The approach to composite indicators used in this paper aims at mitigating this problem and makes final users more aware of the unavoidable uncertainty of the results (e.g. rankings) based on a given composite. We illustrate our approach by applying it to the Human Development Index.
Communicating the uncertainty of synthetic indicators: a reassessment of the HDI ranking
Luzzati, Tommaso;Cheli, Bruno;Gucciardi, Gianluca
2017-01-01
Abstract
Composite indicators convert information about different facets of a given phenomenon into a single figure. Unavoidably, the “conversion process” involves a high level of arbitrariness, which, in general, makes the results not robust. The approach to composite indicators used in this paper aims at mitigating this problem and makes final users more aware of the unavoidable uncertainty of the results (e.g. rankings) based on a given composite. We illustrate our approach by applying it to the Human Development Index.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Luzzati Cheli Gucciardi Disc_Paper_2017_final.pdf
accesso aperto
Tipologia:
Versione finale editoriale
Licenza:
Creative commons
Dimensione
2.67 MB
Formato
Adobe PDF
|
2.67 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
