Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions

In recent decades, the measurement and evaluation of important social and natural phenomena has significantly evolved, with many traditional measurements based on single variables increasingly being replaced by multidimensional approaches. One key aspect of these approaches is the development of com...

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Autores principales:	Vincenzo Mauro, Caterina Giusti, Stefano Marchetti, Monica Pratesi
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	62-08 62P12 62P25 Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/ca84ceda1d7345619d1dbf7731769e7c
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spelling	oai:doaj.org-article:ca84ceda1d7345619d1dbf7731769e7c2021-12-01T04:52:27ZDoes uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions1470-160X10.1016/j.ecolind.2021.107740https://doaj.org/article/ca84ceda1d7345619d1dbf7731769e7c2021-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21004052https://doaj.org/toc/1470-160XIn recent decades, the measurement and evaluation of important social and natural phenomena has significantly evolved, with many traditional measurements based on single variables increasingly being replaced by multidimensional approaches. One key aspect of these approaches is the development of composite indexes, usually real-value functions of multiple achievements of a group of units. The achievements in each of the selected dimensions are generally synthesised through one or more variables, often referred to as indicators. When indicators are obtained through an estimation process, it is crucial to understand if and how their estimation error – for example, sampling error – affects the resulting composite index.This paper presents a methodology based on a parametric bootstrap technique that evaluates to what extent uncertainty in indicators affects the reliability of the aggregate composite index. The method is applied to four composite indexes measuring the environmental performances of Italian regions based on real population and survey data.To our knowledge, this is the first attempt to measure the impact of indicators’ sampling error on composite indexes. If adequately generalised, our methodology could be used in the presence of measurement errors, non-response issues, or other kinds of non-sampling errors.Vincenzo MauroCaterina GiustiStefano MarchettiMonica PratesiElsevierarticle62-0862P1262P25EcologyQH540-549.5ENEcological Indicators, Vol 127, Iss , Pp 107740- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	62-08 62P12 62P25 Ecology QH540-549.5
spellingShingle	62-08 62P12 62P25 Ecology QH540-549.5 Vincenzo Mauro Caterina Giusti Stefano Marchetti Monica Pratesi Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
description	In recent decades, the measurement and evaluation of important social and natural phenomena has significantly evolved, with many traditional measurements based on single variables increasingly being replaced by multidimensional approaches. One key aspect of these approaches is the development of composite indexes, usually real-value functions of multiple achievements of a group of units. The achievements in each of the selected dimensions are generally synthesised through one or more variables, often referred to as indicators. When indicators are obtained through an estimation process, it is crucial to understand if and how their estimation error – for example, sampling error – affects the resulting composite index.This paper presents a methodology based on a parametric bootstrap technique that evaluates to what extent uncertainty in indicators affects the reliability of the aggregate composite index. The method is applied to four composite indexes measuring the environmental performances of Italian regions based on real population and survey data.To our knowledge, this is the first attempt to measure the impact of indicators’ sampling error on composite indexes. If adequately generalised, our methodology could be used in the presence of measurement errors, non-response issues, or other kinds of non-sampling errors.
format	article
author	Vincenzo Mauro Caterina Giusti Stefano Marchetti Monica Pratesi
author_facet	Vincenzo Mauro Caterina Giusti Stefano Marchetti Monica Pratesi
author_sort	Vincenzo Mauro
title	Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
title_short	Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
title_full	Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
title_fullStr	Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
title_full_unstemmed	Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions
title_sort	does uncertainty in single indicators affect the reliability of composite indexes? an application to the measurement of environmental performances of italian regions
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/ca84ceda1d7345619d1dbf7731769e7c
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Does uncertainty in single indicators affect the reliability of composite indexes? An application to the measurement of environmental performances of Italian regions

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