2012
DOI: 10.1007/s11205-012-0070-4
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An Unbalance Adjustment Method for Development Indicators

Abstract: This paper analyzes some aggregation aspects of the procedure for constructing a composite index on a multidimensional socio-economic phenomenon such as development, the main focus being on the unbalance among individual dimensions. First a theoretical framework is set up for the unbalance adjustment of the index. Then an aggregation function is proposed that takes unbalance among development dimensions into account; a separate index is also introduced that measures the unbalance itself. Finally the dataset of… Show more

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Cited by 100 publications
(15 citation statements)
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“…Normalization allows adjusting a series of values (typically representing a set of measurements) according to a transformation function to make them comparable with certain specific reference points. We proceeded with a min-max standardization (Casadio Tarabusi and Guarini, 2013) to obtain a positive resilience impact variable (Eq. 4) and a negative resilience impact variable (Eq.…”
Section: Methods and Tools For Resilience Assessmentmentioning
confidence: 99%
See 1 more Smart Citation
“…Normalization allows adjusting a series of values (typically representing a set of measurements) according to a transformation function to make them comparable with certain specific reference points. We proceeded with a min-max standardization (Casadio Tarabusi and Guarini, 2013) to obtain a positive resilience impact variable (Eq. 4) and a negative resilience impact variable (Eq.…”
Section: Methods and Tools For Resilience Assessmentmentioning
confidence: 99%
“…Nevertheless, in some case studies, urbanization has been shown to have other results and is one of main elements to be taken into account when building response capacity to risks (Garschagen and Romero-Lankao, 2015). This response capacity can be determined by flood preparedness (Chinh et al, 2016), government implication and risk governance (Garschagen, 2015). Studying the city in the face of risks and its resilience capacity requires considering different spatial scales of interactions and challenges.…”
Section: A Framework For Defining Resilience Data?mentioning
confidence: 99%
“…This quantitative data set is from the ISPF, a French Polynesian open data website (Table 3). To make this method as adaptable as possible, the statistical data is transformed into percentages and then standardized using Min-Max normalization [43] to homogenize data of different natures so that they can be compared using a similar measurement scale [32]. The values obtained range from 0 (very low resilience) to 1 (very high resilience).…”
Section: Urban and Social Resiliencementioning
confidence: 99%
“…The creation of composite indicators should be carried out with due diligence. The rules to be followed and stages of construction are presented in the literature; for example, see Zeliaś (2002), Saisana-Saltelli (2011), Casadio Tarabusi-Guarini (2013, and Mazziotta-Pareto (2013).…”
Section: Introductionmentioning
confidence: 99%