A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe

Stefania Capecchi () and Rosaria Simone ()
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Stefania Capecchi: University of Naples Federico II
Rosaria Simone: University of Naples Federico II

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2019, vol. 141, issue 1, No 4, 95-110

Abstract: Abstract In social sciences the need often arises to compare and rank groups of respondents by analyzing huge amounts of data and composite indicators are amongst the most effective tools. The paper aims to design an original procedure suitable for ordinal data and able to synthesize subjective evaluations while accounting for both agreement and heterogeneity in response patterns. A composite indicator for ordinal data based on cub models is introduced: the proposal discloses and preserves the heterogeneity also at an aggregated level. Empirical evidence relies on perceived discrimination analysis stemming from the Special Eurobarometer Survey 2015.

Keywords: Composite indicators; Ordinal data; Heterogeneity; cub models; Perceived discrimination (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11205-018-1848-9

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