A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe
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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.
KeywordsComposite indicators Ordinal data Heterogeneity cub models Perceived discrimination
This research has been partially funded by the CUBREMOT project (code: RBFR12SHVV) of the University of Naples Federico II, Italy. Authors thank very much Editor and Anonymous Referees for their critical comments and suggestions.
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