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

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  • Stefania Capecchi

    (University of Naples Federico II)

  • Rosaria Simone

    (University of Naples Federico II)

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.

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  • Stefania Capecchi & Rosaria Simone, 2019. "A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 95-110, January.
    • Handle: RePEc:spr:soinre:v:141:y:2019:i:1:d:10.1007_s11205-018-1848-9
    DOI: 10.1007/s11205-018-1848-9
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    References listed on IDEAS

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    1. Stefania Capecchi & Maria Iannario & Rosaria Simone, 2018. "Well-Being and Relational Goods: A Model-Based Approach to Detect Significant Relationships," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 729-750, January.
    2. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 476-487, August.
    3. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    4. Maria Iannario & Domenico Piccolo, 2016. "A comprehensive framework of regression models for ordinal data," METRON, Springer;Sapienza Università di Roma, vol. 74(2), pages 233-252, August.
    5. Fernando Molero & Patricia Recio & Cristina García-Ael & María Fuster & Pilar Sanjuán, 2013. "Measuring Dimensions of Perceived Discrimination in Five Stigmatized Groups," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(3), pages 901-914, December.
    6. Filomena Maggino & Marco Fattore & Alberto Arcagni, 2015. "Exploiting Ordinal Data for Subjective Well-Being Evaluation," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(3), pages 409-428, September.
    7. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    8. Stefania Capecchi & Domenico Piccolo, 2017. "Dealing with heterogeneity in ordinal responses," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2375-2393, September.
    9. Maria Iannario, 2010. "On the identifiability of a mixture model for ordinal data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 87-94.
    10. Baert, Stijn, 2017. "Hiring Discrimination: An Overview of (Almost) All Correspondence Experiments Since 2005," IZA Discussion Papers 10738, Institute of Labor Economics (IZA).
    11. Domenico Piccolo, 2015. "Inferential Issues on CUBE Models with Covariates," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(23), pages 5023-5036, December.
    12. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
    13. Matteo Mazziotta & Adriano Pareto, 2016. "Methods for Constructing Non-Compensatory Composite Indices: A Comparative Study," Forum for Social Economics, Taylor & Francis Journals, vol. 45(2-3), pages 213-229, August.
    14. D'Elia, Angela & Piccolo, Domenico, 2005. "A mixture model for preferences data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 917-934, June.
    15. Marco Fattore, 2016. "Partially Ordered Sets and the Measurement of Multidimensional Ordinal Deprivation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(2), pages 835-858, September.
    16. Francesca Giambona & Erasmo Vassallo, 2014. "Composite Indicator of Social Inclusion for European Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(1), pages 269-293, March.
    17. Lieselotte Blommaert & Marcel Coenders & Frank Tubergen, 2014. "Ethnic Discrimination in Recruitment and Decision Makers’ Features: Evidence from Laboratory Experiment and Survey Data using a Student Sample," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(3), pages 731-754, May.
    18. Marco Fattore & Filomena Maggino & Alberto Arcagni, 2015. "Exploiting Ordinal Data For Subjective Well-Being Evaluation," Statistics in Transition New Series, Polish Statistical Association, vol. 16(3), pages 409-428, September.
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    Cited by:

    1. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    2. Ribecco, Nunziata & D'Uggento, Angela Maria & Labarile, Angela, 2022. "What influences the perception of immigration in Italian adolescents? An analysis with CUB models for rating data," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Domenico Piccolo & Rosaria Simone, 2019. "Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 477-493, September.
    4. Marta Kuc-Czarnecka & Samuele Lo Piano & Andrea Saltelli, 2020. "Quantitative Storytelling in the Making of a Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 775-802, June.
    5. Francesca Iorio & Riccardo Lucchetti & Rosaria Simone, 2024. "Testing distributional assumptions in CUB models for the analysis of rating data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 669-701, September.

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