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Optimizing Data-driven Weights In Multidimensional Indexes

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  • Lidia Ceriani
  • Chiara Gigliarano
  • Paolo Verme

Abstract

Multidimensional indexes are ubiquitous, and popular, but present non-negligible normative choices when it comes to attributing weights to their dimensions. This paper provides a more rigorous approach to the choice of weights by defining a set of desirable properties that weighting models should meet. It shows that Bayesian Networks is the only model across statistical, econometric, and machine learning computational models that meets these properties. An example with EU-SILC data illustrates this new approach highlighting its potential for policies.

Suggested Citation

  • Lidia Ceriani & Chiara Gigliarano & Paolo Verme, 2025. "Optimizing Data-driven Weights In Multidimensional Indexes," Papers 2504.06012, arXiv.org.
    • Handle: RePEc:arx:papers:2504.06012
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    1. Wolfgang Karl Härdle & Léopold Simar & Matthias R. Fengler, 2024. "Applied Multivariate Statistical Analysis," Springer Books, Springer, edition 0, number 978-3-031-63833-6, January.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    3. Asis Kumar Banerjee, 2018. "Multidimensional Indices with Data-driven Dimensional Weights: A Multidimensional Coefficient of Variation," Arthaniti: Journal of Economic Theory and Practice, , vol. 17(2), pages 140-156, December.
    4. Lidia Ceriani & Chiara Gigliarano, 2020. "Multidimensional Well-Being: A Bayesian Networks Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 237-263, November.
    5. Paolo Liberati & Giuliano Resce & Francesca Tosi, 2023. "The probability of multidimensional poverty: A new approach and an empirical application to EU‐SILC data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(3), pages 668-700, September.
    6. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 476-487, August.
    7. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 70, Elsevier.
    8. Alessio Fusco & Paul Dickes, 2008. "The Rasch Model and Multidimensional Poverty Measurement," Palgrave Macmillan Books, in: Nanak Kakwani & Jacques Silber (ed.), Quantitative Approaches to Multidimensional Poverty Measurement, chapter 3, pages 49-62, Palgrave Macmillan.
    9. Bosmans, Kristof & Decancq, Koen & Ooghe, Erwin, 2015. "What do normative indices of multidimensional inequality really measure?," Journal of Public Economics, Elsevier, vol. 130(C), pages 94-104.
    10. Walter Bossert & Satya R. Chakravarty & Conchita D’Ambrosio, 2019. "Multidimensional Poverty and Material Deprivation with Discrete Data," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 191-209, Springer.
    11. Scutari, Marco, 2010. "Learning Bayesian Networks with the bnlearn R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i03).
    12. Jaya Krishnakumar, 2007. "Going Beyond Functionings to Capabilities: An Econometric Model to Explain and Estimate Capabilities," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 8(1), pages 39-63.
    13. Frederik Booysen, 2002. "An Overview and Evaluation of Composite Indices of Development," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 59(2), pages 115-151, August.
    14. Koen Decancq & María Ana Lugo, 2013. "Weights in Multidimensional Indices of Wellbeing: An Overview," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 7-34, January.
    15. GUIO Anne-Catherine & FUSCO Alessio & MARLIER Eric, 2009. "A European Union Approach to Material Deprivation using EU-SILC and Eurobarometer data," IRISS Working Paper Series 2009-19, IRISS at CEPS/INSTEAD.
    16. Belhadj, Besma, 2012. "New weighting scheme for the dimensions in multidimensional poverty indices," Economics Letters, Elsevier, vol. 116(3), pages 304-307.
    17. Zhang, Zhao & Ma, Caoyuan & Wang, Aiping, 2021. "A longitudinal study of multidimensional poverty in rural China from 2010 to 2018," Economics Letters, Elsevier, vol. 204(C).
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    More about this item

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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