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E pluribus, quaedam. Gross domestic product out of a dashboard of indicators

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  • Guerini, Mattia
  • Vanni, Fabio
  • Napoletano, Mauro

Abstract

Is aggregate income enough to summarize the well-being of a society? We address this longstanding question by exploiting a novel approach to study the relationship between gross domestic product (GDP) and a set of economic, social and environmental indicators for nine developed economies. By employing dimensionality reduction techniques, we quantify the share of variability stemming from a large set of different indicators that can be compressed into a univariate index. We also evaluate how well this variability can be explained if the univariate index is GDP. Our results indicate that univariate measures, and GDP among them, are doomed to fail in accounting for the variability of well-being indicators. Even if GDP would be the best linear univariate index, its quality in synthesizing information from indicators belonging to different domains is poor. Our approach provides additional support for policy makers interested in measuring the trade offs between income and other relevant socio-economic and ecological dimensions. Furthermore, it adds new quantitative evidence to the already vast literature criticizing GDP as the most prominent measure of well-being.

Suggested Citation

  • Guerini, Mattia & Vanni, Fabio & Napoletano, Mauro, "undated". "E pluribus, quaedam. Gross domestic product out of a dashboard of indicators," FEEM Working Papers 324043, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemwp:324043
    DOI: 10.22004/ag.econ.324043
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    1. Huguet Ferran, Pau & Heijungs, Reinout & Vogtländer, Joost G., 2018. "Critical Analysis of Methods for Integrating Economic and Environmental Indicators," Ecological Economics, Elsevier, vol. 146(C), pages 549-559.
    2. Luzzati, T. & Gucciardi, G., 2015. "A non-simplistic approach to composite indicators and rankings: an illustration by comparing the sustainability of the EU Countries," Ecological Economics, Elsevier, vol. 113(C), pages 25-38.
    3. Claudio Barbieri & Mattia Guerini & Mauro Napoletano, 2021. "The anatomy of government bond yields synchronization in the Eurozone," Sciences Po Economics Publications (main) hal-03373853, HAL.
    4. Hoekstra,Rutger, 2019. "Replacing GDP by 2030," Cambridge Books, Cambridge University Press, number 9781108497336, January.
    5. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    6. Malay, Olivier E., 2019. "Do Beyond GDP indicators initiated by powerful stakeholders have a transformative potential?," Ecological Economics, Elsevier, vol. 162(C), pages 100-107.
    7. Iyetomi, Hiroshi & Nakayama, Yasuhiro & Yoshikawa, Hiroshi & Aoyama, Hideaki & Fujiwara, Yoshi & Ikeda, Yuichi & Souma, Wataru, 2011. "What causes business cycles? Analysis of the Japanese industrial production data," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 246-272, September.
    8. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    9. Kalimeris, Panos & Bithas, Kostas & Richardson, Clive & Nijkamp, Peter, 2020. "Hidden linkages between resources and economy: A “Beyond-GDP” approach using alternative welfare indicators," Ecological Economics, Elsevier, vol. 169(C).
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    Keywords

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    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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