IDEAS home Printed from https://ideas.repec.org/p/fem/femwpa/2022.15.html

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

Author

Listed:
  • Mattia Guerini

    (University of Brescia, Fondazione Eni Enrico Mattei (FEEM), GREDEG, CNRS, Université Côte d'Azur and Institute of Economics, Sant'Anna School of Advanced Studies)

  • Fabio Vanni

    (Università degli Studi dell'Insubria, GREDEG, CNRS, Université Côte d'Azur and Institute of Economics, Sant'Anna School of Advanced Studies)

  • Mauro Napoletano

    (GREDEG, CNRS, Université Côte d'Azur, Sciences Po, OFCE, SKEMA Business School and Institute of Economics, Sant'Anna School of Advanced Studies)

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

  • Mattia Guerini & Fabio Vanni & Mauro Napoletano, 2022. "E pluribus, quaedam. Gross domestic product out of a dashboard of indicators," Working Papers 2022.15, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2022.15
    as

    Download full text from publisher

    File URL: https://feem-media.s3.eu-central-1.amazonaws.com/wp-content/uploads/NDL2022-015.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Hoekstra,Rutger, 2019. "Replacing GDP by 2030," Cambridge Books, Cambridge University Press, number 9781108497336, Enero-Abr.
    3. 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.
    4. Claudio Barbieri & Mattia Guerini & Mauro Napoletano, 2021. "The Anatomy of Government Bond Yields Synchronization in the Eurozone," LEM Papers Series 2021/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2023. "Synchronization patterns in the European Union," Applied Economics, Taylor & Francis Journals, vol. 55(18), pages 2038-2059, April.
    10. 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.
    11. Laurent Laloux & Pierre Cizeau & Marc Potters & Jean-Philippe Bouchaud, 2000. "Random Matrix Theory And Financial Correlations," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 391-397.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    3. Joel Bun & Jean-Philippe Bouchaud & Marc Potters, 2016. "Cleaning large correlation matrices: tools from random matrix theory," Papers 1610.08104, arXiv.org.
    4. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    5. Tom Boot & Bart Keijsers, 2025. "Diffusion index forecasts under weaker loadings: PCA, ridge regression, and random projections," Papers 2506.09575, arXiv.org.
    6. Nine Klaassen & Arno Scheepens & Bas Flipsen & Joost Vogtlander, 2020. "Eco-Efficient Value Creation of Residential Street Lighting Systems by Simultaneously Analysing the Value, the Costs and the Eco-Costs during the Design and Engineering Phase," Energies, MDPI, vol. 13(13), pages 1-18, June.
    7. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    8. Sebastiano Michele Zema & Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2025. "Mesoscopic structure of the stock market and portfolio optimization," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 20(2), pages 307-333, April.
    9. Liusha Yang & Romain Couillet & Matthew R. McKay, 2015. "A Robust Statistics Approach to Minimum Variance Portfolio Optimization," Papers 1503.08013, arXiv.org.
    10. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    11. Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Swiss Finance Institute Research Paper Series 22-81, Swiss Finance Institute.
    12. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
    13. Antonia Arsova, 2019. "Exchange rate pass-through to import prices in Europe: A panel cointegration approach," Working Paper Series in Economics 384, University of Lüneburg, Institute of Economics.
    14. Luke Hartigan & James Morley, 2020. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 271-293, September.
    15. Yongfu Huang & Muhammad G. Quibria, 2015. "The global partnership for sustainable development," Natural Resources Forum, Blackwell Publishing, vol. 0(3-4), pages 157-174, August.
    16. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
    17. Magacho, Guilherme & Spinola, Danilo, 2025. "Dynamic Adjustments in Environmental Input-Output Models: Incorporating Quantity and Price Traverse Disequilibrium," CAFE Working Papers 40, Centre for Accountancy, Finance and Economics (CAFE), Birmingham City Business School, Birmingham City University.
    18. Zhou, Wuhao & Xu, Yuanlu & Zhang, Li & Lin, Huifang, 2023. "Does public behavior and research development matters for economic growth in SMEs: Evidence from Chinese listed firms," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 107-119.
    19. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    20. Funke, Michael & Tsang, Andrew, 2019. "The direction and intensity of China's monetary policy conduct: A dynamic factor modelling approach," BOFIT Discussion Papers 8/2019, Bank of Finland Institute for Emerging Economies (BOFIT).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fem:femwpa:2022.15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alberto Prina Cerai The email address of this maintainer does not seem to be valid anymore. Please ask Alberto Prina Cerai to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.