IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2019i1p88-d300485.html
   My bibliography  Save this article

Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis

Author

Listed:
  • Salvatore F. Pileggi

    (School of Information, Systems and Modelling (ISM), University of Technology Sydney, Sydney, NSW 2007, Australia
    Centre on Persuasive Systems for Wise Adaptive Living (PERSWADE), University of Technology Sydney, Sydney, NSW 2007, Australia)

Abstract

Is the World becoming a better or a worse place to live? In this paper, we propose a tool that can help to answer the question by combining a number of global indicators belonging to multiple categories. The proliferation of statistical data about various aspects of the World performance may suggest that it should be “easy” to evaluate the overall success of human enterprise on this planet. Moreover, it also points out the intrinsic importance in the selection of indicators. However, people have different values, biases, and preferences about the importance of various indicators, making it almost impossible to find an objective answer to this question. To address the variety and the heterogeneity of available indicators and world views, we present the analysis of global World performance as a multi-criteria decision problem, making sure that the assessment method remains as transparent as possible. By dynamically selecting a set of indicators of interest, defining the weights that we attach to various indicators and specifying the desired trends associated with each indicator, we make the assessment adaptive to individual values. We also try to deal with the inherent bias that may exist in the set of indicators that are chosen. As a study case, from various data sets that are openly available online, we have selected several that are most relevant and easy to interpret in the context of the question in the title of the paper. We demonstrate how the choice of personal preferences, or weights, can strongly change the result. Our method also provides analysis of the weights space, showing how results for particular value sets compare to the average and extreme (optimistic and pessimistic) combinations of weights that may be chosen by users.

Suggested Citation

  • Salvatore F. Pileggi, 2019. "Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis," Sustainability, MDPI, vol. 12(1), pages 1-24, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2019:i:1:p:88-:d:300485
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/1/88/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/1/88/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jutta Bolt & Jan Luiten Zanden, 2014. "The Maddison Project: collaborative research on historical national accounts," Economic History Review, Economic History Society, vol. 67(3), pages 627-651, August.
    2. Inklaar, Robert & de Jong, Harmen & Bolt, Jutta & van Zanden, Jan, 2018. "Rebasing 'Maddison': new income comparisons and the shape of long-run economic development," GGDC Research Memorandum GD-174, Groningen Growth and Development Centre, University of Groningen.
    3. Chao Zhang & Guanghui Zhou & Qi Lu & Fengtian Chang, 2017. "Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7187-7203, December.
    4. Durbach, Ian N. & Stewart, Theodor J., 2012. "Modeling uncertainty in multi-criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 223(1), pages 1-14.
    5. Hämäläinen, Raimo P. & Alaja, Susanna, 2008. "The threat of weighting biases in environmental decision analysis," Ecological Economics, Elsevier, vol. 68(1-2), pages 556-569, December.
    6. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    7. Lawrence Phillips & Carlos Bana e Costa, 2007. "Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing," Annals of Operations Research, Springer, vol. 154(1), pages 51-68, October.
    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. Wulf, David & Bertsch, Valentin, 2016. "A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making," MPRA Paper 75025, University Library of Munich, Germany.
    2. Baudry, Gino & Macharis, Cathy & Vallée, Thomas, 2018. "Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty," European Journal of Operational Research, Elsevier, vol. 264(1), pages 257-269.
    3. S. Scrieciu & Valerie Belton & Zaid Chalabi & Reinhard Mechler & Daniel Puig, 2014. "Advancing methodological thinking and practice for development-compatible climate policy planning," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(3), pages 261-288, March.
    4. Narcisse Cha'Ngom & Christoph Deuster & Frédéric Docquier & Joël Machado, 2023. "Selective Migration and Economic Development: A Generalized Approach," LISER Working Paper Series 2023-06, Luxembourg Institute of Socio-Economic Research (LISER).
    5. Valentin Bertsch & Wolf Fichtner, 2016. "A participatory multi-criteria approach for power generation and transmission planning," Annals of Operations Research, Springer, vol. 245(1), pages 177-207, October.
    6. Sédi-Anne Boukaka & Giulia Mancini & Giovanni Vecchi, 2021. "Poverty and inequality in Francophone Africa, 1960s–2010s," Economic History of Developing Regions, Taylor & Francis Journals, vol. 36(1), pages 1-29, January.
    7. Hartley, Jonathan S., 2021. "Friedman’s plucking model: New international evidence from Maddison Project data," Economics Letters, Elsevier, vol. 199(C).
    8. Gallardo-Albarrán, Daniel, 2019. "Missed opportunities? Human welfare in Western Europe and the United States, 1913–1950," Explorations in Economic History, Elsevier, vol. 72(C), pages 57-73.
    9. Fernanda Cimini & Jorge Britto & Leonardo Costa Ribeiro, 2020. "Complexity systems and middle-income trap: the long-term roots of Latin America underdevelopment [Sistemas complexos e armadilha da renda media: as raízes de longo prazo do subdesenvolvimento latino-a," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 30(spe), pages 1225-1256, December.
    10. Cristián Ducoing & José Peres-Cajías & Marc Badia-Miró & Ann-Kristin Bergquist & Carlos Contreras & Kristin Ranestad & Sara Torregrosa, 2018. "Natural Resources Curse in the Long Run? Bolivia, Chile and Peru in the Nordic Countries’ Mirror," Sustainability, MDPI, vol. 10(4), pages 1-25, March.
    11. Martina Cioni & Govanni Federico & Michelangelo Vasta, 2018. "Ninety years of publications in Economic History: evidence from the top five field journals (1927-2017)," Department of Economics University of Siena 791, Department of Economics, University of Siena.
    12. Tobias Witt & Matthias Klumpp, 2021. "Multi-Period Multi-Criteria Decision Making under Uncertainty: A Renewable Energy Transition Case from Germany," Sustainability, MDPI, vol. 13(11), pages 1-20, June.
    13. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
    14. Johan Fourie & Nonso Obikili, 2019. "Decolonizing with data: The cliometric turn in African economic history," Working Papers 02/2019, Stellenbosch University, Department of Economics.
    15. Bana e Costa, Carlos A. & Oliveira, Mónica D. & Rodrigues, Teresa C. & Vieira, Ana C.L., 2023. "Desirability–doability group judgment framework for the collaborative multicriteria evaluation of public policies," LSE Research Online Documents on Economics 118192, London School of Economics and Political Science, LSE Library.
    16. Scholten, Lisa & Schuwirth, Nele & Reichert, Peter & Lienert, Judit, 2015. "Tackling uncertainty in multi-criteria decision analysis – An application to water supply infrastructure planning," European Journal of Operational Research, Elsevier, vol. 242(1), pages 243-260.
    17. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
    18. André A. Hofman & Patricio Valderrama, 2021. "Long Run Economic Growth Performance In Latin America – 1820–2016," Journal of Economic Surveys, Wiley Blackwell, vol. 35(3), pages 833-869, July.
    19. David Huckebrink & Valentin Bertsch, 2021. "Integrating Behavioural Aspects in Energy System Modelling—A Review," Energies, MDPI, vol. 14(15), pages 1-26, July.
    20. Joan R Rosés & Nikolaus Wolf, 2021. "Regional growth and inequality in the long-run: Europe, 1900–2015," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(1), pages 17-48.

    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:gam:jsusta:v:12:y:2019:i:1:p:88-:d:300485. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.