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Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction

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  • Ida Kubiszewski
  • Kenneth Mulder
  • Diane Jarvis
  • Robert Costanza

Abstract

In 2015, all 193 member states of the United Nations (UN) adopted the Sustainable Development Goals (SDGs). These 17 goals, 169 targets, and 232 indicators (including over 650 indicators if all the subdivisions are included) are intended to guide and improve sustainable wellbeing and life satisfaction for everyone on earth. Challenges include the fact that many indicators are not measured or reliably tracked in many countries, the cost of tracking is unclear, and no explicit overarching goal exists. To highlight some of the problems with this approach, we model life satisfaction (LS) survey scores by country, as a proxy for overall wellbeing, as the dependent variable against the official 232 SDG indicators. Using a constrained linear regression approach (LASSO), we identify a model that includes only 8 of the 232 indicators and explains 84% of the variation in LS. These eight indicators are proxies for economic, social, and environmental variables. We also cluster countries according to these indicators and LS showing correlation within geographical and cultural regions. We discuss these results with regard to the meaning and measurement of sustainable development vs. sustainable wellbeing and its relationship with LS and the SDGs. We recommend how these results can be used to prioritize goals and measurement efforts to create more meaningful and useful measures of sustainable wellbeing.

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  • Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
  • Handle: RePEc:wly:sustdv:v:30:y:2022:i:1:p:139-148
    DOI: 10.1002/sd.2234
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    3. Cook, David & Kaji, Takeshi Benjamín & Davíðsdóttir, Brynhildur, 2023. "An assessment of the scope and comprehensiveness of well-being economy indicator sets: The cases of Iceland, Scotland and New Zealand," Ecological Economics, Elsevier, vol. 205(C).
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    5. Juan A. García-Esparza & Javier Pardo & Pablo Altaba & Mario Alberich, 2023. "Validity of Machine Learning in Assessing Large Texts Through Sustainability Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(2), pages 323-337, April.
    6. Cristi Spulbar & Lucian Claudiu Anghel & Ramona Birau & Simona Ioana Ermiș & Laurențiu-Mihai Treapăt & Adrian T. Mitroi, 2022. "Digitalization as a Factor in Reducing Poverty and Its Implications in the Context of the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(17), pages 1-26, August.
    7. Evita Milana & Frank Ulrich, 2022. "Do open innovation practices in firms promote sustainability?," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1718-1732, December.
    8. Jingru Chen & Hengyuan Zeng & Qiang Gao, 2023. "Using the Sustainable Development Capacity of Key Counties to Guide Rural Revitalization in China," IJERPH, MDPI, vol. 20(5), pages 1-26, February.
    9. Katherine S. Nelson & Tuan D. Nguyen & Jean R. Francois & Shreya Ojha, 2023. "Rural sustainability methods, drivers, and outcomes: A systematic review," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1226-1249, June.
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    11. Henderson, Kirsten & Loreau, Michel, 2023. "A model of Sustainable Development Goals: Challenges and opportunities in promoting human well-being and environmental sustainability," Ecological Modelling, Elsevier, vol. 475(C).

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