Onikoyi, Ayi, M.A.A (2022) Identifying Trade-offs and Synergies in Implementing the Sustainable Development Goals using Machine Learning. Master thesis, Sustainable Entrepreneurship (SE).
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Abstract
Since the launch of the SDG initiatives in 2015 by the United Nations, policymakers, scholars, and practitioners have become increasingly concerned about the implications of spillovers – Meaning that advancing one specific SDG indicator can come at the cost of another (trade-off) or a benefit (synergy). Despite this becoming a growing concern, little is known about the mechanisms that drive these spillovers between the multi-dimensional 17 goals. This thesis addresses the problem of spillovers in SDG using multivariate quantitative research, namely, Principal Component Analysis to summarize each goal and interaction in the SDG agenda. PCA allows mapping spillover effects at the level of goals for five SDGs while using all available information for the selected indicators between SDGs between 2011 – 2018. The most striking finding is that the share of renewable energy correlates negatively with indicators measuring the population's access to electricity, internet usage, and unemployment rate. In contrast, clean energy technology gave the complete opposite result. This result may imply that different forms of sustainable energy sources have significantly different results on SDG progress.
| Item Type: | Thesis (Master) |
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| Name supervisor: | Folmer, E.C. and Engel, O. |
| Date Deposited: | 09 Sep 2022 09:15 |
| Last Modified: | 09 Sep 2022 09:15 |
| URI: | https://campus-fryslan.studenttheses.ub.rug.nl/id/eprint/221 |
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