Working Papers

This paper proposes the use of synthetic training data generated by large language models
to improve machine learning SDG classifiers. It shows that supplementing existing training data with
synthetic data produced by the ChatGPT tool improves the performance of the SDGClassy classifier.
This addition of synthetic data is especially useful in building SDG classifiers given the limited availability
of properly labeled data and the complex, interconnected nature of the SDGs. Synthetic data thus enables
more effective machine-learning applications in this context.

Lack of fiscal space and the risk of sovereign debt distress remain key stumbling blocks to achieving Sustainable Development Goals (SDGs) in developing countries. Because the allocation of concessional funds and debt relief is essentially reserved to Low Income countries (LICs), official financing strategies and mechanisms to support developing countries provide insufficient support to non-LICs that may need and deserve special consideration concerning official financing. This paper discusses how official financial support allocation could consider countries’ vulnerabilities in critical dimensions, with special reference to Small Island Developing States (SIDS). It explores how a…

This paper conceptualizes recently negotiated international agreements, particularly the 2030 Agenda for Sustainable Development, as a collective roadmap to overcome challenges associated with globalization. By analyzing the effects and implications of globalization on societies and economies, the paper highlights concrete aspects of the international commitments that address globalization challenges in the three dimensions of sustainable development. Particular focus is placed on global production patterns, labor markets, poverty and inequality, global imbalances, migration and climate change. The paper concludes that, in the context of a changing political economy of globalization and…

This paper offers a unifying conceptual framework for understanding the relationship between climate change and “within-country inequalities,” referred here collectively as “social inequality.” Available evidence indicates that this relationship is characterized by a vicious cycle, whereby initial inequality causes the disadvantaged groups to suffer disproportionately from the adverse effects of climate change, resulting in greater subsequent inequality. The paper identifies three main channels through which the inequality-aggravating effect of climate change materializes, namely (a) increase in the exposure of the disadvantaged groups to the adverse effects of climate change; (b)…

This paper maps interrelationships among targets of the Sustainable Development Goal dedicated to oceans (SDG 14), as well as interrelationships between those targets and other SDGs. This is done using a large number of UN reports as well as scientific publications. The literature identifies many linkages among the targets of SDG 14; most of these targets are potentially synergistic with one another. Many linkages also exist between SDG 14 targets and other SDGs. Different targets under SDG 14 link to different SDGs. This has implications for policy discussions on how to achieve progress on SDG 14. The interrelationships that we highlight can be used as a tool for dialogue between policy…

To achieve the greatest possible human welfare, the Stockholm Environment Institute’s Climate and Regional Economics of Development (CRED) model calls for rapid reduction of greenhouse gas emissions to keep cumulative 21st century carbon dioxide emissions below 2,000 Gt. We explain why as some other models claim very slow emission reductions are best. We make three changes to the basic assumptions of the well-known DICE model to include the most recent estimates of economic damages from climate change, express greater concern about the well-being of future generations, and expect rich countries to invest in emissions and poverty reduction in poorer countries.