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.

Research suggests that achieving the Sustainable Development Goals (SDGs) can open up market opportunities worth USD 12 trillion in the four largest sectors that represent 60 per cent of real economy – food and agriculture; cities; energy and materials; and health and well-being. While the concept of the SDGs creating a win-win situation for all is growing increasingly trendy, further evidence needs to be accumulated to better chart the important discourse on the private sector’s engagement with the SDGs. To this end, this paper aims to shed light on three questions: (i) How is the private sector currently engaging with the SGDs in these sectors?; (ii) What are the key areas of…

Between the many resolutions, speeches, reports and other documents that are produced each year, the United Nations is awash in text. It is an ongoing challenge to create a coherent and useful picture of this corpus. In particular, there is an interest in measuring how the work of the United Nations system aligns with the Sustainable Development Goals (SDGs). There is a need for a scalable, objective, and consistent way to measure how similar any given publication is to each of the 17 SDGs. This paper explains a proof-of-concept process for building such a system using machine learning algorithms. By creating a model of the 17 SDGs it is possible to measure how similar the contents of…

This paper examines the relationship between “Transformative Change,” advocated by the 2030 Agenda for sustainable development, and “Structural Change,” which has been a longstanding and important concept in Development Economics. It shows that while structural change is still relevant, growing concerns for social development and environmental protection made it necessary to switch to the more encompassing concept of “Transformative Change” that provides greater space for inclusion and interaction of all three dimensions of sustainable development. The paper notes that, in the era of greater globalization, countries have followed more varied patterns of structural change, all of which…