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…

This paper investigates the role of trade costs in exporter dynamics in Africa. In comparison to exporters from other regions, African exporting firms are fewer, smaller and relatively less diversified in terms of products and destinations. African countries also display the highest rates of entry, exit and turnover of exporting firms, exporting products and export destinations. This suggests that Africa’s exporting activity is volatile and subject to a lot of experimentation, with exporters having difficulties in maintaining trade relationships. The analysis also confirms that trade costs are a crucial factor in explaining exporter performance in Africa vis-à-vis other regions, but also…

Productive and technological capabilities matter. The more conventional strands of the literature have emphasized them as major engines of export, growth and development. But how they matter is less clear, and many open questions remain on how capabilities influence export dynamics at microeconomic level. This paper empirically investigates their role on export dynamics in 40 developing countries between 2002 and 2012. In doing so, the paper exploits a country-sector-year database containing exporter-level statistical information. The empirical analysis shows that, within sectors, countries with higher productive capacities have more exporters, and the exporters are larger and charge…

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…

We introduce two separate datasets (The Global Consumption Dataset (GCD) and The Global Income Dataset (GID)) containing an unprecedented portrait of consumption and income of persons over time, within and across countries, around the world. The benchmark version of the dataset presents estimates in PPP units of monthly real consumption and income for every decile of the population (a ‘consumption/income profile’) for 133 countries and more than half a century (1960-2012). We describe the construction of the datasets and demonstrate some possible uses by presenting preliminary results concerning the consumption distribution, poverty and inequality for the world and specific country…