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.

The pandemic has progressed differently across the world. Using monthly data on COVID-19 cases and fatalities, we evaluate whether income inequality is an important factor in explaining cross-country differences in the spread and mortality of the virus. The results show that income inequality is positively correlated with the number of COVID-19 cases. Higher income inequality is associated with a more rapid spread of the virus and an increase in the number of cases, indirectly increasing mortality rates as well. Also, higher levels of inequality are associated with reduced effectiveness of social distancing measures in containing new infections. Thus, elevated inequalities place…

As developing countries pursue infrastructure projects, they should aim to address a combination of the pandemic, climate, inequality, and other crises with the right mix of economic and social infrastructure. To do this, governments must invest in a national infrastructure planning process, align planning with the SDGs, and prioritize sustainable infrastructure over infrastructure that does not put people and the planet first. There is no silver bullet for all the challenges; however, incremental changes based on innovative precedents can potentially make a difference on the ground. This paper proposes an analytical framework to consider these challenges and concludes with possible…

The objective of this paper is to examine the impact of unconventional monetary policy measures adopted in developed countries (the US, UK, Euro Area and Japan) on developing economies (Brazil, China, India and Russia). First, we analyse the domestic and cross-border financial market impact of unconventional monetary policy announcements by central banks, using a series of event studies. We find that quantitative easing (QE) by the FED, BoE, ECB and BoJ influenced long term yields, equity prices, and possibly exchange rates both in the developed and developing countries (for example we find that QE resulted in decreases in long term yields by about 125 basis points in the US, about 100…

This paper examines the distributional effects of fiscal austerity. Using episodes of fiscal consolidation measures for a sample of 17 OECD countries over the period 1978-2009, we find that fiscal consolidation episodes have typically led to a significant and long-lasting increase in inequality. Tax-based consolidation episodes tend to have a larger and more persistent effect on inequality than spendingbased consolidations. The evidence also shows that while fiscal consolidations have typically led to a fall in wage income, they have not had a significant effect on profit and rent income.