“Unbalanced Trade 2.0” by Alejandro Cuñat and Robert Zymek.
“Do trade imbalances boost incomes in surplus economies at the expense of deficit economies? We show that the answer is yes in an important subclass of quantitative trade models. This is the consequence of scale economies concentrated in the traded sector. A rise in net exports causes the traded sector to expand, which raises productivity and real income in surplus economies. …major deficit economies may prefer to correct their traded-sector underproduction by moving to financial autarky. However, financial autarky reduces global welfare and is generally not the optimal policy to bolster the traded sector in the presence of scale economies.”
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“Accounting for Uncertainty and Risks in Monetary Policy” by Michael Bauer, Travis Berge, Giuseppe Fiori, Francesca Loria, and Molin Zhong.
“This paper discusses the measurement, assessment, and communication of risks and uncertainty that are relevant for monetary policy. It provides a taxonomy of policy-relevant uncertainty related to the state and the structure of the economy, and the formation of expectations. A wide range of tools is available to assess and quantify uncertainty and the balance of risks. Qualitative assessments of uncertainty—in policy statements, minutes, and speeches—are the main tools to communicate uncertainty and the balance of risks across major central banks. However, the use of quantitative tools for such communications including scenario analysis—is evolving, and so far no clear consensus has emerged for best practices.”
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“Harnessing artificial intelligence for monitoring financial markets” by Matteo Aquilina, Douglas Kiarelly Godoy de Araujo, Gaston Gelos, Taejin Park, and Fernando Perez-Cruz.
“We study how artificial intelligence can help monitor financial markets. We build a two-step tool that forecasts market stress and explains the reasons behind its forecast. First, a recurrent neural network learns from over one hundred daily market indicators. It predicts the average size of gaps between euro–yen traded directly and euro–dollar–yen traded via the US dollar. These “triangular arbitrage parity” gaps should vanish within seconds in normal times, and big or persistent gaps signal that market frictions are rising. Second, the model shows, day by day, which market indicators matter most for its signal. This information can then direct a large language model to search recent news about those high-importance indicators to add timely context.”
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“A Research Agenda for the Economics of Transformative AI” by Erik Brynjolfsson, Anton Korinek, and Ajay K. Agrawal.
“As we approach Transformative Artificial Intelligence (TAI), there is an urgent need to advance our understanding of how it could reshape our economic models, institutions and policies. We propose a research agenda for the economics of TAI by identifying nine Grand Challenges: economic growth, innovation, income distribution, decision-making power, geoeconomics, information flows, safety risks, human well-being, and transition dynamics. By accelerating work in these areas, researchers can develop insights and tools to help fulfill the economic potential of TAI.”
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“Outside Job Opportunities and the Gender Gap in Pay” by Peter Fredriksson, Dogan Gülümser, and Lena Hensvik.
“We show that the wages of men and women are differentially affected byoutside options, and that these differential responses contribute to the genderpay gap.”
“Using Swedish register data, we find that improved outside options are associated with higher within-job wage growth for men but not for women. Importantly, we can rule out that these gendered responses arise from differences in the quality of external offers as these are balanced across genders by design. Additionally, men’s and women’s job mobility responses are verysimilar. In the light of the model, we attribute these findings to differences in negotiation behavior between men and women. Policies encouraging women to bargain in response to outside options may thus be a powerful tool for reducing the remaining within-job gender gap in pay.”