The outbreak of COVID-19 in early 2020 heralded a deep global recession not seen since the Second World War. With a billion people out of work and entire countries in lock-down, the burgeoning economies of countries like India has plunged into a downward spiral. The conventional instruments of...

This Article investigates whether all stakeholder groups share the same understanding and useof the relevant terms and concepts of the DSA and DMA. Leveraging the power ofcomputational text analysis, we find significant differences in the employment ofterms like “gatekeepers,”...

In this paper, we compare two popular statistical learning techniques, logistic regression and random forest, with respect to their ability to classify jobseekers by their likelihood to become long-term unemployed. We study the performance of the two methods before the COVID-19 pandemic as well...

Intro -- Contents -- Acknowledgments -- Introduction / Ajay Agrawal, Joshua Gans, and Avi Goldfarb -- I. AI as a GPT -- 1. Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics / Erik Brynjolfsson, Daniel Rock, and Chad Syverson, Comment: Rebecca...

Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine...

Financial crises cause economic, social and political havoc. Macroprudential policies are gaining traction but are still severely under-researched compared to monetary policy and fiscal policy. We use the general framework of sequential predictions also called online machine learning to forecast...