We propose a model in which risk, at both the micro and the macro levels, is endogenous. In the model, each firm can choose the mean and the variance of its productivity process, as well as how it covaries with the productivity of other firms. To study the aggregate impact of these decisions, we embed the firms into an otherwise standard production network economy. Through their impact on risk-taking decisions, distortions such as taxes and markups can make GDP more volatile in equilibrium. The theory also predicts that the productivity of larger firms and those with smaller markups is less volatile and less correlated with aggregate productivity. We find support for these predictions in the data. In a calibrated version of the model, removing distortions significantly reduces GDP volatility.

We examine a novel mechanism whereby the US dollar’s global dominance can have a large, unexpected impact on foreign Treasury yields in crisis periods. Non-US institutions hold substantial dollar assets and hedge dollar exposures by selling dollars forward. In crisis periods, the dollar appreciates against other currencies. To meet margin calls on FX hedging positions, traditionally passive institutions sell domestic safe assets, thereby contributing to yield spikes in domestic markets. We show that during the recent COVID crisis, UK institutions with substantial dollar holdings and FX hedging positions sold large amounts of gilts, which contributed to the observed gilt yield spike.

We decode China’s industrial policy from 2000 by employing large language models (LLMs) to extract and analyze rich information from a comprehensive dataset of 3 million documents issued by central, provincial, and municipal governments. Through careful prompt engineering, multistage extraction and refinement, and rigorous verification, LLMs allow us to capture detailed policy dimensions, including context and scope, targeted industries, tools, implementation mechanisms, and intergovernmental relationships, etc., and thus provide a nuanced understanding of the evolution of China’s industrial policy. By combining structured policy data with micro-level firm data, we document 13 key facts about China's industrial policy. Our analysis explores the following critical questions. Which industries are targeted and how does this align with economic theory? What tools are deployed most frequently and how does their usage vary across government levels and regions? We also examine the impact of these policies on firm behavior, including entry, production, and productivity growth, and highlight the heterogeneous effects of different policy tools. In addition, we explore the political economy of industrial policy, focusing on top-down transmission mechanisms, policy diffusion, and persistence across regions. Finally, we document spatial inefficiencies and industry-wide overcapacity as potential downsides. This study provides a comprehensive picture of China’s industrial policies, highlighting both successes and inefficiencies in the policy landscape. Moving beyond his work in ESM, Dr. Koopman has gained a wealth of knowledge and experience in the field generally that he would love to share. As a Full Professor with an endowed position, a winner of several early-career awards and “Best Reviewer” awards, a publication record of over 40+ manuscripts in top OB/HR journals, and the Division-Chair Elect for the Human Resources Division of the Academy of Management, Dr. Koopman has thoughts, opinions, and perspectives on excellence in this profession (research, teaching, and service). In the second half of the session, he will field questions from the audience on a variety of topics and offer his thoughts to attendees.