Bayesian learning implies decreasing weights on prior beliefs and increasing weights on track records, as the latter become more precise. We test whether investors learn about analyst predictive ability in this manner by examining market reactions to analysts' forecasts. Consistent with...

This study investigates how occupational AI exposure impacts employment at the intensive margin, i.e., the length of workdays and the allocation of time between work and leisure. Drawing on individual-level time diary data from 2004-2023, we find that higher AI exposure--whether stemming from...

This paper analyzes how corporate disclosure has been reshaped by machine processors, employed by algorithmic traders, robot investment advisors, and quantitative analysts. Our findings indicate that increasing machine and AI readership, proxied by machine downloads, motivates firms to prepare...

Growing AI readership, proxied by expected machine downloads, motivates firms to prepare filings that are friendlier to machine parsing and processing. Firms avoid words that are perceived as negative by computational algorithms, as compared to those deemed negative only by dictionaries meant...

Using trading information of a comprehensive sample of relisted Chapter 11 firms in the past few decades, we find that the one-year market-adjusted buy-and-hold returns of post-reorg equity are over 50%. An equal-weighted calendar-time portfolio generates 7.2% annualized excess returns over a...

China's industrial policies ("Five-Year Plans") displace U.S. production/employment and heighten plant closures in the same industries as those targeted by the policies in China. The impact was not anticipated by the stock market, but U.S. companies in the "treated industries" suffer a valuation...