ABSTRACT For many benchmark predictor variables, short‐horizon return predictability in the U.S. stock market is local in time as short periods with significant predictability (“pockets”) are interspersed with long periods with no return predictability. We document this result empirically using a flexible time‐varying parameter model that estimates predictive coefficients as a nonparametric function of time and explore possible explanations of this finding, including time‐varying risk premia for which we find limited support. Conversely, pockets of return predictability are consistent with a sticky expectations model in which investors slowly update their beliefs about a persistent component in the cash flow process.

We study daily money market mutual fund flows at the individual share class level during September 2008. This fine granularity of data allows new insights into investor and portfolio holding characteristics conducive to run risk in cash-like asset pools. We find that cross-sectional flow data observed during the week of the Lehman failure are consistent with key implications of a simple model of coordination with incomplete information and strategic complementarities. Similar conclusions follow from daily models fitted to capture dynamic interactions between investors with differing levels of sophistication within the same money fund, holding constant the underlying portfolio. (JEL D14, G11, G23)

For whom has earnings risk changed, and why? We answer these questions by combining the Kalman filter and EM algorithm to estimate persistent and temporary earnings for every individual at every point in time. We apply our method to administrative earnings linked with survey data. We show that since the 1980s, persistent earnings risk rose by 12.5 percent for both employed and unemployed workers and the scarring effects of unemployment doubled. At the same time, temporary earnings risk declined. Using education and occupation codes, we show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption. (JEL J22, J24, J31, J64)