This paper constructs high-frequency and timely income distributions for the United States. We develop a methodology to combine the information contained in high-frequency public data sources--including monthly household and employment surveys, quarterly censuses of employment and wages, and...

We collect a comprehensive set of non-academic characteristics for a representative sample of incoming freshman to explore which measures best predict the wide variance in first-year college performance unaccounted for by past grades. We focus our attention on student outliers. Students whose...

How much do different monetary and non-monetary motivators induce costly effort? Does the effectiveness line up with the expectations of researchers? We present the results of a large-scale real-effort experiment with 18 treatment arms. We compare the effect of three motivators: (i) standard...

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands/U.K. (1629-1812), U.K. (1813-1870) and U.S. (1871-2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for...

We present an alternative expectation formation mechanism that helps rationalize well known asset pricing anomalies, such as the predictability of excess returns, excess volatility, and the equity-premium puzzle. As with rational expectations (RE), the expectation formation mechanism we consider...

In asset pricing, estimation risk refers to investor uncertainty about the parameters of the return or cashflow process. We show that with estimation risk the observable properties of prices and returns can differ significantly from the properties perceived by rational investors. In particular,...

This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have...

We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence...