Data are used from the 1984–2016 Displaced Workers Surveys (DWS) to investigate the incidence and consequences of job loss, 1981–2015. These data show a record high rate of job loss in the Great Recession, with serious employment consequences for job losers, including very low rates of re-employment and difficulty finding full-time employment. The average reduction in weekly earnings for job losers making a full-time–full-time transition are relatively small, with a substantial minority reporting earning more on their new job than on the lost job. Most of the cost of job loss comes from difficulty finding new full-time employment.

Abstract We estimate the stock’s likelihood of extreme returns by measuring the extent to which the stock’s trades are correlated with market-wide and industry-wide trades during normal times, referred to as herding. We find that stocks whose trades herd most with aggregate-level trades experience most negative (positive) returns during market crashes (booms). While herding generates extreme returns in both sides, investors appear to demand compensation for the possibility of extreme low returns. This is the case even when we control for standard asset pricing variables and other tail risk proxies.

This paper examines the interplay among bank liquidity creation (which incorporates all bank on- and off-balance sheet activities), monetary policy, and financial crises. We find that: (1) high liquidity creation (relative to trend) – particularly off-balance sheet liquidity creation – helps predict crises, controlling for other factors; (2) monetary policy has statistically significant, but economically minor effects on liquidity creation by small banks during normal times, and these effects are even weaker during financial crises; (3) monetary policy has very little effects on medium and large bank liquidity creation during both normal times and crises. These findings suggest that authorities may wish to monitor bank liquidity creation closely in order to predict and perhaps lessen the likelihood of financial crises. They might also consider other tools to control bank liquidity creation, such as capital and liquidity requirements.

Abstract We argue that anomalies may experience prolonged decay after discovery and propose a Bayesian framework to study how that impacts portfolio decisions. Using the January effect and short-term index autocorrelations as examples of disappearing anomalies, we find that prolonged decay is empirically important, particularly for small-cap anomalies. Papers that document new anomalies without accounting for such decay may actually underestimate the original strength of the anomaly and imply an overstated level of the anomaly out of sample. We show that allowing for potential decay in the context of portfolio choice leads to out-of-sample outperformance relative to other approaches.

Extant literature shows that IPO first-day returns are correlated with market returns preceding the issue. We propose a rational explanation for this puzzling predictability by adding a public signal to Benveniste and Spindt (1989)’s information-based framework. A novel result of our model is that the compensation required by investors to truthfully reveal their information decreases with the public signal. This “incentive effect” receives strong empirical support in a sample of 6300 IPOs in 1983–2012. Controlling for the incentive effect, the positive relation between initial returns and pre-issue market returns disappears for top-tier underwriters, where the order book is held to be most informative, effectively resolving the predictability puzzle.

Abstract Recent years have seen increased demand from institutional investors for passive replication products that track the performance of hedge fund strategies using liquid investable assets such as futures contracts. In practice, linear replication methods suffer from poor tracking performance and high turnover. We propose a model combination approach to index replication that pools information from a diverse set of pre-specified factor models. Compared with existing methods, the pooled clone strategies yield consistently lower tracking errors, generate less severe portfolio drawdowns, and require substantially smaller trading volume. The pooled hedge fund clones also provide economic benefits in a portfolio allocation context.

This paper empirically investigates how sentences to be assigned at trial impact plea bargaining. The analysis is based on the model of bargaining with asymmetric information by Bebchuk, 1984. I provide conditions for the nonparametric identification of the model, propose a consistent nonparametric estimator, and implement it using data on criminal cases from North Carolina. Employing the estimated model, I evaluate how different sentencing reforms affect the outcome of criminal cases. My results indicate that lower mandatory minimum sentences could greatly reduce the total amount of incarceration time assigned by the courts, but may increase conviction rates. In contrast, the broader use of non‐incarceration sentences for less serious crimes reduces the number of incarceration convictions, but has a very small effect over the total assigned incarceration time. I also consider the effects of a ban on plea bargains. Depending on the case characteristics, over 20 percent of the defendants who currently receive incarceration sentences would be acquitted if plea bargains were forbidden.