We examine short selling in US stocks based on new SEC-mandated data for 2005. There is a tremendous amount of short selling in our sample: short sales represent 24% of NYSE and 31% of Nasdaq share volume. Short sellers increase their trading following positive returns and they correctly predict future negative abnormal returns. These patterns are robust to controlling for voluntary liquidity provision and for opportunistic risk-bearing by short sellers. The results are consistent with short sellers trading on short-term overreaction of stock prices. A trading strategy based on daily short-selling activity generates significant positive returns during the sample period.

A new methodology is proposed to estimate theoretical prices of financial contingent claims whose values are dependent on some other underlying financial assets. In the literature, the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples. This paper proposes a simulation-based method. When it is used in connection with ML, it can improve the finite-sample performance of the ML estimator while maintaining its good asymptotic properties. The method is implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond and bond option pricing model. It is especially favored when the bias in ML is large due to strong persistence in the data or strong nonlinearity in pricing functions. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims when ML is biased. The bias reductions are sometimes accompanied by reductions in variance. Empirical applications to U.S. Treasury bills highlight the differences between the bond prices implied by the simulation-based approach and those delivered by ML. Some consequences for the statistical testing of contingent-claim pricing models are discussed.

A decade ago in a paper, “Reassessing Discretionary Fiscal Policy,” published in the Journal of Economic Perspectives, I concluded that “in the current context of the US economy, it seems best to let fiscal policy have its main countercyclical impact through the automatic stabilizers. ... It would be appropriate in the current circumstances for discretionary fiscal policy to be saved explicitly for longer term issues, requiring less frequent changes.” This was not an unusual conclusion at the time. As Martin Eichenbaum (1997) put it, “There is now widespread agreement that countercyclical discretionary fiscal policy is neither desirable nor politically feasible,” or, according to Martin Feldstein (2002), “There is now widespread agreement in the economics profession that deliberate ‘countercyclical’ discretionary policy has not contributed to economic stability and may have actually been destabilizing in the past.” Despite this widespread agreement of a decade ago, there has recently been a dramatic revival of interest in discretionary fiscal policy. The purpose of this short paper is to review the empirical evidence during the past decade and determine whether it calls for such a revival. I find that it does not.

We propose a broad generalization of standard choice-theoretic welfare economics that encompasses a wide variety of nonstandard behavioral models. Our approach exploits the coherent aspects of choice that those positive models typically attempt to capture. It replaces the standard revealed preference relation with an unambiguous choice relation: roughly, x is (strictly) unambiguously chosen over y (written xP*y) iff y is never chosen when x is available. Under weak assumptions, P* is acyclic and therefore suitable for welfare analysis; it is also the most discerning welfare criterion that never overrules choice. The resulting framework generates natural counterparts for the standard tools of applied welfare economics and is easily applied in the context of specific behavioral theories, with novel implications. Though not universally discerning, it lends itself to principled refinements.

Most previous research tests market efficiency using average abnormal trading profits on dynamic trading strategies, and typically rejects the joint hypothesis of market efficiency and an asset pricing model. In contrast, we adopt the perspective of a buy‐and‐hold investor and examine stock price levels. For such an investor, the price level is more relevant than the short‐horizon expected return, and betas of cash flow fundamentals are more important than high‐frequency stock return betas. Our cross‐sectional tests suggest that there exist specifications in which differences in relative price levels of individual stocks can be largely explained by their fundamental betas.

We find a significant discontinuity in the pooled distribution of monthly hedge fund returns: The number of small gains far exceeds the number of small losses. The discontinuity is present in live and defunct funds, and funds of all ages, suggesting that it is not caused by database biases. The discontinuity is absent in the 3 months culminating in an audit, suggesting it is not attributable to skillful loss avoidance. The discontinuity disappears when using bimonthly returns, indicating a reversal in fund performance following small gains. This result suggests that the discontinuity is caused at least in part by temporarily overstated returns.

Most previous research tests market efficiency using average abnormal trading profits on dynamic trading strategies, and typically rejects the joint hypothesis of market efficiency and an asset pricing model. In contrast, we adopt the perspective of a buy-and-hold investor and examine stock price levels. For such an investor, the price level is more relevant than the short-horizon expected return, and betas of cash flow fundamentals are more important than high-frequency stock return betas. Our cross-sectional tests suggest that there exist specifications in which differences in relative price levels of individual stocks can be largely explained by their fundamental betas.

A norm of 50–50 division appears to have considerable force in a wide range of economic environments, both in the real world and in the laboratory. Even in settings where one party unilaterally determines the allocation of a prize (the dictator game), many subjects voluntarily cede exactly half to another individual. The hypothesis that people care about fairness does not by itself account for key experimental patterns. We consider an alternative explanation, which adds the hypothesis that people like to be perceived as fair. The properties of equilibria for the resulting signaling game correspond closely to laboratory observations. The theory has additional testable implications, the validity of which we confirm through new experiments.

This paper reports the first laboratory study of the swing voter's curse and provides insights on the larger theoretical and empirical literature on “pivotal voter” models. Our experiment controls for different information levels of voters, as well as the size of the electorate, the distribution of preferences and other theoretically relevant parameters. The design varies the share of partisan voters and the prior belief about a payoff relevant state of the world. Our results support the equilibrium predictions of the Feddersen-Pesendorfer model. The voters act as if they are aware of the swing voter's curse and adjust their behaviour to compensate. While the compensation is not complete and there is some heterogeneity in individual behaviour, we find that aggregate outcomes, such as efficiency, turnout and margin of victory, closely track the theoretical predictions.

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