Subjects in a laboratory experiment withdraw earnings from a cash reserve evolving according to an arithmetic Brownian motion in near-continuous time. Aggressive withdrawal policies expose subjects to risk of bankruptcy, but the policy that maximizes expected earnings need not maximize the odds of survival. When profit maximization is consistent with high rates of survival (HS parameters), subjects adjust decisively towards the optimum. When survival and profit maximization are sharply at odds (LS parameters), subjects persistently (and sub-optimally) hoard excess cash in an evident effort to improve survival rates. The design ensures that this hoarding is not due to standard risk aversion. Analysis of period-to-period adjustments in strategies suggests instead that hoarding is due to a widespread bias towards survival in the subject population. Robustness treatments varying feedback, parameters, and framing fail to eliminate the bias.

We provide evidence that classic lottery anomalies like probability weighting and loss aversion are not special phenomena of risk. They also arise (and often with equal strength) when subjects evaluate deterministic, positive monetary payments that have been disaggregated to resemble lotteries. Thus, we find, e.g., apparent probability weighting in settings without probabilities and loss aversion in settings without scope for loss. Across subjects, anomalies in these deterministic tasks strongly predict the same anomalies in lotteries. These findings suggest that much of the behavior motivating our most important behavioral theories of risk derive from complexity-driven mistakes rather than true risk preferences. (JEL C91, D44, D81, D91)

We study the complexity of rules by paying experimental subjects to implement a series of algorithms and then eliciting their willingness-to-pay to avoid implementing them again in the future. The design allows us to examine hypotheses from the theoretical “automata” literature about the characteristics of rules that generate complexity costs. We find substantial aversion to complexity and a number of regularities in the characteristics of rules that make them complex and costly for subjects. Experience with a rule, the way a rule is represented, and the context in which a rule is implemented (mentally versus physically) also influence complexity. (JEL C73, D11, D12, D83, D91)

Abstract We provide evidence for a bias that we call “representative signal distortion” (RSD), which is particularly relevant to settings of statistical discrimination. Experimental subjects distort their evaluation of new evidence on individual group members and interpret such information to be more representative of the group to which the individual belongs (relative to a reference group) than it really is. This produces a discriminatory gap in the evaluation of members of the two groups. Because it is driven by representativeness, the bias (and the discriminatory gap) disappears when subjects are prevented from contrasting different groups; because it is a bias in the interpretation of information, it disappears when subjects receive information before learning of the individual’s group. We show that this bias can be easily estimated from appropriately constructed data sets and can be distinguished from previously documented inferential biases in the literature. Importantly, we document how removing the bias produces a kind of free lunch in reducing discrimination, making it possible to significantly reduce discrimination without lowering accuracy of inferences.

The theory of continuous time games (Simon and Stinchcombe (1989), Bergin and MacLeod (1993)) shows that continuous time interactions can generate very different equilibrium behavior than conventional discrete time interactions. We introduce new laboratory methods that allow us to eliminate natural inertia in subjects' decisions in continuous time experiments, thereby satisfying critical premises of the theory and enabling a first‐time direct test. Applying these new methods to a simple timing game, we find strikingly large gaps in behavior between discrete and continuous time as the theory suggests. Reintroducing natural inertia into these games causes continuous time behavior to collapse to discrete time‐like levels in some settings as predicted by subgame perfect Nash equilibrium. However, contra this prediction, the strength of this effect is fundamentally shaped by the severity of inertia: behavior tends towards discrete time benchmarks as inertia grows large and perfectly continuous time benchmarks as it falls towards zero. We provide evidence that these results are due to changes in the nature of strategic uncertainty as inertia approaches the continuous limit.

We study prisoners' dilemmas played in continuous time with flow payoffs accumulated over 60 seconds. In most cases, the median rate of mutual cooperation is about 90 percent. Control sessions with repeated matchings over eight subperiods achieve less than half as much cooperation, and cooperation rates approach zero in one-shot sessions. In follow-up sessions with a variable number of subperiods, cooperation rates increase nearly linearly as the grid size decreases, and, with one-second subperiods, they approach continuous levels. Our data support a strand of theory that explains how capacity to respond rapidly stabilizes cooperation and destabilizes defection in the prisoner's dilemma. (JEL C72, C78, C91)

We study David Gale's (1963) economy using laboratory markets. Tatonnement theory predicts prices will diverge from an equitable interior equilibrium toward infinity or zero depending only on initial prices. The inequitable equilibria determined by these dynamics give all gains from exchange to one side of the market. We show surprisingly strong support for these predictions. In most sessions one side of the market eventually outgains the other by more than 20 times, leaving the disadvantaged side to trade for mere pennies. We also find preliminary evidence that these dynamics are sticky, resisting exogenous interventions designed to reverse their trajectories. (JEL C92, D50)

Human subjects decide when to sink a fixed cost C to seize an irreversible investment opportunity whose value V is governed by Brownian motion. The optimal policy is to invest when V first crosses a threshold V* = (1 + w*)C, where the wait option premium w* depends on drift, volatility, and expiration hazard parameters. Subjects in the Low w* treatment on average invest at values quite close to optimum. Subjects in the two Medium and the High w* treatments invested at values below optimum, but with the predicted ordering, and values approached the optimum by the last block of 20 periods.

The influence of behavioral biases on aggregate outcomes depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. In betting market, auction and committee experiments, we document that some errors are strongly reduced through self-selection, while others are not affected at all or even amplified. A large part of this variation is explained by differences in the relationship between confidence and performance. In some tasks, they are positively correlated, such that self-selection attenuates errors. In other tasks, rational and biased people are equally confident, such that self-selection has no effects on aggregate quantities. (JEL C91, D44, D91)

Several impatient investors with private costs C i face an indivisible irreversible investment opportunity whose value V is governed by geometric Brownian motion. The first investor i to seize the opportunity receives the entire payoff, V-C i . We characterize the symmetric Bayesian Nash equilibrium for this game. A laboratory experiment confirms the model's main qualitative predictions: competition drastically lowers the value at which investment occurs; usually the lowest-cost investor preempts the other investors; observed investment patterns in competition (unlike monopoly) are quite insensitive to changes in the Brownian parameters. Support is more qualified for the prediction that markups decline with cost. (JEL C73, D44, D82, G31)