We investigate the impact of wealth redistribution on economic growth, building on Kelly’s (1956) optimal investment portfolio theory. A growth-optimal policy redistributes wealth from “lucky” overperforming individuals to underperforming ones, minimizing the systematic component of this redistribution in a myopic fashion. That is, the optimal policy minimizes the discrepancy between endowments and outcomes, counterfactually taking outcomes as independent of endowments. The myopia in this result follows from a decoupling argument that allows us to model the planner as independently choosing a growth-maximizing policy and a pattern of wealth circulation. (JEL D31, E23, G41, G51, H23, O41)

In a model inspired by neuroscience, we study choice between lotteries as a process of encoding and decoding noisy perceptual signals. The implications of this process for behavior depend on the decision-maker's understanding of risk. When the aggregation of perceptual signals is coarse, encoding and decoding generate behavioral risk attitudes even for vanishing perceptual noise. We show that the optimal encoding of lottery rewards is S-shaped and that low-probability events are optimally oversampled. Taken together, the model can explain adaptive-risk attitudes and probability weighting, as in prospect theory. Furthermore, it predicts that risk attitudes are influenced by the anticipation of risk, time pressure, experience, salience, and availability heuristics.

Evidence suggests that consumers do not perfectly optimize, contrary to a critical assumption of classical consumer theory. We propose a model in which consumer types can vary in both their preferences and their choice behavior. Given data on demand and the distribution of prices, we identify the set of possible values of the consumer surplus based on minimal rationality conditions: every type of consumer must be no worse off than if they either always bought the good or never did. We develop a procedure to narrow the set of surplus values using richer data sets and provide bounds on counterfactual demands.

This paper examines connections between stochastic growth and decision problems. We use tools from the theory of large deviations to show that wishful thinking decision problems are equivalent to utility maximization problems, both of which are equivalent to growth maximization under idiosyncratic risk. Rational inattention problems are equivalent to growth-optimal portfolio problems, both of which are equivalent to growth maximization under aggregate risk. Stochastic growth generates extreme inequality, with nearly all wealth eventually held by those who happen to have faced empirical distributions that match the solution to the wishful thinking or rational inattention problem. (JEL D31, D81, D82, D83, G51, O41)

In a model inspired by neuroscience, we show that constrained optimal perception encodes lottery rewards using an S-shaped encoding function and over-samples low-probability events. The implications of this perception strategy for behavior depend on the decision-maker's understanding of the risk. The strategy does not distort choice in the limit as perception frictions vanish when the decision-maker fully understands the decision problem. If, however, the decision-maker underrates the complexity of the decision problem, then risk attitudes reflect properties of the perception strategy even for vanishing perception frictions. The model explains adaptive risk attitudes and probability weighting as in prospect theory and, additionally, predicts that risk attitudes are strengthened by time pressure and attenuated by anticipation of large risks.

This paper considers a model where a risk-neutral individual can receive both a signal about whether an outcome is above a certain threshold (a reference point) and a continuous signal on the value of the outcome. The paper shows that, given the existence of these two signals for an outcome, the expected value function of the outcome exhibits diminishing sensitivities both above and below the reference point. Furthermore, in the examples considered, loss aversion occurs if the reference point is not too high. The paper shows how the informativeness of each signal affects the declining sensitivities and loss aversion effects, and how the model reduces to risk-neutral decision-making when the continuous signal on the value of the outcome is perfectly informative. The loss aversion effects occur for low reference points because the reference point is below the expected value of the outcome and because of the greater likelihood of receiving the signal that the outcome is above the reference point. The paper obtains the same result in a rational inattention framework because the individual may pay greater attention to the less likely low outcomes.

A health authority chooses a binary action for each of several individuals that differ in their pretest probabilities of being infectious and in the additive losses associated with two types of decision errors. The authority is endowed with a portfolio of tests that differ in their sensitivities and specificities. We derive a simple necessary condition for optimality of test allocation. In special cases, precision parameters of the allocated test are monotone in the individuals' types. We characterize the marginal benefit of a test, provide an algorithmic solution for the test-allocation problem and consider the benefits of confirmatory testing. (c) 2021 Elsevier Inc. All reserved.

We study the impact of manipulating the attention of a decision‐maker who learns sequentially about a number of items before making a choice. Under natural assumptions on the decision‐maker's strategy, directing attention toward one item increases its likelihood of being chosen regardless of its value. This result applies when the decision‐maker can reject all items in favor of an outside option with known value; if no outside option is available, the direction of the effect of manipulation depends on the value of the item. A similar result applies to manipulation of choices in bandit problems.

To prevent the spread of an infection, an organization obeys social distancing restrictions and thus limits the number of its members physically present on a given day. We study rotation schemes in which mutually exclusive groups are active on different days. The frequency of rotation affects risk over the duration of diffusion prior to the time the organization is able to react to the infection. If this reaction time is speedy, then such risk is undesirable because prevalence is initially convex in time. In this case, frequent rotation acts as insurance against exposure-time risk and is optimal. Infrequent rotation becomes optimal if the organization reacts slowly. Cross-mixing of the rotating subpopulations is detrimental because it increases contacts between sick and healthy individuals. However, the effect of mixing is small if the terminal prevalence is low in the absence of mixing. This paper was accepted by Joshua Gans, business strategy.

This article assesses the merit of a test through the lenses of economics, with applications to SARS-CoV-2. This allows us to rank distinct tests and to show that this ranking is not universal; it depends on the pre-test information available to the decision-maker and the losses stemming from incorrect actions. We provide a method to select, from multiple tests with different sensitivity and specificity, the test that helps the decision-maker the most to achieve her objective.

We study the impact of manipulating the attention of a decision-maker who learns sequentially about a number of items before making a choice. Under natural assumptions on the decision-maker’s strategy, directing attention toward one item increases its likelihood of being chosen regardless of its value. This result applies when the decision-maker can reject all items in favor of an outside option with known value; if no outside option is available, the direction of the effect of manipulation depends on the value of the item. A similar result applies to manipulation of choices in bandit problems.

A memoryless agent can acquire arbitrarily many signals. After each signal observation, she either terminates and chooses an action, or she discards her observation and draws a new signal. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the benefits of selective memory applied to the extracted signals. Implications-obtained in simple examples-include (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.

We study the impact of manipulating the attention of a decision-maker who learns sequentially about a number of items before making a choice. Under natural assumptions on the decision-maker's strategy, forcing attention toward one item increases its likelihood of being chosen.

When an agent chooses between prospects, noise in information processing generates an effect akin to the winner’s curse. Statistically unbiased perception systematically overvalues the chosen action because it fails to account for the possibility that noise is responsible for making the preferred action appear to be optimal. The optimal perception pattern exhibits a key feature of prospect theory, namely, overweighting of small probability events (and corresponding underweighting of high probability events). This bias arises to correct for the winner’s curse effect.

We present a two-stage coordination game in which early choices of experts with special interests are observed by followers who move in the second stage. We show that the equilibrium outcome is biased toward the experts’ interests even though followers know the distribution of expert interests. Expert influence is fully decentralised in the sense that each individual expert has a negligible impact. The bias in favour of experts results from a social learning effect that is multiplied through a coordination motive. We apply our results to the onset of social movements and to the diffusion of products with network externalities. When a large group of agents seek to coordinate their behaviour in an uncertain environment, it is common for individuals to look to better informed experts for guidance. The preferences of these experts may not coincide with those of the agents who observe their choices. In light of this conflict, do the experts’ preferences influence mass opinion and behaviour? We show that the choices of expert early movers can have a large effect on outcomes, biasing the results toward their own preferences. The effect arises even though our model features Bayesian decision-makers who

In a choice model, we characterize the loss induced by misperceptions of payoff-relevant parameters across a distribution of decision problems. When the agent cannot avoid misperceptions but has some control over the distribution of errors, we show that strategies that minimize loss from misperception exhibit systematic biases, akin to some documented in the behavioural and psychological literatures. We include illusion of control, order effect, overprecision, and overweighting of small probabilities as illustrative examples.

When observable cues correlate with optimal choices, habit-driven behavior can alleviate cognition costs. We experimentally study the degree of sophistication in habit formation and cue selection. To this end, we compare lab treatments that differ in the information provided to subjects, holding fixed the serial correlation of optimal actions. We find that a particular cue – own past action – affects behavior only in treatments in which this habit is useful. The result suggests that caution is warranted when modeling habits via a fixed non-separable utility. Despite this sophistication, lab behavior also reveals myopia in information acquisition.

In a choice model, we characterize the loss induced by misperceptions of payoff-relevant parameters across a distribution of decision problems. When the agent cannot avoid misperceptions but has some control over the distribution of errors, we show that strategies that minimize loss from misperception exhibit systematic biases, akin to some documented in the behavioral and psychological literatures. We include illusion of control, order effect, overprecision, and overweighting of small probabilities as illustrative examples.