Total Recall, 2026,
with Stewart
A decision-maker observes a signal, forgets it, and
acts on its garbled record. Because her information sets are not nested,
delegating to her future self can be unattractive: for generic memory channels,
some interim selves are better off with a blank memory in some decision
problems, despite stable preferences. We characterize channels immune to such
deviations in every decision problem. Every memory state must either recall the
payoff-relevant information perfectly or induce one and the same belief. When interim selves can manipulate the record
rather than merely suppress it, only perfect recall and total amnesia survive.
The Importance of Unlikely Events, 2026, with Eden and Samuelson, presentation
We study an expected-utility maximizer controlling a
stochastic growth process over a long horizon. Using large deviations theory,
we characterize how risk attitudes determine which vanishingly rare events
govern optimal choice. Under constant relative risk aversion, information and
hedging have only subexponential value: asymptotically, even perfect foresight
of future shock frequencies is not worth any permanent reduction in per-period
returns. For generalized CRRA utilities, optimal choice maximizes hope for
extraordinary wealth subject to a constraint that fear of ruin does not
dominate. Information can then have exponential value, but hedging across two
actions makes its marginal value subexponential.
Robust Latent Data
Representations, 2026, with Samuelson, presentation
We study how an empirical Bayesian applies a
latent-type theory to an observed sample. She starts with primitive types, each
a distribution over observables, but may find the sample inconsistent with any
mixture of the types. We axiomatically characterize a familiar statistical
procedure---maximum-likelihood estimation followed by Bayesian updating---that adjusts
the type definitions to match the sample.
This procedure endogenizes latent types, usually primitive in economic
theory, and addresses the wedge between predictions and observations left open
by Berk-Nash reasoning. Economic
examples illustrate the interplay between data and the agent's view of the
latent types.
Growth and
Redistribution: The Hedging Perspective, with Samuelson, 2025,
American Economic
Review: Insights, 7(2), 250–267, online appendix, presentation
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.
Risk Perception: Measurement
and Aggregation, 2025,
JEEA 23(4), 1309–1349, with Netzer, Robson and Kocourek, presentation
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.
Boundedly Rational Demand, 2024, Theoretical Economics 19(4),
1415-1442, with Kocourek and Stewart
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 datasets and provide bounds on counterfactual
demands.
Decision Theory and Stochastic
Growth, with Robson
and Samuelson, American Economic Review: Insights 5(3), 2023, 357-76 presentation, přednáška, homework
assignment
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.
Attention
Please! with Gossner and Stewart, 2021, Econometrica
89(4), 1717-1751, presentation, puzzle
Optimal Test Allocation,
2021, with Ely, Galeotti and Jann, J. Econ. Theory 105236
Rotation as Contagion
Mitigation, 2021, with Ely and Galeotti, Management Science, 67(5), 3117-3126
(ideas from this paper have been incorporated into the DELVE
report of the Royal Society)
Habits as Adaptations: An
Experimental Study, 2020, with Matyskova, Rogers, and Sun, presentation, Game
Econ Behav 122, 391-406
Selective
Sampling with Information-Storage Constraints, 2020, with Jehiel, presentation, Economic Journal, 1753-1781
On the Cost of Misperception:
General Results and Behavioral Applications, 2018, with Gossner, J. Econ.
Theory 177, 816-847, presentation
Rational Inattention Dynamics:
inertia and delay in decision-making, 2017, with Stewart
and Matějka, Econometrica 85(2), 521-553,
presentation, popularizační
přednáška
Perceiving Prospects Properly,
2016, with Stewart,
American Economic Review 106,
1601-31, presentation, press
summary by AEA
Price Distortions under Coarse
Reasoning with Frequent Trade, 2015, with Stewart, J.
Econ. Theory 159, 574-595, presentation, supplement
Influential Opinion Leaders,
2014, with Stewart
and Loeper, Economic
Journal 124, 1147-1167
Tractable Dynamic
Global Games and Applications, 2013, with Mathevet, J. Econ. Theory 148,
2583-2619
Reversibility in Dynamic
Coordination Problems, 2013, with Kováč, Game Econ Behav 77, 298-320
Who Matters in Coordination Problems?,
2012, with Sákovics, American
Economic Review 102(7), 3439-3461
Dynamic
Coordination with Private Learning, 2012, with Dasgupta and Stewart, Game Econ Behav 74, 83-101
Communication, Timing, and Common Learning,
2011, with Stewart, J.
Econ. Theory 146, 230-247,
(the paper explained on the blog
of Jeff Ely)
Contagion through Learning, 2008, with Stewart, Theoretical
Economics 3, 431-458
Coordination of Mobile Labor, 2008, J.
Econ. Theory 139(1), 25-46
Coordination Cycles, 2008, Game Econ Behav 63(1), 308-327
The Effects of Risk Aversion in Mixed-Strategy
Equilibria of 2x2 Games, 2007, with Engelmann, Game Econ Behav 60, 381-388
A
Trace of Anger is Enough: On the Enforcement of Social Norms, 2007, Economics
Bulletin, vol. 8.
Dynamic
scaling and universality in evolution of fluctuating random networks, 2002,
with Kotrla and Slanina, Europhys. Lett. 60, 14-20