Rational Inattention Dynamics: Inertia and Delay in Decision-Making, with Jakub Steiner and Filip Matějka
We solve a general class of dynamic rational-inattention problems in which an agent repeatedly acquires costly information about an evolving state and selects actions. Optimal behavior resembles that in a dynamic logit model. The distribution of actions at each decision node depends on the expected payoffs (not including information costs) and on an endogenous default rule that does not depend on the realized history of states. We apply the general solution to the study of (i) the sunk-cost fallacy; (ii) inertia in actions leading to lagged adjustments to shocks; and (iii) the tradeoff between accuracy and delay in decision-making.
Perceiving Prospects Properly, with Jakub Steiner, revise and resubmit at the American Economic Review
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 patterns share key features with prospect theory,
namely, overweighting of small probability events (and corresponding
underweighting of high probability events), status quo bias, and
reference-dependent S-shaped valuations. These biases arise to
correct for the winner’s curse effect.
Price Distortions under Coarse Reasoning, with Jakub Steiner, conditionally accepted at the Journal of Economic Theory
study the effect of frequent trading opportunities and categorization
on pricing of a risky asset. Frequent opportunities to trade can lead
to large distortions in prices if some agents forecast future prices
using a simplified model of the world that fails to distinguish
between some states. In the limit as the period length vanishes,
these distortions take a particular form: the price must be the same
in any two states that a positive mass of agents categorize together.
Price distortions therefore tend to be large when different agents
categorize states in different ways, even if each individual’s
categorization is not very coarse.
Influential Opinion Leaders, with Antoine Loeper and Jakub Steiner, The Economic Journal, Vol. 124, December 2014, 1147-1167
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 and account for it when evaluating
observed experts’ actions. Expert influence is fully decentralized
in the sense that each individual expert has a negligible impact. The
bias in favor of experts results from a social learning effect that
is multiplied through a coordination motive. We show that the total
effect can be large even if the direct social learning effect is
small. We apply our results to the diffusion of products with network
externalities and the onset of social movements.
Dynamic Coordination with Individual Learning, with Amil Dasgupta and Jakub Steiner, Games and Economic Behavior, Vol. 74 (1), January 2012, 83-101
study coordination in dynamic global games with private learning.
Players choose whether and when to invest irreversibly in a project
whose success depends on its quality and the timing of investment.
Players gradually learn about project quality. We identify conditions
on temporal incentives under which, in sufficiently long games,
players coordinate on investing whenever doing so is not dominated.
Roughly speaking, this outcome occurs whenever players' payoffs are
sufficiently tolerant of non-simultaneous coordination. We also
identify conditions under which players coordinate on the
risk-dominant action. We provide foundations for these results in
terms of higher order beliefs.
Nonmanipulable Bayesian Testing, Journal of Economic Theory, Vol. 146 (5), September 2011, 2029-2041
paper considers the problem of testing an expert who makes
probabilistic forecasts about the outcomes of a stochastic process. I
show that, as long as uninformed experts do not learn the correct
forecasts too quickly, a likelihood test can distinguish informed
from uninformed experts with high prior probability. The test rejects
informed experts on some data-generating processes; however, the set
of such processes is topologically small. These results contrast
sharply with many negative results in the literature.
Communication, Timing, and Common Learning, with Jakub Steiner, Journal of Economic Theory, Vol. 146 (1), January 2011, 230-247
study the effects of stochastically delayed communication on common
knowledge acquisition (common learning). If messages do not report
dispatch times, communication prevents common learning under general
conditions even if common knowledge is acquired without
communication. If messages report dispatch times, communication can
destroy common learning under more restrictive conditions. The
failure of common learning in the two cases is based on different
infection arguments. Communication can destroy common learning even
if it ends in finite time, or if agents communicate all of their
information. We also identify conditions under which common learning
is preserved in the presence of communication. This paper
largely supercedes our earlier note, "Communication
Can Destroy Common Learning."
Contagion through Learning, with Jakub Steiner, Theoretical Economics, Vol. 3 (4), December 2008, 431-458
Previously titled "Learning by Similarity in Coordination Problems."
study learning in a large class of complete information normal form
games. Players continually face new strategic situations and must
form beliefs by extrapolation from similar past situations. The use
of extrapolations in learning may generate contagion of actions
across games even if players learn only from games with payoffs very
close to the current ones. Contagion may lead to unique long-run
outcomes where multiplicity would occur if players learned through
repeatedly playing the same game. The process of contagion through
learning is formally related to contagion in global games, although
the outcomes generally differ. We characterize the long-run outcomes
of learning in terms of iterated dominance in a related incomplete
information game with subjective priors, which clarifies the
connection to global games.
Testing Multiple Forecasters, with Yossi Feinberg, Econometrica, Vol. 76 (3), May 2008, 561-582
consider a cross-calibration
of predictions by multiple potential experts in a stochastic
environment which tests whether each expert is calibrated conditional
on the predictions made by other experts. We show that this test is
good in the sense that a true expert – one informed of the true
distribution of the process – is guaranteed to pass the test no
matter what the other potential experts do, and false experts will
fail the test on all but a small (category one) set of true
distributions. Furthermore, even when there is no true expert
present, a test similar to cross-calibration cannot be simultaneously
manipulated by multiple false experts, but at the cost of failing
some true experts.
Robust Conventions and the Structure of Social Networks
Universal Deformations, Rigidity, and Ihara's Cocycle, Communications in Algebra, Vol. 31(2), 2003, pp. 901-943.
Goldbach's Conjecture for Z[x] (with Amarpreet Rattan), Mathematical Reports of the Academy of Science, Vol. 20(3), 1998, pp. 83-85.