**Unpublished:**

**On
Second Thoughts and Resulting Behavioral Biases, **with
Philippe Jehiel, work
in progress

We
propose a model of constrained information processing and make a
prediction about the constrained-optimal stochastic choice that is
robust to the details of the feasible information
structures.Decision-maker collects payoff-relevant information until
she reaches her cognitive constraint, at which point she either
terminates the decision process and chooses an action, or restarts
the process. By conditioning the probability of termination on the
information collected, the decision-maker affects correlation between
the payoff state and the terminal action. The constrained-optimal
stochastic choice rule satisfies a *second-thought-free*
condition: Given her information, terminating decision-maker is
indifferent between the termination and the restart of the decision
process. The condition partially identifies preferences from choice
data. The constrained-optimal choice rule exhibits (i) confirmation
bias, (ii) speed-accuracy complementarity, (iii) overweighting of
rare events, and (iv) salience effect: (i) The decision process is
likely to terminate at an information set supporting choice that is a
priori attractive. (ii) Delayed response indicates second thoughts
and the surprising state, in which mistakes occur relatively often.
(iii) A constrained-optimal belief formation process focuses on a
priori rare events such as flight accidents, since these surprising
events are more informative than common events. (iv) In perceptual
tasks, the constrained-optimal perception discriminates in favor of
distinct states that are easily distinguished from other states.

On the Cost of Misperception: General Results and Related Behavioural Biases, with Olivier Gossner, this draft Aug 2017

We study perception biases arising under second-best perception strategies. An agent correctly observes a parameter that is payoff-relevant in many decision problems that she encounters in her environment but is unable to retain all the information until her decision. A designer of the decision process chooses a perception strategy that determines the distribution of the perception errors. If some information loss is unavoidable due to cognition constraints, then (under additional conditions) the optimal perception strategy exhibits the illusion of control, overconfidence, and optimism.

**Publications:**

1.
Rational Inattention Dynamics: inertia and delay in
decision-making 2017,
*Econometrica
85(2), *521-553*,*with
Colin
Stewart and Filip
Matějka,

Presentation, Popularizační přednáška v Češtině

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. The solution resembles the choice rule in a dynamic logit model, but it is biased towards an optimal default rule that depends only on the history of actions, not on the realized state. We apply the general solution to the study of (i) the status quo bias; (ii) inertia in actions leading to lagged adjustments to shocks; and (iii) the tradeoff between accuracy and delay in decision-making.

2.
Perceiving Prospects Properly, with Colin
Stewart, 2016, *American
Economic Review 106, 1601-31.*

Presentation, Summary for press by AEA

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.

3.
Price Price Distortions under Coarse Reasoning with
Frequent Trade, with Colin
Stewart, 2015, *J.
Econ. Theory 159,* *574-595.
*Presentation,
Supplement

4.
Influential Opinion Leaders, with Colin
Stewart and Antoine
Loeper, 2014, *Economic
Journal 124, 1147–1167.*

5.
Tractable Dynamic Global Games and
Applications, with Laurent
Mathevet, 2013, *J.
Econ. Theory *148,
2583–2619*.
*(previously
circulated as “Sand in the Wheels: A Dynamic Global Game
Approach”)

6.
Reversibility in Dynamic Coordination Problems,
with Eugen Kováč,
2013, *Games
and Economic Behavior 77, 298–320.*
(An
older version)

7. Who
Matters in Coordination Problems?, with József
Sákovics, 2012, *American
Economic Review 102(7), 3439–3461*.
(An older version)

8.
Dynamic Coordination with Private
Learning, with Amil
Dasgupta and Colin
Stewart, 2012, *Games
and Economic Behavior 74, 83–101.*

9.
Communication, Timing, and Common
Learning, with Colin
Stewart, 2011, *J.
Econ. Theory 146, 230–247. *(An
older version), The paper explained on the blog
of Jeff Ely.

10. Contagion through
Learning, with Colin
Stewart, 2008, *Theoretical
Economics 3, 431–458.*

11.
Coordination of Mobile Labor, 2008,
*J.
Econ. Theory 139(1), 25–46.*
(An
older version)

12. Coordination
Cycles, 2008, *Games
and Economic Behavior 63(1), 308–327.*

13. The
Effects of Risk Aversion in Mixed-Strategy Equilibria of 2x2 Games,
with Dirk Engelmann,
2007, *Games
and Economic Behavior 60, 381–388*.

14. A
Trace of Anger is Enough: On the Enforcement of Social Norms,
2007, *Economics
Bulletin, vol. 8*.
(An expanded version)

15. Dynamic
scaling and universality in evolution of fluctuating random
networks, with Kotrla M. and F. Slanina, 2002, *Europhys.
Lett. 60, 14*–*20.*