Carl Heese



I'm an Assistant Professor in Economics at the University of Vienna, with research interest in microeconomic theory (primary), political theory and behavioral economics (secondary). I received my Ph.D. from the University of Bonn.



  Email: heese(at)uni-bonn.de
  Contact: +49 151 1083 7212
  Office: Oskar-Morgenstern-Platz 1, 1090 Wien

  Curriculum Vitae (PDF)

Working Papers

Voter Attention and Distributive Politics

link to CRC discussion paper

[abstract]

This paper studies theoretically how endogenous attention to politics affects social welfare and its distribution. When information of citizens about uncertain policy consequences is exogenous, a median voter theorem holds. When information is endogenous, attention shifts election outcomes into a direction that is welfare-improving. For a large class of settings, election outcomes maximize a weighted welfare rule. The implicit decision weight of voters with higher utilities is higher, but less so, when information is more cheap. In general, decision weights are proportional to how informed voters are. The results imply that uninformed voters have effectively almost no voting power, that the ability to access and interpret information is a critical determinant of democratic participation, and that elections are susceptible to third-party manipulation of voter information.

Persuasion and Information Aggregation in Elections

(with Stephan Lauermann, link to discussion paper , link to current version )

[abstract]

This paper studies a large majority election with voters who have heterogeneous, private preferences and exogenous private signals. We show that a Bayesian persuader can implement any state-contingent outcome in some equilibrium by providing additional information. In this setting, without the persuader's information, a version of the Condorcet Jury Theorem would hold (Feddersen and Pesendorfer, 1997). Persuasion does not require detailed knowledge of the distribution of the voters' exogenous private information and preferences: the same additional information is effective across environments. Also, the results require almost no commitment power by the persuader. Finally, a numerical example shows that persuasion is effective in elections with as few as 15 voters.

Motivated Information Acquisition (with Si Chen)

My co-author was awarded the Econ Job Market Best Paper Award 6th Edition for this paper.
(UniCredit Foundation & European Economic Association), link to UPDATED version (NEW!) ,

[abstract]

The literature on motivated reasoning argues that people skew their personal beliefs so that they can feel moral when acting selfishly. We study dynamic information acquisition of decision-makers with a motive to form positive moral self-views and a motive to act selfishly. Theoretically and experimentally, we find that individuals ``fish for desirable information’’: they are more likely to continue (stop) acquiring information having received mostly information suggesting that acting selfishly is harmful (harmless) to others. Empirically, the tendency for this behavior is stronger among individuals with above-median cognitive ability. We discuss the resulting welfare effects. We relate our results to the literature on interpersonal Bayesian persuasion (Kamenica and Gentzkow, 2011).

Work in Progress

Social Learning with State-Dependent Observations

Note

[abstract]

In this note, I study a variant of the canonical binary-state binary-choice social learning model (Bikhchandani et al., 1992). An individual would like to choose an action only in the high state. When making her own decision, she observes previous decision-makers who chose the action. Importantly, the likelihood of observing the action of previous decision-maker depends on the state. I show that when observing the action is more likely in the low state, the individual faces an inference problem: does she observe many actions because the state is high and previous decision-makers had private information about this or because the state is low and previous actions are more visible. In this situation, learning is confounded (Smith and Sorensen, 2000).