research

2024

1. 

   Strategic communication of narratives

   Gerrit Bauch, and Manuel Foerster

   2024

   Job Market Paper

   Abs arXiv HTML

   We conceptualize the communication of narratives as a cheap-talk game under model uncertainty. The sender has private information about the true data generating process of publicly observable data. The receiver is uncertain about how to interpret the data, but aware of the sender’s incentives to strategically provide interpretations (“narratives”) in her favor. We consider a general class of decision rules under ambiguity resolving the receiver’s ignorance of the true data generating process, including maximum likelihood expected utility. The set of equilibria is characterized by a positive integer N: there is an equilibrium that induces n different actions for each 1≤n ≤N. The diverting power of the sender is weaker than with a naïve receiver being unaware of the sender’s incentives. Surprisingly, the receiver sometimes prefers to be naïve.

2. 

   Acts, correlation uncertainty and aggregation

   Gerrit Bauch, and Lorenz Hartmann

   2024

   Work in progress

3. 

   From words of approach to words of departure: Essays on noisy communication and partnership dissolution under uncertainty

   Gerrit Bauch

   Bielefeld University library, 2024

   Doctoral Thesis

   HTML

4. 

   The Texas Shoot-Out under Knightian uncertainty

   Gerrit Bauch, and Frank Riedel

   Games and Economic Behavior, 2024

   Abs HTML

   We investigate a widely used mechanism to resolve disputes among business partners, known as Texas Shoot-Out, under Knightian uncertainty. For a non-degenerate range of intermediate valuations, an ambiguity-averse divider truthfully reveals their valuation in equilibrium. As a consequence, the resulting outcome is efficient, in contrast to the Bayesian case. With equal shares, both agents prefer ex-ante to be the chooser and would like to avoid triggering the mechanism in the first place.

2023

1. 

   Underreaction and dynamic inconsistency in communication games under noise

   Gerrit Bauch

   arXiv preprint arXiv:2311.12496, 2023

   Abs arXiv

   Communication is rarely perfect, but rather prone to error of transmission and reception. Often the origin of these errors cannot be properly quantified and is thus imprecisely known. We analyze the impact of an ambiguous noise which may alter the received message on a communication game of common interest. The noise is ambiguous in the sense that the parameters of the error-generating process and thus the likelihood to receive a message by mistake are Knightianly unknown. Ex-ante and interim responses are characterized under maxmin preferences. While the sender can disregard ambiguity, the receiver reveals a dynamically inconsistent, but astonishing behavior under a quadratic loss. Their interim actions will be closer to the pooling action than their ex-ante ones, as if facing a higher likelihood of an occurring error.

2021

1. 

   Effects of Noise on the Grammar of Languages

   Gerrit Bauch

   2021

   R&R (minor revision) in the International Journal of Game Theory

   Abs HTML

   We study a signaling game of common interest in which a stochastic noise is perturbing the communication between an informed sender and an uninformed receiver. Despite this inhibiting factor,efficient languages exist. In equilibrium, sender uses a tessellation consisting of convex cells while receiver converts posterior beliefs into Bayesian estimators serving as interpretations. Shannon entropy measures the noise level and describes to which extent communication is possible. A limit case of errors that respect the distance between words leads to concise interpretations in the decoding process. Comparative statics for different levels of noise reveal which grammatical structures are more robust towards noise. For increasing error separation between most distinct types becomes more important than precision about each single one. Furthermore, distinct words are saved for the description of opposite domains of the type space. Evolutionary modeling approaches converge to equilibria, but not every equilibrium is stable.