arXiv subjects

Gerrit Bauch

Publications and source records attributed to Gerrit Bauch.

7 recordsLinked to original sources

arXiv2026

Strategic communication of narratives: An experiment

We investigate the strategic communication of narratives 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''). We theoretically show that the size of the conflict of interest between the sender and the receiver is a crucial determinant of equilibrium communication. In particular, the stronger the sender's bias, (i) the more senders exaggerate their information and (ii) the more receivers correct the sender's action recommendations. In a laboratory experiment, we find evidence in line with both predictions, suggesting that people in complex and uncertain environments take a narrator's strategic incentives into account. Additional analyses reveal that narrative likelihood does not drive receiver behavior and that narratives are, on average, slightly persuasive only when bias is low.

econ.TH↗

arXiv2026

Extreme points of sets of probability measures and $\varphi$-divergences

In this work, we prove several equivalent characterizations of the extreme points of convex sets of probability measures of the form $\mathcal{M}=\mathcal{P} \cap H$, where $\mathcal{P}$ denotes the set of all probability measures on an arbitrary measurable space $(\Omega,\mathcal{F})$ and $H$ is an affine set of signed measures on $(\Omega,\mathcal{F})$ with finite variation. We first give a precise measure-theoretic formulation of the heuristic that extreme measures have minimal support. We then connect this with the notion of minimality with respect to absolute continuity, and prove that points that dominate no other element of $\mathcal{M}$ are the only ones realizing the blow-up of a certain divergence map for any suitable $\phi$-divergence. Finally, considering a different class of $\phi$-divergences, we recover a characterization of the extreme points of $\mathcal{M}$ as strict local maximizers of $\phi$-divergences relative to any suitable dominating measures. We apply our result to recover and complement results from the literature in the context of finite spaces, sets of measures defined by integral constraints, multi-marginal couplings, and dominated sets of probability measures.

math.PR↗

arXiv2025

Dependence uncertainty: a decision-theoretic approach

We propose and axiomatize preferences on a product state space in light of uncertainty regarding the dependency of different payoff-relevant factors. Dependence structures allow to decompose probabilities and allow to pin down behavior towards dependence. The degree of dependence aversion is measured by dependence premia that are compatible with the encompassed MEU and smooth preferences on the dependence uncertainty set. A separation axiom clarifies when uncertainty about dependence breaks down and the decision maker treats factors as independent, making dependence neglect testable. We describe the dependence uncertainty set as a convex polytope and characterize their extreme points as maximizers of divergences. The model and its tools are applied to simple examples on climate change, insurance, and portfolio choice.

econ.TH↗

arXiv2024

Expected Utility Without Assuming Continuity

I provide an axiomatization of expected utility in which topological continuity is replaced by a geometric axiom. The axiom requires a finite set of indifferent lotteries that span a hyperplane. In the case of three prizes, two indifferent lotteries suffice. The axiom is weaker than Solvability, as well as logically independent of Weak Continuity and the Archimedean axiom.

econ.TH↗

arXiv2024

Strategic communication of narratives

We model 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"). We introduce a general class of ambiguity rules resolving the receiver's ignorance of the true data generating process, including maximum likelihood and max-min expected utility. The set of equilibria is characterized by a positive integer $N$: we derive an algorithm which yields an equilibrium that induces $n$ different actions for each $1\leq n \leq N$. We further show that the persuasive power of the sender is weaker in the sense of state-wise dominance than with a na\"ive receiver being unaware of the sender's incentives.

econ.TH↗

arXiv2023

Underreaction and dynamic inconsistency in communication games under noise

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.

econ.TH↗

arXiv2022

The Texas Shootout under Uncertainty

We investigate the allocation of a co-owned company to a single owner using the Texas Shoot-Out mechanism with private valuations. We identify Knightian Uncertainty about the peer's distribution as a reason for its deterrent effect of a premature dissolving. Modeling uncertainty by a distribution band around a reference distribution $F$, we derive the optimal price announcement for an ambiguity averse divider. The divider hedges against uncertainty for valuations close to the median of $F$, while extracting expected surplus for high and low valuations. The outcome of the mechanism is efficient for valuations around the median. A risk neutral co-owner prefers to be the chooser, even strictly so for any valuation under low levels of uncertainty and for extreme valuations under high levels of uncertainty. If valuations are believed to be close, less uncertainty is required for the mechanism to always be efficient and reduce premature dissolvements.

econ.TH↗