arXiv subjects

Florian Mudekereza

Publications and source records attributed to Florian Mudekereza.

7 recordsLinked to original sources

arXiv2026

Constraint Preferences: Inattention and Aggregation

We study robust decision problems when individuals have maxmin preferences whose belief sets are neighborhoods around reference models, commonly known as "constraint preferences." We first show that a more disciplined form of rationally inattentive behavior is equivalent to the behavior implied by a subclass of constraint preferences. We then introduce an aggregation principle that requires collective beliefs to satisfy every individual's constraint. This requirement links collective beliefs to the information-processing technologies that generate individual constraints. Applications reveal how these technologies determine asset prices, when prediction-market prices become self-confirming, and how much dynamic mechanisms can reduce information rents.

econ.TH↗

arXiv2026

Contracting under Misspecification

This paper studies agency problems when both parties worry that the model linking action to output is misspecified. With observable actions, an optimal contract is linear in output, so performance pay arises solely to share misspecification exposure, the slope reflects the parties' relative robustness concerns, and its allocation is Pareto efficient. With hidden actions, this sharing rule survives and incentives add a nonlinear correction. Misspecification concerns can polarize effort by making intermediate actions impossible to implement. Moreover, ambiguity across competing models has asymmetric effects: uncertainty about desired actions raises the principal's payoff, whereas uncertainty about deviations can lower it.

econ.TH↗

arXiv2026

Motivating Innovation with a Misspecified Roadmap

We analyze a principal-agent relationship where a principal communicates a roadmap to guide an agent who is learning the value of innovation. However, the agent is concerned that the roadmap is misspecified. We find that the agent can fall into a breakthrough trap, where early unexplained success triggers a loss of trust in the roadmap, such that no contract can motivate him to continue innovating. We also obtain an upper bound on the frequency of innovative activity that tightens as the degree of misspecification increases, which can cause ``exploration-exploitation'' cycles to emerge endogenously over time.

econ.TH↗

arXiv2026

Complexity and Misspecification

We propose a tractable model of repeated decision problems that combines concern about model misspecification, as in robust control, with a complexity cost, such as Shannon entropy, that makes pessimistic beliefs trade off statistical plausibility against simplicity. In a static setting, stronger complexity aversion selects more concentrated worst-case beliefs and tilts choice toward actions whose adverse scenarios are harder to summarize with a simple narrative. In a dynamic learning environment, complexity aversion can eliminate the endogenous cycles generated by misspecification concerns alone. We use the model to explain scale heterogeneity in discrete choice, probability neglect, and home bias.

econ.TH↗

arXiv2026

Aggregate Efficiency in Games

We show that, in large population games, decentralized information aggregation generically corrects for individual-level biases. This establishes a new testable aggregate efficiency benchmark where the behavior of boundedly rational agents mimics that of fully rational agents. However, we find that structural economic forces such as strategic network formation and profit-maximizing platforms can systematically select pathological environments to exploit individuals' biases, thereby causing aggregate inefficiencies. We characterize these inefficiencies in monopoly and labor markets. Our findings therefore suggest that policy should shift focus from correcting individuals' behavior to monitoring and regulating information structures.

econ.TH↗

arXiv2026

Robust Aggregation of Preferences

This paper analyzes a society composed of individuals who have diverse sets of beliefs (or models) and diverse tastes (or utility functions). It characterizes the model selection process of a social planner who wishes to aggregate individuals' beliefs and tastes but is concerned that their beliefs are misspecified (or incorrect). A novel impossibility result emerges under several desiderata: a utilitarian social planner who prioritizes robustness to misspecification never aggregates individuals' beliefs but instead behaves as a dictator by adopting one individual's belief as the social belief. This tension between robustness and aggregation exists because aggregation yields policy-contingent beliefs, which are very sensitive to policy outcomes. The impossibility can be resolved, but it would require assuming individuals have heterogeneous tastes and some common beliefs. Applications in treatment choice and dynamic macroeconomics are explored.

econ.TH↗

arXiv2025

Collective Intelligence in Dynamic Networks

We revisit DeGroot learning to examine the robustness of social learning in dynamic networks -- networks that evolve randomly over time. Dynamics have double-edged effects depending on social structure: while they can foster consensus and boost collective intelligence in "sparse" networks, they can have adverse effects such as slowing down the speed of learning and causing long-run disagreement in "well-connected" networks. Collective intelligence arises in dynamic networks when average influence and trust remain balanced as society grows. We also find that the initial social structure of a dynamic network plays a central role in shaping long-run beliefs. We then propose a robust measure of homophily based on the likelihood of the worst network fragmentation.

econ.TH↗