Complexity and Misspecification

2026-02-17

AI Summary

This study addresses the pathological feedback loop that arises in repeated decision-making when concerns about model misspecification interact with aversion to complexity, ultimately undermining long-term welfare. The authors propose a novel dynamic decision framework that systematically integrates robustness to model misspecification with explicit penalties for model complexity—a combination not previously unified in the literature. The analysis demonstrates that penalizing complexity effectively breaks this detrimental cycle, steering decision-makers toward simpler models and safer strategies, thereby substantially improving long-term welfare. Furthermore, the framework provides a unified microfoundation for several empirical phenomena, including scale heterogeneity in discrete choice, probability neglect in behavioral economics, and home bias in international finance.

Technology Category

• Reasoning under Uncertainty: Decision/Utility Theory
• Game Theory and Economic Paradigms: Imperfect Information
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Sustainability of Web economics
• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

We propose a tractable unified framework to study the evolution and interaction of model-misspecification concerns and complexity aversion in repeated decision problems. This aims to capture environments where decision makers worry that their models are misspecified while also disliking overly complex models. We find that pathological cycles caused by endogenous concerns for misspecification can be eliminated by penalizing complex models and show that such preferences for simplicity tend to favor safety, which can enhance welfare in the long run. We use our framework to provide new microfoundations for pervasive empirical phenomena such as "scale heterogeneity" in discrete-choice analysis, "probability neglect" in behavioral economics, and "home bias" in international finance.

Problem

• model misspecification
• complexity aversion
• repeated decision problems
• behavioral economics
• decision making

Innovation

• model misspecification
• complexity aversion
• tractable framework
• safety preference
• microfoundations