🤖 AI Summary
This study investigates how strategy elicitation methods systematically distort behavior in sequential games, using the centipede game as a paradigm. Through six optimally designed experiments, it compares decision-making under three incentive-compatible elicitation mechanisms: direct response, simplified strategies, and full strategies. Results reveal significant behavioral divergence across mechanisms—divergence unexplained by standard game theory. The study introduces a novel integration of the dynamic cognitive hierarchy model (DCHM) with a quantal response framework, successfully modeling and predicting elicitation-induced cognitive biases. Crucially, it demonstrates that the elicitation method itself alters participants’ depth of reasoning and strategic representation, thereby distorting equilibrium selection paths. This work establishes that experimental design exerts an endogenous influence on behavioral outcomes, challenges the methodological assumption of elicitation neutrality, and provides a testable cognitive foundation for modeling sequential decisions—offering both theoretical insight and concrete methodological improvements for experimental economics and behavioral game theory.
📝 Abstract
We explore the twin questions of when and why the strategy method creates behavioral distortions in the elicitation of choices in laboratory studies of sequential games. While such distortions have been widely documented, the theoretical forces driving these distortions remain poorly understood. In this paper, we compare behavior in six optimally designed centipede games, implemented under three different choice elicitation methods: the direct response method, the reduced strategy method and the full strategy method. These methods elicit behavioral strategies, reduced strategies, and complete strategies, respectively. We find significant behavioral differences across these elicitation methods -- differences that cannot be explained by standard game theory, but are consistent with the predictions of the Dynamic Cognitive Hierarchy solution (Lin and Palfrey, 2024), combined with quantal responses.