An eye-tracking study of feature-based choice in one-shot games
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Previous experimental research suggests that individuals apply rules of thumb to a simplified mental model of the “real” decision problem. We claim that this simplification is obtained either by neglecting the other players’ incentives and beliefs or by taking them into consideration only for a subset of game outcomes. We analyze subjects’ eye movements while playing a series of two-person, 3 × 3 one-shot games in normal form. Games within each class differ by a set of descriptive features (i.e., features that can be changed without altering the game equilibrium properties). Data show that subjects on average perform partial or non-strategic analysis of the payoff matrix, often ignoring the opponent´s payoffs and rarely performing the necessary steps to detect dominance. Our analysis of eye-movements supports the hypothesis that subjects use simple decision rules such as “choose the strategy with the highest average payoff” or “choose the strategy leading to an attractive and symmetric outcome” without (optimally) incorporating knowledge on the opponent’s behavior. Lookup patterns resulted being feature and game invariant, heterogeneous across subjects, but stable within subjects. Using a cluster analysis, we find correlations between eye-movements and choices; however, applying the Cognitive Hierarchy model to our data, we show that only some of the subjects present both information search patterns and choices compatible with a specific cognitive level. We also find a series of correlations between strategic behavior and individual characteristics like risk attitude, short-term memory capacity, and mathematical and logical abilities.
KeywordsOne-shot games Eye-tracking Focal points Individual behavior Bounded rationality Feature-based choice
JEL ClassificationC72 C91 D01 D83
Financial supports from the “Italian Ministry of Education, University and Research” (MIUR, project PRIN 2008), from the “Fonds de la Recherche Fondamentale Collective” (research grant “Preference dynamics in adaptive networks”, n° 2.4614.12) and from the “Fondazione Cassa di Risparmio di Perugia” (grant “Ricerca di Base 2010”) are gratefully acknowledged. We thank participants in the ESA 2011 North American meeting, the 6th Nordic Conference on Behavioral and Experimental Economics at Lund University, the Workshop on Rationality, Heuristics and Motivation in Decision Making at Scuola Normale Superiore in Pisa, and seminar participants at the University of Strasbourg and Luiss Guido Carli in Rome for useful comments and suggestions. The usual disclaimer applies.
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