Abstract
Models of electoral agency address the levels of discipline and selection that voters can achieve in elections. The models are demanding in terms of individual belief formation and consistency of behavior. We investigate a baseline model of electoral agency in a controlled laboratory environment. This baseline model, although simple, forms the central plank of more complex electoral agency models. Our design seeks to limit the behavioral impact of social preferences. We find little support for the baseline model in our data. However, simple (non-rational) learning rules explain behavioral patterns well. Simulations indicate that non-rational learning drives behavior most forcefully towards equilibrium in situations that are favorable to Bayesian updating.
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