Seminari Theory-Experimental

Ludmila Matyskova

Universidad de Alicante


Sala Vicens Vives – 14:30


We study a model in which a payoff-relevant state comprises of multiple, unknown attributes. The principal delegates learning about the attributes to a biased agent, who chooses how to allocate a budget of informative tests across attributes. We derive the optimal learning strategy in this setting. Depending on the bias, the agent may learn about different attributes or choose different intensities than the principal’s optimum. Notably, the agent may abstain from learning altogether. We study how the agent’s optimal learning strategy and the principal’s payoff change with the agent’s absolute and relative bias and show that the principal may prefer more biased agents. Furthermore, we analyze the principal’s preferred organizational setup regarding delegation of learning and/or decision rights. Finally, we provide an application to an insurance setting.

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