We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...

We propose a general model of decision-rights allocation and choice, formulated in the context of a dynamic psychological game. Decision rights are valued not only according to the value of the outcomes, but also according to the procedure by which outcomes are achieved. We introduce freedom,...

This paper introduces a model of boundedly rational observational learning, which is rationally founded and applicable to general environments. Under Quasi-Bayesian updating each action is treated as if it were based only on the private information of its respective observed agent. We analyze...

This paper presents a non-Bayesian model of social learning in networks in an environment with a finite set of actions. We conduct a laboratory experiment in which participants play an urn-guessing game over several decision rounds while observing the previous choices of the network members to...

This paper establishes existence and uniqueness of Quantal Response Equilibrium (QRE) in a double auction. The concept of QRE has the intuitive property that a deviation from best response is less likely the higher the cost associated with the deviation itself. Thanks to such property, the QRE...

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...

This paper proposes a methodology to implement probabilistic belief elicitation in continuous-choice games. Representing subjective probabilistic beliefs about a continuous variable as a continuous subjective probability distribution, the methodology involves eliciting partial information about...

We study first- and second-order subjective expectations (beliefs) in strategic decision making. We propose a method to elicit probabilistically both first- and second-order beliefs and apply the method to a Hide-and-Seek experiment. We study the relationship between choice and beliefs in terms...