Learning Faster or More Precisely? Strategic Experimentation in Networks

The paper analyzes a dynamic model of rational strategic learning in a network. It complements existing literature by providing a detailed picture of short-run dynamics in a game of strategic experimentation where agents are located in a social network. The delay in information transmission caused by incomplete network structures induces players to increase own experimentation efforts. As a consequence a complete network can fail to be optimal even if there are no costs for links. This means that in the design of networks there exists a trade-off between the speed of learning and accuracy. For an incomplete network to generate strictly higher payoffs than the complete network a combination of delay and specialization, where only some agents exert effort, is necessary. Further, splitting a network is only strictly optimal in case of specialization