摘要：This paper examines the role of education in technology adoption in a multi-agent finite-time dynamic game setting. It is assumed that education decreases prior variance on the best action in using a new technology in the target-input Bayesian model, experience accumulates in a community (social learning information spillover), and the experience, however, is not transferrable from one technology to another. The paper shows that, depending on the schooling distribution, the equilibrium s different dynamic patterns of technology adoption.
