Discussion Paper, Center for Mathematical Studies in Economics and Management Science 1516
We analyze social learning and innovation in an overlapping generations model in which available technologies have correlated payoffs. Each generation experiments within a set of policies whose payoffs are initially unknown and drawn from the path of a Brownian motion with drift. Marginal innovation consists in choosing a technology within the convex hull of policies already explored and entails no direct cost. Radical innovation consists in experimenting beyond the frontier of that interval, and entails a cost that increases with the distance from the frontier, and may decrease with the best technology currently available. We study how successive generations alternate between radical and marginal innovation, in a pattern reminiscent of Schumpeterian cycles. Even when the underlying Brownian motion has a positive drift, radical innovation stops in finite time. New generations then fine-tune policies in search of a local optimum, converging to a single technology. Our analysis thus suggests that sustaining radical innovation in the long-run requires external intervention.
innovation Schumpeter cycles experimentation social learning R&D intergenerational externalities