Social Learning and the Adoption of Innovations

This chapter studies the evolution of technological innovations when agents face " fundamental" learning limits: these limits derive from the idea that certain features of the environment in which innovations are evaluated may not be statistically identified, forcing agents to make decisions in the face of ambiguity. It further assumes that agents are rational decision makers, but places the agents in a context in which alternative perspectives on the environment are observationally equivalent. Manski shows that this environment can lead to complex innovation dynamics and can replicate the classical S-shaped pattern of innovation adoption.