ambiguous lotteries. In the second experiment the sample averages do not converge.If we define fictive learning in an experiment …, then we expect fictive learning in the first experiment, but no fictive learning in the second experiment. The surprising … finding in this paper is the presence of fictive learning in the second experiment. We attribute this counterintuitive result …

This paper examines social learning when only one of the two types of decisions is observable. Because agents arrive …, as in the standard model, learning is complete if and only if signals are unbounded. If signals are bounded, cascades may …

Learning or experience curves are widely used to estimate cost functions in manufacturing modeling. They have recently … shows that there is a fundamental statistical identification problem in trying to separate learning from exogenous … technological change and that the estimated learning coefficient will generally be biased upwards. Second, we present two empirical …

, then this contraction mapping property fails. We show by example that common learning can fail in this case …

' performances in order to bias the learning process in her favor. To manipulate the market's assessments, we argue that in …

correlation across players. For each information structure, we define a simple learning efficiency index, which only considers the … this index characterizes the speed of common learning (Cripps, Ely, Mailath, and Samuelson, 2008): In particular, the speed … individual learning, and does not depend on the correlation across players’ signals. Second, we build on this characterization to …