infinite-horizon learning, and subjective expectations with Euler-equation learning. Under rational expectations, the model … necessitates of large, possibly unrealistically so, degrees of myopia. The same result persists under infinite-horizon learning …, given that agents are still remarkably farsighted. But, under Euler-equation learning, the model can fit the data with only …

The adaptive learning approach has been fruitfully employed to model the formation of aggregate expectations at the … macroeconomic level, as an alternative to rational expectations. This paper uses adaptive learning to understand, instead, the … sentiment, defined as the degrees of excess optimism and pessimism that cannot be justified by the near-rational learning model …

study experimentally to what extent cross-game learning can reduce overbidding in SPAs, taking into account cognitive skills … losses from high bids are more salient than in SPAs. Experience in FPAs causes substantial cross-game learning for … bid shading by cognitively more able participants, resulting in lower profits in FPAs. Thus, cross-game learning has the …

private returns to education within the employer learning framework of Farber and Gibbons [1996] and Altonji and Pierret [2001 …

mediated by learning. Using administrative data from speed cameras that capture the full driving histories of more than a … and temporary salience effects. Instead, it supports a learning model in which agents update their priors on the expected … punishment in a 'coarse' manner. Additional results indicate that learning from law enforcement affects drivers' behavior more …

-social behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer …

foreign competitors. The industry can stochastically lower its cost via learning by doing. Whether the industry has …