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 …

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

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 …

with a large (but finite) number of heterogeneous agents using deep learning. The „curse of dimensionality“ is avoided due … the most generalizable over-parameterized deep learning approximation without calculating the stationary distribution or …

We study the effects of two dimensions of teacher quality, subject knowledge and didactic skills, on student learning …

learning as a two-armed bandit problem and highlight the interaction between learning (experimentation) and production. We …