This exercise offers an innovative learning mechanism to model economic agent's decision-making process using a deep reinforcement learning algorithm. In particular, this AI agent is born in an economic environment with no information on the underlying economic structure and its own preference....

We propose a heuristic switching model of an asset market where the agents' choice of heuristic is consistent with their individual risk aversion. They choose between a fundamentalist and a trend-following rule to form expectations about the price of a risky asset. Given their risk aversion,...

This paper experimentally studies the role of associative memory for belief formation. Realworld information signals are often embedded in memorable contexts. Thus, today’s news, and the contexts they are embedded in, may cue the selective retrieval of similar past news and hence contribute to...

The paper investigates social-learning when the information structure is not commonly known. Individuals repeatedly interact in social-learning settings with distinct information structures. In each round of interaction, they use their experience gained in past rounds to draw inferences from...

It is common to analyze the effects of alternative monetary policy commitments under the assumption of fully model-consistent expectations. This implicitly assumes unrealistic cognitive abilities on the part of economic decision makers. The relevant question, however, is not whether the...

We develop a model of firm learning in volatile markets with noisy signals and test its predictions using historical German data. Firms' forecasts improve with age. We exploit German Reunification as a natural experiment where firms in the East are treated with ignorance about the distribution...