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....

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...

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...

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 shows that price rigidity evolves in an economy populated by imperfectly rational agents who experiment with alternative rules of thumb. In the model, firms must set their prices in face of aggregate demand shocks. Their payoff depends on the level of aggregate demand, as well as on...

This paper estimates a New Keynesian model with new and old behavioral elements. Agents in the model exhibit cognitive discounting, or myopia: they discount variables far into the future at higher rates than typically implied in the benchmark model. We investigate the model under different...

We study the effects of overconfidence in a two-period investment-decision agency setting. Under common priors, agent risk aversion implies inefficiently low first-period investment. In our model, principal and agent disagree about the profitability of the investment decision conditional on a...

Agents forming adaptive expectations generally make systematic mistakes. This characterization has fostered the rejection of adaptive expectations in macroeconomics. Experimental evidence, however, shows that in complex environments human subjects frequently rely on adaptive heuristics –...

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 formation of expectations at the micro-level, by...