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....

Agents have foresight when they receive information about a random process above and beyond the information contained in its current and past history. In this paper, we propose an information-theoretic measure of the quantity of foresight in an information structure, and show how to separate...

We develop a fast, tractable, and robust method for solving the transition path of dynamic rational inattention problems in linear-quadratic-Gaussian settings. As an application of our general framework, we develop an attention-driven theory of dynamic pricing in which the Phillips curve slope...

Expectations about different macroeconomic aspects correlate with each other. I perform a structural test in the framework of the noisy information model and show that individual forms their expectations on multiple macroeconomic variables jointly rather than independently, thus causing these...

This paper considers the implications of an important source of model misspecification for the design of monetary policy rules: the assumed manner of expectations formation. Following a considerable literature on learning, it is assumed that private agents seek to maximize their objectives...

Recent studies suggest that the type of strategic environment or expectation feedback may have a large impact on whether the market learns the rational fundamental price. We present an experiment where the fundamental price experiences large unexpected shocks. Markets with negative expectation...

We study zero interest-rate policy in response to a large negative demand shock when long-run expectations can fall over time. Because falling expectations make monetary policy less effective by raising real interest rates, the optimal forward guidance policy makes large front-loaded promises to...