We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

We introduce the concept of a Misspecification Equilibrium to dynamic macroeconomics. Agents choose between a list of misspecified econometric models and base their selection on relative forecast performance. A Misspecification Equilibrium is an equilibrium stochastic process in which agents...

This paper identifies two channels through which the economy can generate endogenous inflation and output volatility, an empirical regularity, by introducing model uncertainty into a Lucas-type monetary model. The equilibrium path of inflation depends on agents' expectations and a vector of...

In an asset-pricing model, risk-averse agents need to forecast the conditional variance of a stock's return. A near-rational restricted perceptions equilibrium exists in which agents believe prices follow a random walk with a conditional variance that is self-fulfilling. When agents estimate...

This paper addresses the output-price volatility puzzle by studying the interaction of optimal monetary policy and agents' beliefs. We assume that agents choose their information acquisition rate by minimizing a loss function that depends on expected forecast errors and information costs....

This paper identifies two channels through which the economy can generate endogenous inflation and output volatility, an empirical regularity, by introducing model uncertainty into a Lucas-type monetary model. The equilibrium path of inflation depends on agents' expectations and a vector of...

This paper addresses the output-price volatility puzzle by studying the interaction of optimal monetary policy and agents' beliefs. We assume that agents choose their information acquisition rate by minimizing a loss function that depends on expected forecast errors and information costs....

We study the properties of generalized stochastic gradient (GSG) learning in forwardlooking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they generate forecasts of the conditional variance of a stock's return. Recursive...