We initially examine two different methods for learning about parameters in a Rational Expectations setting, and show that there are conflicting E-stability results. We show that this conflict also extends to Minimum State Variable (MSV) representations. One of these methods of learning lends...

Saddlepath learning occurs when agents know the form but not the coefficients of the sad?dlepath relationship defining rational expectations equilibrium. Under saddlepath learning, we obtain a completely general relationship between determinacy and e-stability, and generalise Min?imum State...

Forward looking agents with expectational errors provide a problem for monetary policy. We show that under such conditions a standard interest rate rule may not achieve determinacy. We suggest a modification to the standard policy rule that guarantees determinacy in this setting, which involves...

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 need to make forecasts of the conditional variance of a stock¡¯s return....

To isolate the impact of the assumption of model-consistent expectations, this paper proposes a baseline case in which households are individually rational, have full information and learn using forecast rules specified as in the minimum state variable representation of the economy. Applying...

In this paper, we consider a model where producers set their prices based on their prediction of the aggregated price level and an exogenous variable, which can be a demand or a cost-push shock. To form their expectations, they use OLS-type econometric learning with bounded memory. We show that...

Within the standard RBC model, we examine issues of expectational coordination on the unique rational expectations equilibrium. Our study first provides a comprehensive assessment of the sensitivity of agents’ ?plans and decisions to their short-run and long-run expectations. We show this...

I develop an equilibrium model with collateral constraints in which rational agents are uncertain and learn about the equilibrium mapping between fundamentals and collateral prices. Bayesian updating of beliefs by agents can endogenously generate booms and busts in collateral prices and largely...

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...

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the...