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 develops an adaptive learning formulation of an extension to the Ball, Mankiw and Reis (2005) sticky information model that incorporates endogenous inattention. We show that, following an exogenous increase in the policymaker's preferences for price vs. output stability, the learning...

A striking implication of the replacement of adaptive expectations by Rational Expectations was the "Lucas Critique," which showed that expectation parameters, and endogenous variable dynamics, depend on policy parameters. We consider this issue from the vantage point of a bounded rationality,...

This paper studies how children learn to bargain. We performed simple anonymous bargaining experiments with real payoffs with 256 children from age 8 to 18. On average, offers by even the youngest children were close to optimal, given the responses. Both offers and responses were similar to the...

The most distinctive prediction of prospect theory is the fourfold pattern (FFP) of risk attitudes. People are said to be (1) risk-seeking over low-probability gains, (2) risk-averse over low-probability losses, (3) risk-averse over high-probability gains, and (4) risk-seeking over...

This paper studies the implications for monetary policy of heterogeneous expectations in a New Keynesian model. The assumption of rational expec- tations is replaced with parsimonious forecasting models where agents select between predictors that are underparameterized. In a Misspecification...

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...

We compare the performance of alternative recursive forecasting models. A simple constant gain algorithm, used widely in the learning literature, both forecasts well out of sample and also provides the best fit to the Survey of Professional Forecasters.

We consider the stability under adaptive learning of the complete set of solutions to the model x_i=beta(Ei*)(x_i+1) when |beat| 1. In addition to the fundamentals solution, the literature describes both finite-state Markov sunspot solutions and autoregressive solutions depending on an arbitrary...

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...