We estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low...

Given the unobserved nature of expectations, this paper employs latent variable analysis to examine three financial instability models and assess their out-of-sample forecasting accuracy. We compare a benchmark linear random walk model, which implies exogenous instability phenomena, with a...

This paper tests the ability of popular New Keynesian models, which are traditionally used to study monetary policy and business cycles, to match the data regarding a key channel for monetary transmission: the dynamic interactions between macroeconomic variables and their corresponding...

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...

This paper provides a general strategy for analyzing monetary policy in real time which accounts for data uncertainty without explicitly modelling the revision process. The strategy makes use of all the data available from a real-time data matrix and averages model estimates across all data...

We construct a slope factor from changes in federal funds futures of different horizons. Slope predicts stock returns at the weekly frequency: faster monetary policy easing positively predicts excess returns. Investors can achieve increases in weekly Sharpe ratios of 20% conditioning on the...