Expectations Formation and Forward Information
We propose a model where forecasters have access to noisy signals about the future (forward information). In this setting, information varies not only across agents but also across horizons. As a result, estimated persistence of forecasts deviates from persistence of fundamentals and the ability of forecasts at shorter horizons to explain forecasts at longer horizons is limited. These properties tend to diminish as the forecast horizon increases. We document that this novel pattern is consistent with survey data for professional forecasters. We provide further evidence that time-series and cross-sectional variation in professional forecasts is driven by forward information. We propose a simple method for extracting the forward information component from survey and provide several applications of forward information.
We thank Ryan Chahrour, Filip Matĕjka, Dmitriy Sergeyev, Eric Sims, and seminar participants at UC Davis, Tel-Aviv University, Ben-Gurion University, University of Haifa, Reichman University, Bar-Ilan University, Bank of Israel for comments. We thank Eric Sims for sharing code for the Barsky-Sims approach. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.