Identifying News Shocks with Forecast Data

Recent studies attempt to quantify the empirical importance of news shocks (i.e., anticipated future shocks) in business cycle fluctuations. This paper identifies news shocks in a dynamic stochastic general equilibrium model estimate with not only actual data but also forecast data. The estimation results show new empirical evidence that anticipated future technology shocks are the most important driving force of U.S. business cycles. The use of the forecast data makes the anticipated shocks play a much more important role in fitting model-implied expectations to this data, since such shocks have persistent effects on the expectations and thereby help to replicate the observed persistence of the forecasts.