Identifying News Shocks With Forecast Data

Abstract

The empirical importance of news shocks—anticipated future shocks—in business cycle fluctuations has been explored by using only actual data when estimating models augmented with news shocks. This paper additionally exploits forecast data to identify news shocks in a canonical dynamic stochastic general equilibrium model. The estimated model shows new empirical evidence that technology news shocks are a major source of fluctuations in US output growth. Exploiting the forecast data not only generates more precise estimates of news shocks and other parameters in the model, but also increases the contribution of technology news shocks to the fluctuations.

Identifying News Shocks from Forecasts

“…And current fiscal policy is already somewhat stabilizing; when we consider a counterfactual with fixed government spending, real activity 2 Examples include Beaudry and Portier (2006), Barsky and Sims (2012), Schmitt-Grohé and Uribe (2012), Blanchard et al (2013), and Chahrour and Jurado (2022). The most closely related papers are those that utilize forecast data to identify news about technology: Hirose and Kurozumi (2021) include forecast data in a New Keynesian DSGE model to identify news shocks and estimate that technology news drives nearly half of output volatility; Cascaldi-Garcia (2022) uses forecast revisions of economic growth to instrument for technology news shocks, which drive 11% − 26% of output volatility depending on the horizon.…”