Identifying News Shocks with Forecast Data

Hirose, Yasuo; Kurozumi, Takushi

doi:10.24149/gwp366

Working Paper

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 U.S. 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.

Keywords: business cycle fluctuations; Technology Shock; Technology News Shock; Forecast Data; Bayesian Estimation;

JEL Classification: E30; E32;

https://doi.org/10.24149/gwp366