IDENTIFYING NEWS SHOCKS with FORECAST DATA

Yasuo Hirose, Takushi Kurozumi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
JournalMacroeconomic Dynamics
DOIs
Publication statusAccepted/In press - 2019 Jan 1

Keywords

  • Bayesian Estimation
  • Business Cycle Fluctuation
  • Forecast Data
  • Technology News Shock
  • Technology Shock

ASJC Scopus subject areas

  • Economics and Econometrics

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