Identifying News Shocks with Forecast Data

Yasuo Hirose and Takushi Kurozumi

No 366, Globalization Institute Working Papers from Federal Reserve Bank of Dallas

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 (search for similar items in EconPapers)
JEL-codes: E30 E32 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2019-05-01
New Economics Papers: this item is included in nep-dge, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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https://www.dallasfed.org/-/media/documents/institute/wpapers/2019/0366a.pdf Appendix (application/pdf)

Related works:
Journal Article: IDENTIFYING NEWS SHOCKS WITH FORECAST DATA (2021)
Working Paper: Identifying News Shocks with Forecast Data (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:feddgw:366

DOI: 10.24149/gwp366

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