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Identifying News Shocks with Forecast Data


  • Yasuo Hirose
  • Takushi Kurozumi


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.

Suggested Citation

  • Yasuo Hirose & Takushi Kurozumi, 2012. "Identifying News Shocks with Forecast Data," CAMA Working Papers 2012-01, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2012-01

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    References listed on IDEAS

    1. Guglielmo Barone & Gaia Narciso, 2013. "The effect of organized crime on public funds," Temi di discussione (Economic working papers) 916, Bank of Italy, Economic Research and International Relations Area.
    2. Jose M. Berrospide & Rochelle M. Edge, 2010. "The effects of bank capital on lending: What do we know, and what does it mean?," CAMA Working Papers 2010-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Wouter J. Den Haan & Vincent Sterk, 2011. "The Myth of Financial Innovation and the Great Moderation," Economic Journal, Royal Economic Society, vol. 121(553), pages 707-739, June.
    4. Adrian, Tobias & Shin, Hyun Song, 2010. "Liquidity and leverage," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 418-437, July.
    5. Jose M. Berrospide & Rochelle M. Edge, 2010. "The Effects of Bank Capital on Lending: What Do We Know, and What Does It Mean?," International Journal of Central Banking, International Journal of Central Banking, vol. 6(34), pages 1-50, December.
    6. Jose M. Berrospide & Rochelle M. Edge, 2010. "The effects of bank capital on lending: what do we know, and what does it mean?," Finance and Economics Discussion Series 2010-44, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Sohei Kaihatsu & Takushi Kurozumi, 2014. "Sources of Business Fluctuations: Financial or Technology Shocks?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(2), pages 224-242, April.
    2. MATSUMAE Tatsuyoshi & HASUMI Ryo, 2016. "Impacts of Government Spending on Unemployment: Evidence from a Medium-scale DSGE Model(in Japanese)," ESRI Discussion paper series 329, Economic and Social Research Institute (ESRI).
    3. Milani, Fabio, 2017. "Sentiment and the U.S. business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 289-311.
    4. Jinill Kim & Seth Pruitt, 2017. "Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 585-602, June.
    5. Thuy Lan Nguyen & Wataru Miyamoto, 2014. "News shocks and Business cycles: Evidence from forecast data," 2014 Meeting Papers 259, Society for Economic Dynamics.
    6. Fabio Milani & Ashish Rajrhandari, 2012. "Observed Expectations, News Shocks, and the Business Cycle," Working Papers 121305, University of California-Irvine, Department of Economics.

    More about this item

    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles


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