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News Shocks, Information Flows and SVARs

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  • Fève, Patrick
  • Jidoud, Ahmat

Abstract

This paper assesses SVARs as relevant tools at identifying the aggregate effects of news shocks. When the econometrician and private agents’ information sets are not aligned, the dynamic responses identified from SVARs are biased. However, the bias vanishes when news shocks account for the bulk of fluctuations in the economy. A simple correlation diagnostic test shows that under this condition, news shocks identified through long–run and short–run restrictions have a correlation close to unity.

Suggested Citation

  • Fève, Patrick & Jidoud, Ahmat, 2012. "News Shocks, Information Flows and SVARs," TSE Working Papers 12-286, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:25751
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    References listed on IDEAS

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    1. Paul Beaudry & Bernd Lucke, 2010. "Letting Different Views about Business Cycles Compete," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 413-455, National Bureau of Economic Research, Inc.
    2. Beaudry, Paul & Portier, Franck, 2005. "The "news view" of economic fluctuations: Evidence from aggregate Japanese data and sectoral US data," Journal of the Japanese and International Economies, Elsevier, vol. 19(4), pages 635-652, December.
    3. Fève, Patrick & Matheron, Julien & Sahuc, Jean-Guillaume, 2009. "On the dynamic implications of news shocks," Economics Letters, Elsevier, vol. 102(2), pages 96-98, February.
    4. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    5. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2011. "Foresight and Information Flows," NBER Working Papers 16951, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.

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    More about this item

    Keywords

    Information Flows; News shocks; Non–fundamentalness; SVARs; Identification;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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