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News Shocks, Information Flows and SVARs

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  • Patrick Feve
  • Ahmat Jidoud

Abstract

This paper assesses SVARs as relevant tools at identifying the dynamic effects or news shocks, Because of the misalignment between the econometrician and private agents' information sets resulting from foresight the dynamic responses identified from SVARs using either long-run and short-run restrictions are biased. However the bias vanishes when news shocks account for the bulk of fluctuations in the economy. Furthermore under this condition. he two identified shocks have a correlation close to unity validating the sequential identification approach adopted by BEAUDRY and PORTIER (2006)

Suggested Citation

  • Patrick Feve & Ahmat Jidoud, 2014. "News Shocks, Information Flows and SVARs," Annals of Economics and Statistics, GENES, issue 113-114, pages 293-307.
    • Handle: RePEc:adr:anecst:y:2014:i:113-114:p:293-307
    DOI: 10.15609/annaeconstat2009.113-114.293
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    1. 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.
    2. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    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 & 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.
    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

    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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