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Comparing two methods for the identification of news shocks

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  • Beaudry, Paul
  • Portier, Franck
  • Seymen, Atılım

Abstract

Recent empirical literature delivered, based on different structural VAR approaches, controversial results concerning the role of anticipated technology-news-shocks in business cycle fluctuations. We deal with this controversy and investigate (i) the extent to thich two prominent structural VAR approaches can be usefull in recuperating news shock dynamics from artificially generated data in general and (ii) why and to what extent these SVAR approaches differ in the results the deliver in particular. Thereby, we provide several insights for the users of both VAR techniques with small samples in practice.

Suggested Citation

  • Beaudry, Paul & Portier, Franck & Seymen, Atılım, 2013. "Comparing two methods for the identification of news shocks," ZEW Discussion Papers 13-110, ZEW - Leibniz Centre for European Economic Research.
  • Handle: RePEc:zbw:zewdip:13110
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    References listed on IDEAS

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    1. Eric R. Sims, 2012. "News, Non-Invertibility, and Structural VARs," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 81-135, Emerald Group Publishing Limited.
    2. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106, National Bureau of Economic Research, Inc.
    3. Beaudry, Paul & Portier, Franck, 2004. "An exploration into Pigou's theory of cycles," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1183-1216, September.
    4. 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.
    5. 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.
    6. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    7. Faust, Jon & Leeper, Eric M, 1997. "When Do Long-Run Identifying Restrictions Give Reliable Results?," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 345-353, July.
    8. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    9. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
    10. 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.
    11. Greenwood, Jeremy & Hercowitz, Zvi & Huffman, Gregory W, 1988. "Investment, Capacity Utilization, and the Real Business Cycle," American Economic Review, American Economic Association, vol. 78(3), pages 402-417, June.
    12. Paul Beaudry & Deokwoo Nam & Jian Wang, 2011. "Do Mood Swings Drive Business Cycles and is it Rational?," NBER Working Papers 17651, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Portier, Franck & Beaudry, Paul & Feve, Patrick & Guay, Alain, 2015. "When is Nonfundamentalness in VARs A Real Problem? An Application to News Shocks," CEPR Discussion Papers 10763, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    News Shocks; Structural VAR; 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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