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News, Non-Invertibility, and Structural VARs

Author

Listed:
  • Eric R. Sims

    () (Department of Economics, University of Notre Dame)

Abstract

A state space representation of a linearized DSGE model implies a VAR in terms of observable variables. The model is said be non-invertible if there exists no linear rotation of the VAR innovations which can recover the economic shocks. Non-invertibility arises when the observed variables fail to perfectly reveal the state variables of the model. The imperfect observation of the state drives a wedge between the VAR innovations and the deep shocks, potentially invalidating conclusions drawn from structural impulse response analysis in the VAR. The principal contribution of this paper is to show that non-invertibility should not be thought of as an ``either/or'' proposition even when a model has a non-invertibility, the wedge between VAR innovations and economic shocks may be small, and structural VARs may nonetheless perform reliably. As an increasingly popular example, so-called ``news shocks'' generate foresight about changes in future fundamentals such as productivity, taxes, or government spending and lead to an unassailable missing state variable problem and hence non-invertible VAR representatations. Simulation evidence from a medium scale DSGE model augmented with news shocks about future productivity reveals that structural VAR methods often perform well in practice, in spite of a known non-invertibility. Impulse responses obtained from VARs closely correspond to the theoretical responses from the model, and the estimated VAR responses are successful in discriminating between alternative, nested specifications of the underlying DSGE model. Since the non-invertibility problem is, at its core, one of missing information, conditioning on more information, for example through factor augmented VARs, is shown to either ameliorate oreliminate invertibility problems altogether.

Suggested Citation

  • Eric R. Sims, 2012. "News, Non-Invertibility, and Structural VARs," Working Papers 013, University of Notre Dame, Department of Economics, revised Jun 2012.
  • Handle: RePEc:nod:wpaper:013
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    File URL: http://www3.nd.edu/~tjohns20/RePEc/deendus/wpaper/013_vars.pdf
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    Citations

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    Cited by:

    1. Massimo Franchi & Paolo Paruolo, 2015. "Minimality of State Space Solutions of DSGE Models and Existence Conditions for Their VAR Representation," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 613-626, December.
    2. Soccorsi, Stefano, 2016. "Measuring nonfundamentalness for structural VARs," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 86-101.
    3. Saleem Bahaj, 2014. "Systemic Sovereign Risk: Macroeconomic Implications in the Euro Area," Discussion Papers 1406, Centre for Macroeconomics (CFM).
    4. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel vector autoregressive models: a survey," Working Paper Series 1507, European Central Bank.
    5. Eric R. Sims, 2016. "Differences in Quarterly Utilization-Adjusted TFP by Vintage, with an Application to News Shocks," NBER Working Papers 22154, National Bureau of Economic Research, Inc.
    6. Born, Benjamin & Müller, Gernot J. & Pfeifer, Johannes, 2014. "Does austerity pay off?," SAFE Working Paper Series 77, Research Center SAFE - Sustainable Architecture for Finance in Europe, Goethe University Frankfurt.
    7. Mario Forni & Luca Gambetti & Luca Sala, 2016. "VAR Information and the Empirical Validation of DSGE Models," Center for Economic Research (RECent) 119, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    8. Hashmat Khan & Abeer Reza, 2017. "House Prices and Government Spending Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1247-1271, September.
    9. Ravi Balakrishnan & Stefan Laseen & Andrea Pescatori, 2016. "U.S. Dollar Dynamics; How Important Are Policy Divergence and FX Risk Premiums?," IMF Working Papers 16/125, International Monetary Fund.
    10. Robert B. Barsky & Susanto Basu & Keyoung Lee, 2015. "Whither News Shocks?," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 225-264.
      • Robert B. Barsky & Susanto Basu & Keyoung Lee, 2014. "Whither News Shocks?," NBER Chapters,in: NBER Macroeconomics Annual 2014, Volume 29, pages 225-264 National Bureau of Economic Research, Inc.
    11. Féve, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 919-932.
    12. Andrea Boitani & Salvatore Perdichizzi, 2018. "Public Expenditure Multipliers in recessions. Evidence from the Eurozone," DISCE - Working Papers del Dipartimento di Economia e Finanza def068, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    13. repec:eee:inecon:v:108:y:2017:i:c:p:368-376 is not listed on IDEAS
    14. repec:eee:dyncon:v:87:y:2018:i:c:p:94-105 is not listed on IDEAS
    15. Ben Zeev, Nadav, 2018. "What can we learn about news shocks from the late 1990s and early 2000s boom-bust period?," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 94-105.
    16. Massimo Franchi, 2013. "Comment on: Ravenna, F., 2007. Vector autoregressions and reduced form representations of DSGE models. Journal of Monetary Economics 54, 2048-2064," DSS Empirical Economics and Econometrics Working Papers Series 2013/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    17. Lutz Kilian, 2013. "Structural vector autoregressions," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 22, pages 515-554 Edward Elgar Publishing.

    More about this item

    Keywords

    DSGE; VAR; News shocks;

    JEL classification:

    • E - Macroeconomics and Monetary Economics
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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