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A note on the Cogley–Nason–Sims approach

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  • Hussain, Syed M.
  • Liu, Lin

Abstract

In evaluating an economic model with Structural Vector Auto-Regression (SVAR), the Cogley–Nason–Sims (CNS) approach compares impulse responses estimated from empirical data with those obtained from the identical SVAR run on model generated data. Using Monte-Carlo simulations, this paper examines small sample performance of the CNS approach.

Suggested Citation

  • Hussain, Syed M. & Liu, Lin, 2016. "A note on the Cogley–Nason–Sims approach," Economics Letters, Elsevier, vol. 146(C), pages 77-81.
    • Handle: RePEc:eee:ecolet:v:146:y:2016:i:c:p:77-81
    DOI: 10.1016/j.econlet.2016.06.036
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    References listed on IDEAS

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    1. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
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    3. Christopher A. Sims, 1989. "Models and Their Uses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 489-494.
    4. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick & Wickens, Michael, 2011. "How much nominal rigidity is there in the US economy? Testing a new Keynesian DSGE model using indirect inference," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2078-2104.
    5. 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.
    6. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
    7. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    8. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    9. Carlstrom, Charles T. & Fuerst, Timothy S. & Paustian, Matthias, 2009. "Monetary policy shocks, Choleski identification, and DNK models," Journal of Monetary Economics, Elsevier, vol. 56(7), pages 1014-1021, October.
    10. Efrem Castelnuovo & Paolo Surico, 2010. "Monetary Policy, Inflation Expectations and The Price Puzzle," Economic Journal, Royal Economic Society, vol. 120(549), pages 1262-1283, December.
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    Cited by:

    1. Giuliano Curatola & Michael Donadelli & Patrick Gruning & Christoph Meinerding, 2016. "Investment-Specific Shocks, Business Cycles, and Asset Prices," Bank of Lithuania Working Paper Series 36, Bank of Lithuania.

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    More about this item

    Keywords

    Cogley–Nason–Sims approach; Small sample properties; Structural Vector Auto-Regression; Identification; Monte-Carlo simulation;
    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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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