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Narrative Sign Restrictions for SVARs

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  • Juan Antolín-Díaz
  • Juan F. Rubio-Ramírez

Abstract

We identify structural vector autoregressions using narrative sign restrictions. Narrative sign restrictions constrain the structural shocks and/or the historical decomposition around key historical events, ensuring that they agree with the established narrative account of these episodes. Using models of the oil market and monetary policy, we show that narrative sign restrictions tend to be highly informative. Even a single narrative sign restriction may dramatically sharpen and even change the inference of SVARs originally identified via traditional sign restrictions. Our approach combines the appeal of narrative methods with the popularized usage of traditional sign restrictions.

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  • Juan Antolín-Díaz & Juan F. Rubio-Ramírez, 2018. "Narrative Sign Restrictions for SVARs," American Economic Review, American Economic Association, vol. 108(10), pages 2802-2829, October.
    • Handle: RePEc:aea:aecrev:v:108:y:2018:i:10:p:2802-29
    Note: DOI: 10.1257/aer.20161852
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    1. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    2. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    3. Leeper, Eric M., 1997. "Narrative and VAR approaches to monetary policy: Common identification problems," Journal of Monetary Economics, Elsevier, vol. 40(3), pages 641-657, December.
    4. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 869-902.
    5. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
    6. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    7. David E. Lindsey & Athanasios Orphanides & Robert H. Rasche, 2013. "The Reform of October 1979: How It Happened and Why," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 487-542.
    8. Ramey, Valerie A. & Shapiro, Matthew D., 1998. "Costly capital reallocation and the effects of government spending," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 48(1), pages 145-194, June.
    9. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    10. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    11. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.
    12. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    13. Kuttner, Kenneth N., 2001. "Monetary policy surprises and interest rates: Evidence from the Fed funds futures market," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 523-544, June.
    14. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    15. Luciana Juvenal & Ivan Petrella, 2015. "Speculation in the Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 621-649, June.
    16. Refet S Gürkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    17. James D. Hamilton, 1985. "Historical Causes of Postwar Oil Shocks and Recessions," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 97-116.
    18. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    19. Robert B. Barsky & Lutz Kilian, 2002. "Do We Really Know That Oil Caused the Great Stagflation? A Monetary Alternative," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 137-198, National Bureau of Economic Research, Inc.
    20. Christiane Baumeister & Lutz Kilian, 2016. "Understanding the Decline in the Price of Oil since June 2014," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(1), pages 131-158.
    21. Christina D. Romer & David H. Romer, 1989. "Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 121-184, National Bureau of Economic Research, Inc.
    22. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    23. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    24. Dario Caldara & Edward Herbst, 2019. "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 157-192, January.
    25. Hoover, Kevin D. & Perez, Stephen J., 1994. "Post hoc ergo propter once more an evaluation of 'does monetary policy matter?' in the spirit of James Tobin," Journal of Monetary Economics, Elsevier, vol. 34(1), pages 47-74, August.
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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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • Q35 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Hydrocarbon Resources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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