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Underidentified SVAR models: A framework for combining short and long-run restrictions with sign-restrictions

  • Andrew Binning

    ()

    (Norges Bank (Central Bank of Norway))

I describe a new method for imposing zero restrictions (both short and long-run) in combination with conventional sign-restrictions. In particular I extend the Rubio-Ramirez et al.(2010) algorithm for applying short and long-run restrictions for exactly identified models to models that are underidentified. In turn this can be thought of as a unifying framework for short-run, long-run and sign restrictions. I demonstrate my algorithm with two examples. In the first example I estimate a VAR model using the Smets & Wouters (2007) dataset and impose sign and zero restrictions based on the impulse responses from their DSGE model. In the second example I estimate a BVAR model using the Mountford & Uhlig (2009) data set and impose the same sign and zero restrictions they use to identify an anticipated government revenue shock.

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File URL: http://www.norges-bank.no/en/Published/Papers/Working-Papers/2013/WP-201314/
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Paper provided by Norges Bank in its series Working Paper with number 2013/14.

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Length: 28 pages
Date of creation: 10 Jun 2013
Date of revision:
Handle: RePEc:bno:worpap:2013_14
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  1. 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.
  2. Andrew Mountford & Harald Uhlig, 2009. "What are the effects of fiscal policy shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 960-992.
  3. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
  4. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2005. "Alternative procedures for estimating vector autoregressions identified with long-run restrictions," International Finance Discussion Papers 842, Board of Governors of the Federal Reserve System (U.S.).
  5. Renee Fry & Adrian Pagan, 2010. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," NCER Working Paper Series 57, National Centre for Econometric Research.
  6. Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 0722, European Central Bank.
  7. Liu, Philip & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2011. "International transmission of shocks: a time-varying factor-augmented VAR approach to the open economy," Bank of England working papers 425, Bank of England.
  8. Christiane Baumeister & Luca Benati, 2012. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," Staff Working Papers 12-21, Bank of Canada.
  9. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September.
  10. Jordi Galí, 1992. "How Well Does The IS-LM Model Fit Postwar U. S. Data?," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 709-738.
  11. Fabio Canova & Gianni De Nicolo, 2000. "Monetary disturbances matter for business fluctuations in the G-7," International Finance Discussion Papers 660, Board of Governors of the Federal Reserve System (U.S.).
  12. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
  13. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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