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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))

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    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. Mountford, Andrew & Uhlig, Harald, 2002. "What are the Effects of Fiscal Policy Shocks?," CEPR Discussion Papers 3338, C.E.P.R. Discussion Papers.
    2. 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.).
    3. 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.
    4. repec:oup:restud:v:77:y:2010:i:2:p:665-696 is not listed on IDEAS
    5. Renee Fry & Adrian Pagan, 2010. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," CAMA Working Papers 2010-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," FRB Atlanta Working Paper 2008-18, Federal Reserve Bank of Atlanta.
    7. Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 0722, European Central Bank.
    8. 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.).
    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. 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.).
    11. 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.
    12. 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.
    13. 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.
    14. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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