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Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications

  • Juan F. Rubio-Ramírez
  • Jonas E. Arias
  • Daniel F. Waggoner

Are optimism shocks an important source of business cycle fluctuations? Are decit-nanced tax cuts better than decit-nanced spending to increase output? These questions have been previously studied using SVARs identied with sign and zero restrictions and the answers have been positive and denite in both cases. While the identication of SVARs with sign and zero restrictions is theoretically attractive because it allows the researcher to remain agnostic with respect to the responses of the key variables of interest, we show that current implementation of these techniques does not respect the agnosticism of the theory. These algorithms impose additional sign restrictions on variables that are seemingly unrestricted that bias the results and produce misleading condence intervals. We provide an alternative and ecient algorithm that does not introduce any additional sign restriction, hence preserving the agnosticism of the theory. Without the additional restrictions, it is hard to support the claim that either optimism shocks are an important source of business cycle fluctuations or decit-nanced tax cuts work best at improving output. Our algorithm is not only correct but also faster than current ones.

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Paper provided by BBVA Bank, Economic Research Department in its series Working Papers with number 1338.

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Length: 70 pages
Date of creation: Dec 2013
Date of revision:
Handle: RePEc:bbv:wpaper:1338
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  13. Juan F. Rubio-Ramírez & Daniel F.Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," Working Paper 2008-18, Federal Reserve Bank of Atlanta.
  14. Mariana A. Toran & F. Javier Morales & Sara G. Castellanos, 2012. "Analysis of the Use of Financial Services by Companies in Mexico: What does the 2009 Economic Census tell us?," Working Papers 1216, BBVA Bank, Economic Research Department.
  15. Daniel F. Waggoner & Tao Zha, 2000. "Likelihood-preserving normalization in multiple equation models," Working Paper 2000-8, Federal Reserve Bank of Atlanta.
  16. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
  17. Andrew Binning, 2013. "Underidentified SVAR models: A framework for combining short and long-run restrictions with sign-restrictions," Working Paper 2013/14, Norges Bank.
  18. Dario Caldara & Christophe Kamps, 2012. "The analytics of SVARs: a unified framework to measure fiscal multipliers," Finance and Economics Discussion Series 2012-20, Board of Governors of the Federal Reserve System (U.S.).
  19. Paul Beaudry & Deokwoo Nam & Jian Wang, 2011. "Do mood swings drive business cycles and is it rational?," Globalization and Monetary Policy Institute Working Paper 98, Federal Reserve Bank of Dallas.
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  23. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
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