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

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

Abstract

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.

Suggested Citation

  • Juan F. Rubio-Ramírez & Jonas E. Arias & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 1338, BBVA Bank, Economic Research Department.
  • Handle: RePEc:bbv:wpaper:1338
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    References listed on IDEAS

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    1. Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
    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. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 10(Win), pages 2-16.
    4. 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.
    5. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, Oxford University Press, vol. 113(3), pages 869-902.
    6. Waggoner, Daniel F. & Zha, Tao, 2003. "Likelihood preserving normalization in multiple equation models," Journal of Econometrics, Elsevier, vol. 114(2), pages 329-347, June.
    7. 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.
    8. Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-141, April.
    9. Christiano, Lawrence J & Eichenbaum, Martin & Evans, Charles, 1996. "The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 16-34, February.
    10. Eleonora Granziera & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Inference for VARs identified with sign restrictions," Quantitative Economics, Econometric Society, vol. 9(3), pages 1087-1121, November.
    11. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    12. 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.
    13. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    14. Christiane Baumeister & Luca Benati, 2013. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," International Journal of Central Banking, International Journal of Central Banking, vol. 9(2), pages 165-212, June.
    15. Baumeister, Christiane & Benati, Luca, 2010. "Unconventional monetary policy and the great recession - Estimating the impact of a compression in the yield spread at the zero lower bound," Working Paper Series 1258, European Central Bank.
    16. DeJong, David N., 1992. "Co-integration and trend-stationarity in macroeconomic time series : Evidence from the likelihood function," Journal of Econometrics, Elsevier, vol. 52(3), pages 347-370, June.
    17. Leonardo Gambacorta & Boris Hofmann & Gert Peersman, 2014. "The Effectiveness of Unconventional Monetary Policy at the Zero Lower Bound: A Cross‐Country Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 615-642, June.
    18. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    19. Dario Caldara & Christophe Kamps, 2017. "The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers," Review of Economic Studies, Oxford University Press, vol. 84(3), pages 1015-1040.
    20. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1228-1247, December.
    21. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    22. Hyungsik Roger Moon & Frank Schorfheide, 2012. "Bayesian and Frequentist Inference in Partially Identified Models," Econometrica, Econometric Society, vol. 80(2), pages 755-782, March.
    23. Andrew Binning, 2013. "Underidentified SVAR models: A framework for combining short and long-run restrictions with sign-restrictions," Working Paper 2013/14, Norges Bank.
    24. 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.).
    25. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
    26. Maria Abascal & Tatiana Alonso & Sergio Mayordomo, 2013. "Fragmentation in European Financial Markets: Measures, Determinants, and Policy Solutions," Working Papers 1322, BBVA Bank, Economic Research Department.
    27. 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.
    28. Paul Beaudry & Deokwoo Nam & Jian Wang, 2011. "Do Mood Swings Drive Business Cycles and is it Rational?," NBER Working Papers 17651, National Bureau of Economic Research, Inc.
    29. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
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    More about this item

    Keywords

    Sign and Zero Restrictions; Optimism and Fiscal Shocks; SVARs;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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