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The Variance-Frequency Decomposition as an Instrument for VAR Identification: an Application to Technology Shocks

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  • Lovcha, Yuliya
  • Pérez Laborda, Àlex

Abstract

Abstract: This paper proposes a new framework to study identification in structural VAR models. The framework is based on the variance-frequency decomposition and focuses on the contribution of the identified shock to the variance of model variables in a given frequency range. We use the hours-productivity debate as a connecting thread in our discussion since the identification problem has attracted a lot of attention in this literature. To start, we employ the framework to study the business cycle properties of a set of different identification schemes for technology shocks. Grounded on the simulation results, we propose a new model-based procedure which delivers a precise estimate of the response of hours. Finally, we put all the schemes to work with real data, obtaining substantial evidence in favor of plausible RBC parametrizations, especially from identification restrictions that perform better in simulations. This analysis also reveals that the schemes that recover a very strong response of hours (higher than the implied by typical RBC parameterizations) tend to overstate the contribution of the technology shock to the fluctuations of hours worked at business cycle frequencies. Keywords: Business cycle, frequency domain, hours worked, productivity, vector autoregressions. Classification: C1, E3

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  • Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "The Variance-Frequency Decomposition as an Instrument for VAR Identification: an Application to Technology Shocks," Working Papers 2072/261537, Universitat Rovira i Virgili, Department of Economics.
  • Handle: RePEc:urv:wpaper:2072/261537
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    References listed on IDEAS

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    1. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006. "Alternative Procedures for Estimating Vector Autoregressions Identified with Long-Run Restrictions," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 475-483, 04-05.
    2. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    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 Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05.
    5. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
    6. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
    7. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106, National Bureau of Economic Research, Inc.
    8. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
    9. Nikolay Gospodinov & Alex Maynard & Elena Pesavento, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 455-467, October.
    10. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    11. Faust, Jon & Leeper, Eric M, 1997. "When Do Long-Run Identifying Restrictions Give Reliable Results?," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 345-353, July.
    12. Riccardo DiCecio & Michael T. Owyang, 2010. "Identifying technology shocks in the frequency domain," Working Papers 2010-025, Federal Reserve Bank of St. Louis.
    13. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05.
    14. Fabio Canova & David Lopez-Salido & Claudio Michelacci, 2010. "The effects of technology shocks on hours and output: a robustness analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 755-773.
    15. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    16. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
    17. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2015. "The Hours Worked–Productivity Puzzle: Identification In A Fractional Integration Setting," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1593-1621, October.
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    Cited by:

    1. Alessio Volpicella, 2019. "SVARs Identification through Bounds on the Forecast Error Variance," Working Papers 890, Queen Mary University of London, School of Economics and Finance.
    2. Lovcha, Yuliya & Pérez Laborda, Alejandro, 2016. "Frequency-Domain Estimation as an Alternative to Pre-Filtering External Cycles in Structural VAR Analysis," Working Papers 2072/290743, Universitat Rovira i Virgili, Department of Economics.

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    Cicles econòmics; 33 - Economia;

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