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Fortune or virtue: time-variant volatilities versus parameter drifting

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Abstract

This paper compares the role of stochastic volatility versus changes in monetary policy rules in accounting for the time-varying volatility of U.S. aggregate data. Of special interest to the authors is understanding the sources of the great moderation of business cycle fluctuations that the U.S. economy experienced between 1984 and 2007. To explore this issue, the authors build a medium-scale dynamic stochastic general equilibrium (DSGE) model with both stochastic volatility and parameter drifting in the Taylor rule and they estimate it non-linearly using U.S. data and Bayesian methods. Methodologically, the authors show how to confront such a rich model with the data by exploiting the structure of the high-order approximation to the decision rules that characterize the equilibrium of the economy. Their main empirical findings are: 1) even after controlling for stochastic volatility (and there is a fair amount of it), there is overwhelming evidence of changes in monetary policy during the analyzed period; 2) however, these changes in monetary policy mattered little for the great moderation; 3) most of the great performance of the U.S. economy during the 1990s was a result of good shocks; and 4) the response of monetary policy to inflation under Burns, Miller, and Greenspan was similar, while it was much higher under Volcker.

Suggested Citation

  • Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramirez, 2010. "Fortune or virtue: time-variant volatilities versus parameter drifting," Working Papers 10-14, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:10-14
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    Cited by:

    1. Stevanovic Dalibor, 2016. "Common time variation of parameters in reduced-form macroeconomic models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 159-183, April.
    2. Benigno, Gianluca & Benigno, Pierpaolo & Nisticò, Salvatore, 2013. "Second-order approximation of dynamic models with time-varying risk," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1231-1247.
    3. Francesco Bianchi & Cosmin Ilut, 2017. "Monetary/Fiscal Policy Mix and Agent's Beliefs," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 26, pages 113-139, October.
    4. Stefano Eusepi & Bruce Preston, 2018. "Fiscal Foundations of Inflation: Imperfect Knowledge," American Economic Review, American Economic Association, vol. 108(9), pages 2551-2589, September.
    5. Alejandro Justiniano & Giorgio E. Primiceri & Andrea Tambalotti, 2013. "The Effects of the Saving and Banking Glut on the U.S. Economy," NBER Chapters, in: NBER International Seminar on Macroeconomics 2013, pages 52-67, National Bureau of Economic Research, Inc.
    6. Fasani, Stefano & Rossi, Lorenza, 2018. "Are uncertainty shocks aggregate demand shocks?," Economics Letters, Elsevier, vol. 167(C), pages 142-146.
    7. Andreasen, Martin M., 2012. "An estimated DSGE model: Explaining variation in nominal term premia, real term premia, and inflation risk premia," European Economic Review, Elsevier, vol. 56(8), pages 1656-1674.
    8. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Keith Kuester & Juan Rubio-Ramírez, 2015. "Fiscal Volatility Shocks and Economic Activity," American Economic Review, American Economic Association, vol. 105(11), pages 3352-3384, November.
    9. Traum, Nora & Yang, Shu-Chun S., 2011. "Monetary and fiscal policy interactions in the post-war U.S," European Economic Review, Elsevier, vol. 55(1), pages 140-164, January.
    10. Bidder, R.M. & Smith, M.E., 2012. "Robust animal spirits," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 738-750.
    11. Francesco Bianchi & Leonardo Melosi, 2017. "Escaping the Great Recession," American Economic Review, American Economic Association, vol. 107(4), pages 1030-1058, April.
    12. Jesús Fernández-Villaverde & Juan Rubio-Ramírez, 2010. "Macroeconomics and Volatility: Data, Models, and Estimation," NBER Working Papers 16618, National Bureau of Economic Research, Inc.
    13. Baele, Lieven & Bekaert, Geert & Cho, Seonghoon & Inghelbrecht, Koen & Moreno, Antonio, 2015. "Macroeconomic regimes," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 51-71.
    14. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    15. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    16. Lee, Junghoon, 2016. "The impact of idiosyncratic uncertainty when investment opportunities are endogenous," Journal of Economic Dynamics and Control, Elsevier, vol. 65(C), pages 105-124.
    17. Galvao Ana Beatriz & Marcellino Massimiliano, 2014. "The effects of the monetary policy stance on the transmission mechanism," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-20, May.
    18. Gonzalez-Astudillo, Manuel, 2011. "Policy Rule Coefficients Driven by Latent Factors: Monetary and Fiscal Policy Interactions in an Endowment Economy," MPRA Paper 29976, University Library of Munich, Germany.
    19. Lakdawala, Aeimit, 2016. "Changes in Federal Reserve preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 124-143.
    20. Gonzalez-Astudillo, Manuel, 2013. "Monetary-Fiscal Policy Interactions: Interdependent Policy Rule Coefficients," MPRA Paper 50040, University Library of Munich, Germany.
    21. Gianluca Benigno & Pierpaolo Benigno & Salvatore Nisticò, 2012. "Risk, Monetary Policy, and the Exchange Rate," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 247-309.
    22. Andreasen, Martin, 2011. "An estimated DSGE model: explaining variation in term premia," Bank of England working papers 441, Bank of England.
    23. Bianchi, Francesco, 2016. "Methods for measuring expectations and uncertainty in Markov-switching models," Journal of Econometrics, Elsevier, vol. 190(1), pages 79-99.
    24. Ryo Jinnai, 2011. "News Shocks, Price Levels, and Monetary Policy," Global COE Hi-Stat Discussion Paper Series gd10-173, Institute of Economic Research, Hitotsubashi University.
    25. Tae Bong Kim, 2013. "Monetary Policy in Korea through the lense of Taylor Rule in DSGE model," 2013 Meeting Papers 746, Society for Economic Dynamics.

    More about this item

    Keywords

    Monetary policy; Business cycles; Board of Governors of the Federal Reserve System (U.S.); Econometric models;
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