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Macroeconomics and Volatility: Data, Models, and Estimation

Listed author(s):
  • Jesús Fernández-Villaverde
  • Juan Rubio-Ramírez

One basic feature of aggregate data is the presence of time-varying variance in real and nominal variables. Periods of high volatility are followed by periods of low volatility. For instance, the turbulent 1970s were followed by the much more tranquil times of the great moderation from 1984 to 2007. Modeling these movements in volatility is important to understand the source of aggregate fluctuations, the evolution of the economy, and for policy analysis. In this chapter, we first review the different mechanisms proposed in the literature to generate changes in volatility similar to the ones observed in the data. Second, we document the quantitative importance of time-varying volatility in aggregate time series. Third, we present a prototype business cycle model with time-varying volatility and explain how it can be computed and how it can be taken to the data using likelihood-based methods and non-linear filtering theory. Fourth, we present two "real life" applications. We conclude by summarizing what we know and what we do not know about volatility in macroeconomics and by pointing out some directions for future research.

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File URL: http://www.nber.org/papers/w16618.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16618.

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Date of creation: Dec 2010
Publication status: published as (2013) \Macroeconomics and Volatility: Data, Models, and Methods." Joint with Juan F. Rubio-Ramrez (Duke University). In Advances in Economics and Econo- metrics: Theory and Applications, Tenth World Congress of the Econometric So- ciety , Cambridge University Press.
Handle: RePEc:nbr:nberwo:16618
Note: EFG
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  1. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2010. "Reading the Recent Monetary History of the U.S., 1959-2007," PIER Working Paper Archive 10-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  2. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2010. "Fortune or Virtue: Time-Variant Volatilities Versus Parameter Drifting in U.S. Data," PIER Working Paper Archive 10-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  4. Fernández-Villaverde, Jesús & Rubio-Ramírez, Juan Francisco, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," CEPR Discussion Papers 5513, C.E.P.R. Discussion Papers.
  5. Bekaert, Geert & Hoerova, Marie & Lo Duca, Marco, 2010. "Risk, Uncertainty and Monetary Policy," CEPR Discussion Papers 8154, C.E.P.R. Discussion Papers.
  6. Fernandez-Villaverde, Jesus & Francisco Rubio-Ramirez, Juan, 2004. "Comparing dynamic equilibrium models to data: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 123(1), pages 153-187, November.
  7. Graciela L. Kaminsky & Carmen M. Reinhart & Carlos A. Végh, 2003. "The Unholy Trinity of Financial Contagion," Journal of Economic Perspectives, American Economic Association, vol. 17(4), pages 51-74, Fall.
  8. Elder, John, 2004. "Another Perspective on the Effects of Inflation Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(5), pages 911-928, October.
  9. Steffen Elstner & Eric Sims & Ruediger Bachmann, 2010. "Uncertainty and Economic Activity: Evidence from Business Survey Data," 2010 Meeting Papers 614, Society for Economic Dynamics.
  10. Pablo Guerron & Martin Uribe & Juan Rubio-Ramirez & Jesus Fernandez-Villaverde, 2010. "Risk Matters: The Real Effects of Volatility Shocks," 2010 Meeting Papers 281, Society for Economic Dynamics.
  11. Kevin B. Grier & Mark J. Perry, 2000. "The effects of real and nominal uncertainty on inflation and output growth: some garch-m evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 45-58.
  12. Manuel S. Santos & Adrian Peralta-Alva, 2003. "Accuracy of Simulations for Stochastic Dynamic Models," Levine's Bibliography 666156000000000264, UCLA Department of Economics.
  13. Kiseok Lee & Shawn Ni & Ronald A. Ratti, 1995. "Oil Shocks and the Macroeconomy: The Role of Price Variability," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 39-56.
  14. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez, 2004. "Estimating dynamic equilibrium economies: linear versus nonlinear likelihood," FRB Atlanta Working Paper 2004-3, Federal Reserve Bank of Atlanta.
  15. Jesus Fernández-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2010. "Fortune or virtue: time-variant volatilities versus parameter drifting," Working Papers 10-14, Federal Reserve Bank of Philadelphia.
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