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Macroeconomic forecasting and structural change

  • Gambetti, Luca
  • D’Agostino, Antonello
  • Giannone, Domenico

The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coefficients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the na¨ıve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation. JEL Classification: C32, E37, E47

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Paper provided by European Central Bank in its series Working Paper Series with number 1167.

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Date of creation: Apr 2010
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Handle: RePEc:ecb:ecbwps:20101167
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  1. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  2. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
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  4. Barro, Robert J., 1987. "Government spending, interest rates, prices, and budget deficits in the United Kingdom, 1701-1918," Journal of Monetary Economics, Elsevier, vol. 20(2), pages 221-247, September.
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  7. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
  8. Pivetta, Frederic & Reis, Ricardo, 2007. "The persistence of inflation in the United States," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1326-1358, April.
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  13. John M. Roberts, 2004. "Monetary policy and inflation dynamics," Finance and Economics Discussion Series 2004-62, Board of Governors of the Federal Reserve System (U.S.).
  14. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
  15. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
  16. Giannone, Domenico & Lenza, Michele & Reichlin, Lucrezia, 2007. "Explaining The Great Moderation: It Is Not The Shocks," CEPR Discussion Papers 6600, C.E.P.R. Discussion Papers.
  17. Barbara Rossi & Tatevik Sekhposyan, 2010. "Has Models' Forecasting Performance for US Output Growth and Inflation Changed over Time, and When?," Working Papers 10-16, Duke University, Department of Economics.
  18. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
  19. Todd E. Clark & Michael W. McCracken, 2007. "Forecasting with small macroeconomic VARs in the presence of instabilities," Finance and Economics Discussion Series 2007-41, Board of Governors of the Federal Reserve System (U.S.).
  20. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(01), pages 1-30, February.
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