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Macroeconomic Forecasting and Structural Change

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

Abstract

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 naïve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7542.

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Date of creation: Nov 2009
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Handle: RePEc:cpr:ceprdp:7542

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Keywords: Forecasting; Inflation; Stochastic Volatility; Time Varying Vector Autoregression;

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References

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  1. John M. Roberts, 2006. "Monetary Policy and Inflation Dynamics," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
  2. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2008. "Explaining The Great Moderation: It Is Not The Shocks," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 621-633, 04-05.
  3. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
  4. 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.
  5. 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.
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  7. Douglas Staiger & James H. Stock & Mark W. Watson, 2001. "Prices, Wages and the U.S. NAIRU in the 1990s," NBER Working Papers 8320, National Bureau of Economic Research, Inc.
  8. 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.).
  9. James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
  10. 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.
  11. D'Agostino, Antonello & Domenico, Giannone & Surico, Paolo, 2006. "(Un)Predictability and Macroeconomic Stability," Research Technical Papers 5/RT/06, Central Bank of Ireland.
  12. 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.
  13. 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.
  14. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2008. "Inflation-Gap Persistence in the U.S," NBER Working Papers 13749, National Bureau of Economic Research, Inc.
  15. Tatevik Sekhposyan & Barbara Rossi, 2008. "Has modelsí forecasting performance for US output growth and inflation changed over time, and when?," Working Papers 09-02, Duke University, Department of Economics.
  16. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
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