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Forecasting Inflation Using Constant Gain Least Squares

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  • Antipin, Jan-Erik

    ()
    (National Institute of Economic Research)

  • Boumediene, Farid Jimmy

    ()
    (Ministry of Finance)

  • Österholm, Pär

    ()
    (Sveriges Riksbank)

Abstract

This paper assesses the usefulness of constant gain least squares when forecasting inflation. An out-of-sample forecast exercise is conducted, in which univariate autoregressive models for inflation in Australia, Swe-den, the United Kingdom and the United States are used. The results suggest that it is possible to improve the forecast accuracy by employing constant gain least squares instead of ordinary least squares. In particular, when using a gain of 0.05, constant gain least squares generally outper-forms the corresponding autoregressive model estimated with ordinary least squares. In fact, at longer forecast horizons, the root mean square forecast error is reliably lowered for all four countries and for all lag lengths considered in the study.

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Bibliographic Info

Paper provided by National Institute of Economic Research in its series Working Paper with number 126.

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Length: 26 pages
Date of creation: 01 Feb 2012
Date of revision:
Handle: RePEc:hhs:nierwp:0126

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Keywords: Out-of-sample forecasts; Inflation;

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  1. Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 0247, European Central Bank.
  2. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, September.
  3. Meredith Beechey & Pär Österholm, 2012. "The Rise and Fall of U.S. Inflation Persistence," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 55-86, September.
  4. Meredith J. Beechey & Benjamin K. Johannsen & Andrew T. Levin, 2008. "Are long-run inflation expectations anchored more firmly in the Euro area than in the United States?," Finance and Economics Discussion Series 2008-23, Board of Governors of the Federal Reserve System (U.S.).
  5. Chengsi Zhang & Joel Clovis, 2009. "Modeling US inflation dynamics: persistence and monetary policy regimes," Empirical Economics, Springer, vol. 36(2), pages 455-477, May.
  6. Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327.
  7. Kaushik Mitra & James Bullard, . "Learning About Monetary Policy Rules," Discussion Papers 00/41, Department of Economics, University of York.
  8. Granger, Clive W. J. & Jeon, Yongil, 2003. "Comparing forecasts of inflation using time distance," International Journal of Forecasting, Elsevier, vol. 19(3), pages 339-349.
  9. Lutkepohl, Helmut, 2007. "General-to-specific or specific-to-general modelling? An opinion on current econometric terminology," Journal of Econometrics, Elsevier, vol. 136(1), pages 319-324, January.
  10. Beechey, Meredith & Österholm, Pär, 2010. "Forecasting inflation in an inflation-targeting regime: A role for informative steady-state priors," International Journal of Forecasting, Elsevier, vol. 26(2), pages 248-264, April.
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