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Forecasting Inflation Using Constant Gain Least Squares

  • Antipin, Jan-Erik

    ()

    (National Institute of Economic Research)

  • Boumediene, Farid Jimmy

    ()

    (Ministry of Finance)

  • Österholm, Pär

    ()

    (Sveriges Riksbank)

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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File URL: http://www.konj.se/download/18.33db2ae01355ec8e8f27da/WP_126.pdf
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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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  1. Kaushik Mitra & James Bullard, . "Learning About Monetary Policy Rules," Discussion Papers 00/41, Department of Economics, University of York.
  2. Beechey, Meredith & Österholm, Pär, 2007. "The Rise and Fall of U.S. Inflation Persistence," Working Paper Series 2007:18, Uppsala University, Department of Economics.
  3. Meredith J. Beechey & Benjamin K. Johannsen & Andrew T. Levin, 2011. "Are Long-Run Inflation Expectations Anchored More Firmly in the Euro Area Than in the United States?," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 104-29, April.
  4. 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.
  5. 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.
  6. Chengsi Zhang & Joel Clovis, 2009. "Modeling US inflation dynamics: persistence and monetary policy regimes," Empirical Economics, Springer, vol. 36(2), pages 455-477, May.
  7. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  8. 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.
  9. Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327.
  10. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, March.
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