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Forecasting Some Low-Predictability Time Series Using Diffusion Indices

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  • Marc Brisson
  • Bryan Campbell

    ()

  • John Galbraith

    ()

Abstract

The growth rates of real output and real investment are two macroeconomic time series which are particularly difficult to forecast. This paper considers the application of diffusion index forecasting models to this problem. We begin by characterizing the performance of standard forecasts, via recently-introduced measures of predictability and the forecast content, noting the maximum horizon at which the forecasts have value. We then compare diffusion index forecasts with a variety of alternatives, including the forecasts made by the OECD. We find gains in forecast accuracy at short horizons from the diffusion index models, but do not find evidence that the maximum horizon for forecasts can be extended in this way. Les taux de croissance de production et d'investissements réels sont deux séries macroéconomiques qui sont particulièrement difficiles à prévoir. Nous considérons dans cet article l'application des méthodes d'indice de diffusion à ce problème. Nous commençons avec une caractérisation de la performance des méthodes de prévision standards, via les mesures nouvelles de prévisibilité et la valeur ajoutée des prévisions, en notant l'horizon maximal auquel les prévisions ont de la valeur. Nous comparons les prévisions provenant des indices de diffusion avec les alternatives, incluant les prévisions de l'OCDE. Nous trouvons des gains en précision des prévisions,0501s ne trouvons pas que l'horizon maximal de prévision peut être augmenté.

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Bibliographic Info

Paper provided by CIRANO in its series CIRANO Working Papers with number 2001s-46.

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Date of creation: 01 Jul 2001
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Handle: RePEc:cir:cirwor:2001s-46

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Keywords: Diffusion index; forecasting; investment; GDP; Indice de diffusion; prévisions; investissement; PNB;

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References

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  1. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
  2. Francis X. Diebold & Lutz Kilian, 1998. "Measuring Predictability: Theory and Macroeconomic Applications," Working Papers 98-16, New York University, Leonard N. Stern School of Business, Department of Economics.
  3. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
  4. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September.
  5. Meese, Richard & Geweke, John, 1984. "A Comparison of Autoregressive Univariate Forecasting Procedures for Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 191-200, July.
  6. Clements, Michael P. & Hendry, David F., 1998. "Forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 14(1), pages 111-131, March.
  7. Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
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Citations

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Cited by:
  1. John G. Galbraith & Greg Tkacz, 2006. "How Far Can We Forecast? Forecast Content Horizons For Some Important Macroeconomic Time Series," Departmental Working Papers 2006-13, McGill University, Department of Economics.
  2. Jonas Dovern, 2006. "Predicting GDP Components. Do Leading Indicators Increase Predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy.
  3. Pang, Iris Ai Jao, 2010. "Forecasting Hong Kong economy using factor augmented vector autoregression," MPRA Paper 32495, University Library of Munich, Germany.
  4. John W. Galbraith & Greg Tkacz, 2007. "Forecast content and content horizons for some important macroeconomic time series," Canadian Journal of Economics, Canadian Economics Association, vol. 40(3), pages 935-953, August.
  5. Bryan Campbell & Steve Murphy, 2006. "The Recent Performance of the Canadian Forecasting Industry," Canadian Public Policy, University of Toronto Press, vol. 32(1), pages 23-40, March.
  6. Marcel Dagenais & Claude Montmarquette & Nathalie Viennot-Briot, 2001. "Dropout, School Performance and Working while in School : An Econometric Model with Heterogeneous Groups," CIRANO Working Papers 2001s-63, CIRANO.
  7. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
  8. Schumacher, Christian, 2010. "Factor forecasting using international targeted predictors: The case of German GDP," Economics Letters, Elsevier, vol. 107(2), pages 95-98, May.
  9. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Working Papers 07-8, Bank of Canada.
  10. Konstantin A. Kholodilin & Boriss Siliverstovs, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(3), pages 234-259, May.
  11. Roberto Tatiwa Ferreira & Luiz Ivan de Melo Castelar, 2005. "Forecasting Quarterly Brazilian Gdp Growth Rate With Linear And Nonlinear Diffusion Index Models," Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33th Brazilian Economics Meeting] 029, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
  12. Eickmeier, Sandra & Ng, Tim, 2009. "Forecasting national activity using lots of international predictors: an application to New Zealand," Discussion Paper Series 1: Economic Studies 2009,11, Deutsche Bundesbank, Research Centre.
  13. Boriss Siliverstovs & Kinstantin Kholodilim, 2009. "On selection of components for a diffusion index model: it's not the size, it's how you use it," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1249-1254.
  14. Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Working Papers 01-18, Bank of Canada.
  15. Daniel Grenouilleau, 2004. "A sorted leading indicators dynamic (SLID) factor model for short-run euro-area GDP forecasting," European Economy - Economic Papers 219, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.

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