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Linking series generated at different frequencies This work is part of a PhD dissertation presented at the University of California, San Diego (1999)

  • Namwon Hyung

    (Department of Economics, University of Seoul, Seoul, Korea)

  • Clive W.J. Granger

    (Department of Economics, University of California, San Diego, California, USA)

This is a report on our studies of the systematical use of mixed-frequency datasets. We suggest that the use of high-frequency data in forecasting economic aggregates can increase the accuracy of forecasts. The best way of using this information is to build a single model that relates the data of all frequencies, for example, an ARMA model with missing observations. As an application of linking series generated at different frequencies, we show that the use of a monthly industrial production index improves the predictability of the quarterly GNP. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1042
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 27 (2008)
Issue (Month): 2 ()
Pages: 95-108

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Handle: RePEc:jof:jforec:v:27:y:2008:i:2:p:95-108
DOI: 10.1002/for.1042
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  2. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  3. Abeysinghe, Tilak, 1998. "Forecasting Singapore's quarterly GDP with monthly external trade," International Journal of Forecasting, Elsevier, vol. 14(4), pages 505-513, December.
  4. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  5. Granger, Clive W.J., 1998. "Extracting Information from Mega-Panels and High-Frequency Data," University of California at San Diego, Economics Working Paper Series qt17t2d9n6, Department of Economics, UC San Diego.
  6. Luis C. Nunes, 2005. "Nowcasting quarterly GDP growth in a monthly coincident indicator model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 575-592.
  7. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
  8. Liu, H & Hall, Stephen G, 2001. "Creating High-Frequency National Accounts with State-Space Modelling: A Monte Carlo Experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 441-49, September.
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