IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Forecasting Aggregated Time Series Variables: A Survey

  • Helmut Lütkepohl

Aggregated times series variables can be forecasted in different ways. For example, they may be forecasted on the basis of the aggregate series or forecasts of disaggregated variables may be obtained fi rst and then these forecasts may be aggregated. A number of forecasts are presented and compared. Classical theoretical results on the relative effi ciencies of different forecasts are reviewed and some complications are discussed which invalidate the theoretical results. Contemporaneous as well as temporal aggregation are considered. JEL classifi cation : C22, C32 Key Words : Autoregressive moving-average process, contemporaneous aggregation, temporal aggregation, vector autoregressive moving-average process

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://dx.doi.org/10.1787/jbcma-2010-5km399r2jz9n
Download Restriction: Full text available to READ online. PDF download available to OECD iLibrary subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by OECD Publishing,Centre for International Research on Economic Tendency Surveys in its journal OECD Journal: Journal of Business Cycle Measurement and Analysis.

Volume (Year): 2010 (2010)
Issue (Month): 2 ()
Pages: 1-26

as
in new window

Handle: RePEc:oec:stdkab:5km399r2jz9n
Contact details of provider: Postal: 2 rue Andre Pascal, 75775 Paris Cedex 16
Phone: 33-(0)-1-45 24 82 00
Fax: 33-(0)-1-45 24 85 00
Web page: http://www.oecd.org
Email:


More information through EDIRC

Order Information: Web: http://www.oecd.org/bookshop?lang=en&pub=19952899

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Yamamoto, Taku, 1980. "On the Treatment of Autocorrelated Errors in the Multiperiod Prediction of Dynamic Simultaneous Equation Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(3), pages 735-48, October.
  2. Clements, Michael P. & Taylor, Nick, 2001. "Bootstrapping prediction intervals for autoregressive models," International Journal of Forecasting, Elsevier, vol. 17(2), pages 247-267.
  3. Evan Koenig & Sheila Dolmas & Jeremy M. Piger, 2002. "The use and abuse of 'real-time' data in economic forecasting," Working Papers 2001-015, Federal Reserve Bank of St. Louis.
  4. Andreas Beyer & Katarina Juselius, 2008. "Does it Matter How to Measure Aggregates? The Case of Monetary Transmission Mechanisms in the Euro Area," Discussion Papers 08-07, University of Copenhagen. Department of Economics.
  5. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-36, January.
  6. 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.
  7. Kemp, Gordon C.R., 1999. "The Behavior Of Forecast Errors From A Nearly Integrated Ar(1) Model As Both Sample Size And Forecast Horizon Become Large," Econometric Theory, Cambridge University Press, vol. 15(02), pages 238-256, April.
  8. Helmut Luetkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo Group Munich.
  9. Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-35, November.
  10. Ralf Brueggemann & Helmut Luetkepohl & Massimiliano Marcellino, 2006. "Forecasting Euro-Area Variables with German Pre-EMU Data," Economics Working Papers ECO2006/30, European University Institute.
  11. Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, Elsevier.
  12. David Hendry & Jurgen Doornik, 2000. "Constructing Historical Euro-Zone Data," Economics Series Working Papers 4, University of Oxford, Department of Economics.
  13. Reinsel, Gregory C. & Lewis, Richard A., 1987. "Prediction mean square error for non-stationary multivariate time series using estimated parameters," Economics Letters, Elsevier, vol. 24(1), pages 57-61.
  14. Lorenzo Pascual & Juan Romo & Esther Ruiz, 2004. "Bootstrap predictive inference for ARIMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 449-465, 07.
  15. William W. S. Wei, 1978. "Some Consequences of Temporal Aggregation in Seasonal Time Series Models," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 433-448 National Bureau of Economic Research, Inc.
  16. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non-linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300.
  17. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
  18. SBRANA, Giacomo & SILVESTRINI, Andrea, 2009. "What do we know about comparing aggregate and disaggregate forecasts?," CORE Discussion Papers 2009020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  19. Lutkepohl, Helmut, 1986. "Forecasting Vector ARMA Processes with Systematically Missing Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(3), pages 375-90, July.
  20. Andrea Silvestrini & David Veredas, 2008. "Temporal aggregation of univariate and multivariate time series models: a survey," ULB Institutional Repository 2013/136205, ULB -- Universite Libre de Bruxelles.
  21. Kim, Jae H., 1999. "Asymptotic and bootstrap prediction regions for vector autoregression," International Journal of Forecasting, Elsevier, vol. 15(4), pages 393-403, October.
  22. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  23. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  24. Grigoletto, Matteo, 1998. "Bootstrap prediction intervals for autoregressions: some alternatives," International Journal of Forecasting, Elsevier, vol. 14(4), pages 447-456, December.
  25. Helmut Lütkepohl & Ralf Brüggemann, 2006. "A small monetary system for the euro area based on German data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 683-702.
  26. Angelini, Elena & Marcellino, Massimiliano, 2011. "Econometric analyses with backdated data: Unified Germany and the euro area," Economic Modelling, Elsevier, vol. 28(3), pages 1405-1414, May.
  27. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
  28. Kohn, Robert, 1982. "When is an aggregate of a time series efficiently forecast by its past?," Journal of Econometrics, Elsevier, vol. 18(3), pages 337-349, April.
  29. Ralf Brüggemann & Helmut Lütkepohl, 2005. "Uncovered Interest Rate Parity and the Expectations Hypothesis of the Term Structure: Empirical Results for the U.S. and Europe," SFB 649 Discussion Papers SFB649DP2005-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  30. Víctor Gómez & Félix Aparicio-Pérez, 2009. "A new state-space methodology to disaggregate multivariate time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 97-124, 01.
  31. Lutkepohl, Helmut, 1981. "A model for non-negative and non-positive distributed lag functions," Journal of Econometrics, Elsevier, vol. 16(2), pages 211-219, June.
  32. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
  33. Stock, James H, 1996. "VAR, Error Correction and Pretest Forecasts at Long Horizons," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 685-701, November.
  34. Heather Anderson & Mardi Dungey & Denise R. Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," CAMA Working Papers 2007-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  35. Hoque, Asraul & Magnus, Jan R. & Pesaran, Bahram, 1988. "The exact multi-period mean-square forecast error for the first-order autoregressive model," Journal of Econometrics, Elsevier, vol. 39(3), pages 327-346, November.
  36. Lutkepohl, Helmut, 1985. "The joint asymptotic distribution of multistep prediction errors of estimated vector autoregressions," Economics Letters, Elsevier, vol. 17(1-2), pages 103-106.
  37. Bosker, E.M., 2006. "On the aggregation of eurozone data," Economics Letters, Elsevier, vol. 90(2), pages 260-265, February.
  38. Tiao, G. C. & Guttman, Irwin, 1980. "Forecasting contemporal aggregates of multiple time series," Journal of Econometrics, Elsevier, vol. 12(2), pages 219-230, February.
  39. Fagan, Gabriel & Henry, Jerome & Mestre, Ricardo, 2005. "An area-wide model for the euro area," Economic Modelling, Elsevier, vol. 22(1), pages 39-59, January.
  40. Brewer, K. R. W., 1973. "Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models," Journal of Econometrics, Elsevier, vol. 1(2), pages 133-154, June.
  41. Masarotto, Guido, 1990. "Bootstrap prediction intervals for autoregressions," International Journal of Forecasting, Elsevier, vol. 6(2), pages 229-239, July.
  42. Lewis, Richard & Reinsel, Gregory C., 1985. "Prediction of multivariate time series by autoregressive model fitting," Journal of Multivariate Analysis, Elsevier, vol. 16(3), pages 393-411, June.
  43. Baillie, Richard T, 1981. "Prediction from the Dynamic Simultaneous Equation Model with Vector Autoregressive Errors," Econometrica, Econometric Society, vol. 49(5), pages 1331-37, September.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:oec:stdkab:5km399r2jz9n. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.