IDEAS home Printed from https://ideas.repec.org/a/isa/journl/v12y2010i2-3p73-96.html
   My bibliography  Save this article

Direct vs Indirect Forecasts of Foreign Trade Unit Value Indices

Author

Listed:
  • Giancarlo Lutero

    ()

  • Marco Marini

    () (Italian National Institute of Statistics)

Abstract

This paper examines the forecasting approach of foreign trade unit value indices followed in the compilation of quarterly national accounts of Italy. Total imports and exports indices are indirectly obtained from the aggregation of ARIMA forecasts of disaggregated components, derived from the program TRAMO with automatic identification options. An out-of-sample forecasting exercise is performed to validate the automatic choices made by TRAMO and to evaluate the relative performance of a direct forecasting approach of imports and exports aggregates. Also, we show how the use of international raw commodity prices can improve the forecasting accuracy of aggregate unit value indices.

Suggested Citation

  • Giancarlo Lutero & Marco Marini, 2010. "Direct vs Indirect Forecasts of Foreign Trade Unit Value Indices," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 12(2-3), pages 73-96, October.
  • Handle: RePEc:isa:journl:v:12:y:2010:i:2-3:p:73-96
    as

    Download full text from publisher

    File URL: http://www.istat.it/it/files/2011/09/2-3_2010_4.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    3. Forni, Mario & Lippi, Marco, 1997. "Aggregation and the Microfoundations of Dynamic Macroeconomics," OUP Catalogue, Oxford University Press, number 9780198288008.
    4. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
    5. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    6. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, April.
    7. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    8. Lee, Kevin C & Pesaran, M Hashem & Pierse, Richard G, 1990. "Testing for Aggregation Bias in Linear Models," Economic Journal, Royal Economic Society, vol. 100(400), pages 137-150, Supplemen.
    9. Massimiliano Marcellino, 2004. "Forecast Pooling for European Macroeconomic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 91-112, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sara Rafiq & Liu Hai Yun & Gulzar Ali, 2016. "Forecasting the Trend Analysis of Trade Balance of Pakistan: A Theoretical and Empirical Investigation," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 6(7), pages 188-214, July.

    More about this item

    Keywords

    Forecast aggregation; Foreign trade statistics; Flash estimates; Quarterly National Accounts;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:isa:journl:v:12:y:2010:i:2-3:p:73-96. 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: (Stefania Rossetti). General contact details of provider: http://edirc.repec.org/data/istgvit.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.