IDEAS home Printed from https://ideas.repec.org/a/cpn/umkdem/v11y2011p21-40.html
   My bibliography  Save this article

Information and Prediction Criteria in Selecting the Forecasting Model

Author

Listed:
  • Mariola Pilatowska

    (Nicolaus Copernicus University in Toruñ)

Abstract

The purpose of the paper it to compare the performance of both information and prediction criteria in selecting the forecasting model on empirical data for Poland when the data generating model is unknown. The attention will especially focus on the evolution of information criteria (AIC, BIC) and accumulated prediction error (APE) for increasing sample sizes and rolling windows of different size, and also the impact of initial sample and rolling window sizes on the selection of forecasting model. The best forecasting model will be chosen from the set including three models: autoregressive model, AR (with or without a deterministic trend), ARIMA model and random walk (RW) model.

Suggested Citation

  • Mariola Pilatowska, 2011. "Information and Prediction Criteria in Selecting the Forecasting Model," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 21-40.
  • Handle: RePEc:cpn:umkdem:v:11:y:2011:p:21-40
    as

    Download full text from publisher

    File URL: http://www.dem.umk.pl/dem/archiwa/v11/02_Pilatowska_M.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    2. Kunst, Robert M., 2003. "Testing for Relative Predictive Accuracy: A Critical Viewpoint," Economics Series 130, Institute for Advanced Studies.
    3. K. Skouras & A. P. Dawid, 1998. "On efficient point prediction systems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(4), pages 765-780.
    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. MAWANGA Freddie Festo, 2017. "Investigating A Random Walk In Air Cargo Exports Of Fresh Agricultural Products: Evidence From A Developing Country," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 12(1), pages 129-140, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    2. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    3. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    4. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    5. Oscar Claveria & Salvador Torra, 2013. "“Forecasting Business surveys indicators: neural networks vs. time series models”," AQR Working Papers 201312, University of Barcelona, Regional Quantitative Analysis Group, revised Nov 2013.
    6. Jesús Crespo Cuaresma & Ernest Gnan & Doris Ritzberger-Grünwald, 2005. "The Term Structure as a Predictor of Real Activity and Inflation in the Euro Area: A Reassessment," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 141(2), pages 318-342, July.
    7. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    8. repec:lan:wpaper:470 is not listed on IDEAS
    9. Lars-Erik Öller & Lasse Koskinen, 2004. "A classifying procedure for signalling turning points," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 197-214.
    10. G Johnes, 2005. "Skills and earnings revisited," Working Papers 573993, Lancaster University Management School, Economics Department.
    11. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    12. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del Perú.
    13. Geraint Johnes, 2000. "Up Around the Bend: Linear and nonlinear models of the UK economy compared," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(4), pages 485-493.
    14. Koen Pauwels & Dominique M. Hanssens, 2007. "Performance Regimes and Marketing Policy Shifts," Marketing Science, INFORMS, vol. 26(3), pages 293-311, 05-06.
    15. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    16. Clive Granger & Yongil Jeon, 2000. "Model evaluation based on residual analysis of two similar models," Applied Economics, Taylor & Francis Journals, vol. 32(7), pages 861-867.
    17. repec:lan:wpaper:4408 is not listed on IDEAS
    18. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    19. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    20. Anna Almosova & Niek Andresen, 2023. "Nonlinear inflation forecasting with recurrent neural networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 240-259, March.
    21. Ülengin, Füsun & Önsel, Sule & Ilker Topçu, Y. & Aktas, Emel & Kabak, Özgür, 2007. "An integrated transportation decision support system for transportation policy decisions: The case of Turkey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 80-97, January.
    22. Önsel, Sule & Ülengin, Füsun & Ulusoy, Gündüz & Aktas, Emel & Kabak, Özgür & Topcu, Y. Ilker, 2008. "A new perspective on the competitiveness of nations," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 221-246, December.

    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:cpn:umkdem:v:11:y:2011:p:21-40. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Miroslawa Buczynska (email available below). General contact details of provider: http://www.wydawnictwoumk.pl .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.