IDEAS home Printed from
   My bibliography  Save this paper

Statistical methods for modelling neural networks


  • Marcelo C. Medeiros

    () (Department of Economics PUC-Rio)

  • Timo Terasvirta

    (Department of Economic Statistics, Stockholm School of Economics)


In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model selection criteria and tests. Misspecification tests for evaluating an estimated neural network model are considered. Forecasting with neural network models is discussed and an application to a real time series is presented.

Suggested Citation

  • Marcelo C. Medeiros & Timo Terasvirta, 2001. "Statistical methods for modelling neural networks," Textos para discussão 445, Department of Economics PUC-Rio (Brazil).
  • Handle: RePEc:rio:texdis:445

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    2. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    3. Dolado Juan & Pedrero Ramón María-Dolores & Ruge-Murcia Francisco J., 2004. "Nonlinear Monetary Policy Rules: Some New Evidence for the U.S," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(3), pages 1-34, September.
    4. Bec Frédérique & Ben Salem Mélika & Collard Fabrice, 2002. "Asymmetries in Monetary Policy Reaction Function: Evidence for U.S. French and German Central Banks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    5. Nobay, A. R. & Peel, D. A., 2000. "Optimal monetary policy with a nonlinear Phillips curve," Economics Letters, Elsevier, vol. 67(2), pages 159-164, May.
    6. Márcio gomes Pinto Garcia & Marcus Vinicius Ferrero Valpassos, 1998. "Capital flows, capital controls and currency crisis: the case of Brazil in the nineties," Textos para discussão 389, Department of Economics PUC-Rio (Brazil).
    7. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    8. Dionísio Dias Carneiro & Thomas Yen Hon Wu, 2001. "Contas externas e política monetária," Textos para discussão 442, Department of Economics PUC-Rio (Brazil).
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:rio:texdis:445. 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: (). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.