IDEAS home Printed from https://ideas.repec.org/p/nuf/econwp/0314.html
   My bibliography  Save this paper

The Properties of Automatic Gets Modelling

Author

Listed:
  • David Hendry

    (Dept of Economics and Nuffield College, Oxford University)

  • Hans-Martin Krolzig

    (Department of Economics, and Nuffield College, Oxford University)

Abstract

We examine the properties of automatic model selection, as embodied in PcGets, and evaluate its performance across different (unknown) states of nature. After describing the basic algorithm and some recent changes, we discuss the consistency of its selection procedures, then examine the extent to which model selection is non-distortionary at relevant sample sizes. The problems posed in judging performance on collinear data are noted. The conclusion notes how PcGets can handle more variables than observations, and hence how it can tackle non-linear models.

Suggested Citation

  • David Hendry & Hans-Martin Krolzig, 2003. "The Properties of Automatic Gets Modelling," Economics Papers 2003-W14, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:0314
    as

    Download full text from publisher

    File URL: http://www.nuff.ox.ac.uk/economics/papers/2003/W14/dfhhmk03a.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
    2. Department of Agriculture, 1983. "Statistics," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 22(2), October.
    3. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June.
    4. Kevin D. Hoover & Stephen J. Perez, 2004. "Truth and Robustness in Cross‐country Growth Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 765-798, December.
    5. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    6. Neil R. Ericsson & James G. MacKinnon, 2002. "Distributions of error correction tests for cointegration," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 285-318, June.
    7. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    8. Savin, N.E., 1984. "Multiple hypothesis testing," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 14, pages 827-879, Elsevier.
    9. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    10. Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.
    11. Bruce E. Hansen, 1999. "Discussion of 'Data mining reconsidered'," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 192-201.
    12. repec:oxf:wpaper:2000-w34.2 is not listed on IDEAS
    13. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
    14. J. David Baldwin & Ronald L. Oaxaca, 2003. "Editors' Introduction," American Economic Review, American Economic Association, vol. 93(2), pages 7-7, May.
    15. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    16. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    17. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    18. Department of Agriculture, 1983. "Statistics," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 22(1), April.
    19. P. Dorian Owen, 2003. "General‐to‐Specific Modelling Using PcGets," Journal of Economic Surveys, Wiley Blackwell, vol. 17(4), pages 609-628, September.
    20. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
    21. Atkinson, A. C., 1981. "Likelihood ratios, posterior odds and information criteria," Journal of Econometrics, Elsevier, vol. 16(1), pages 15-20, May.
    22. Banerjee, Anindya & Hendry, David F, 1992. "Testing Integration and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 225-255, August.
    23. Omtzigt Pieter, 2002. "Automatic identification and restriction of the cointegration space," Economics and Quantitative Methods qf0213, Department of Economics, University of Insubria.
    24. S. Fukuda-Parr, 2003. "Editor's Introduction," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 4(3), pages 323-324.
    25. 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.
    Full references (including those not matched with items on IDEAS)

    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. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages C32-C61, 03.

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nuf:econwp:0314. 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: Maxine Collett (email available below). General contact details of provider: https://www.nuffield.ox.ac.uk/economics/ .

    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.