IDEAS home Printed from https://ideas.repec.org/p/nuf/econwp/0425.html
   My bibliography  Save this paper

Two sided analysis of variance with a latent time series

Author

Listed:
  • Lars Hougaard Hansen

    (University of Copenhagen and Codan forsikring)

  • Bent Nielsen

    () (Nuffield College, Oxford University, UK)

  • Jens Perch Nielsen

    (Codan forsikring)

Abstract

Many real life regression problems exhibit some kind of calender time dependency and it is often of interest to predict the behavior of the regression function along this calender time direction. This can be formulated as a regression model with an added latent time series and the task is to be able to analyse this series. In this paper we engage this through a two step procedure, firstly we treat the time dependent elements as parameters and estimate them in the two-sided analysis of variance setup, secondly we use the estimated time series as predictor of the latent time series. An application to risk theory is discussed.

Suggested Citation

  • Lars Hougaard Hansen & Bent Nielsen & Jens Perch Nielsen, 2004. "Two sided analysis of variance with a latent time series," Economics Papers 2004-W25, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:0425
    as

    Download full text from publisher

    File URL: http://www.nuff.ox.ac.uk/economics/papers/2004/w25/latent.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Bent Nielsen, 1995. "Bartlett correction of the unit root test in autoregressive models," Economics Papers 11 & 98., Economics Group, Nuffield College, University of Oxford.
    2. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    3. Nielsen, Bent, 2001. "The Asymptotic Distribution of Unit Root Tests of Unstable Autoregressive Processes," Econometrica, Econometric Society, vol. 69(1), pages 211-219, January.
    4. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    5. Lai, T. L. & Wei, C. Z., 1983. "Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters," Journal of Multivariate Analysis, Elsevier, vol. 13(1), pages 1-23, March.
    6. England, P.D. & Verrall, R.J., 2002. "Stochastic Claims Reserving in General Insurance," British Actuarial Journal, Cambridge University Press, vol. 8(03), pages 443-518, August.
    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. Gregory Connor & Matthias Hagmann & Oliver Linton, 2007. "Efficient Estimation of a Semiparametric Characteristic- Based Factor Model of Security Returns," Swiss Finance Institute Research Paper Series 07-26, Swiss Finance Institute.
    2. Oliver Linton & Jens Perch Nielsen & Søren Feodor Nielsen, 2009. "Non-parametric regression with a latent time series," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 187-207, July.
    3. Park, Byeong U. & Mammen, Enno & Härdle, Wolfgang & Borak, Szymon, 2009. "Time Series Modelling With Semiparametric Factor Dynamics," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 284-298.

    More about this item

    Keywords

    regression; time series; risk theory;

    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:0425. 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: (Maxine Collett). General contact details of provider: https://www.nuffield.ox.ac.uk/economics/ .

    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.