IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v24y1999i1p135-153.html
   My bibliography  Save this article

An investigation into a non-linear stochastic trend model

Author

Listed:
  • Klaus Neusser

    (University of Berne, Department of Economics, Gesellschaftsstrasse 49, CH-3012 Berne, Switzerland)

Abstract

The paper explores the empirical properties of a non-linear stochastic trend model which can be viewed as an intermediate case between a linear and a log-linear trend model. I assess the small sample distribution of the ML estimator by Monte Carlo simulations and use it to model some typical macroeconomic time series. The non-linear trend model turns out to be an important tool which warrants further analysis. I also compute impulse response functions and compare them with those obtained from a conventional linear model.

Suggested Citation

  • Klaus Neusser, 1999. "An investigation into a non-linear stochastic trend model," Empirical Economics, Springer, vol. 24(1), pages 135-153.
    • Handle: RePEc:spr:empeco:v:24:y:1999:i:1:p:135-153
    Note: received: August 1997/final version received: June 1998
    as

    Download full text from publisher

    File URL: http://link.springer.de/link/service/journals/00181/papers/9024001/90240135.pdf
    Download Restriction: Access to the full text of the articles in this series is restricted
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Yoon, Gawon, 2005. "An introduction to I([infinity]) processes," Economic Modelling, Elsevier, vol. 22(3), pages 473-483, May.

    More about this item

    Keywords

    Non-linear trend · impulse response;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:spr:empeco:v:24:y:1999:i:1:p:135-153. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.