IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02485120.html
   My bibliography  Save this paper

Estimation and identification of periodic autoregressive models with one exogenous variable

Author

Listed:
  • E. Ursu
  • Jean-Christophe Pereau

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper analyzes the identification and estimation procedures for periodic autoregressive models with one exogenous variable (PARX). The identification of the optimal PARX model is based on the use of a genetic algorithm combined with the Bayes information criterion. The estimation of the parameters relies on the least squares method and their asymptotic properties are studied. Two simulation experiments are performed and indicate the success of the suggested method. A PARX model is used to study the relationship between the catch-per-unit-effort and the sea surface temperature as exogenous variable for the shrimp French Guiana fishery from January 1989 to December 2012.

Suggested Citation

  • E. Ursu & Jean-Christophe Pereau, 2017. "Estimation and identification of periodic autoregressive models with one exogenous variable," Post-Print hal-02485120, HAL.
    • Handle: RePEc:hal:journl:hal-02485120
    DOI: 10.1016/j.jkss.2017.07.001
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Huaping Chen & Qi Li & Fukang Zhu, 2023. "A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 805-826, October.
    2. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.

    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:hal:journl:hal-02485120. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.