IDEAS home Printed from https://ideas.repec.org/a/qua/journl/v7y2010i1p95-117.html
   My bibliography  Save this article

Ajuste recursivo con transformaciones invariantes y bootstrapping: El caso de una caminata aleatoria con intercepto

Author

Listed:
  • Eddy Lizarazu Alanez

    (UAM-Iztapalapa)

  • Jose A. Villasenor Alva

    (Colegio de Postgraduados)

Abstract

Usamos simulaciones de Monte Carlo para estudiar el desempeno de la prueba de raiz unitaria de Shin-So (DFSS) bajo los enfoques de transformaciones invariantes y el bootstrapping. Si la hipotesis alternativa es un proceso estacionario alrededor de una tendencia lineal, entonces la prueba bootstrap parametrica es la mejor en terminos de la potencia estadistica. Sin embargo, si transformamos las observaciones para construir una prueba invariante, entonces la prueba DFSS es la mejor. Por consiguiente, la recomendacion es usar transformaciones invariantes de la prueba de raiz unitaria de Shin-So debido a que su ejecucion es directa y de menor coste.

Suggested Citation

  • Eddy Lizarazu Alanez & Jose A. Villasenor Alva, 2010. "Ajuste recursivo con transformaciones invariantes y bootstrapping: El caso de una caminata aleatoria con intercepto," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 7(1), pages 95-117, Julio - D.
    • Handle: RePEc:qua:journl:v:7:y:2010:i:1:p:95-117
    as

    Download full text from publisher

    File URL: http://econoquantum.cucea.udg.mx/index.php/EQ/article/view/121
    Download Restriction: no
    File URL: http://econoquantum.cucea.udg.mx/index.php/EQ/issue/view/18
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Ajuste de tendencia recursivo; estadistico DF; metodo bootstrap parametrico.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:qua:journl:v:7:y:2010:i:1:p:95-117. 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: Sandra Ivett Portugal Padilla (email available below). General contact details of provider: https://edirc.repec.org/data/dmudgmx.html .

    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.