IDEAS home Printed from https://ideas.repec.org/a/pcp/pucrev/y2008i62p17-32.html
   My bibliography  Save this article

Una clasificación de modelos de regresión binaria asimétrica: el uso del BAYES-PUCP en una aplicación sobre la decisión del cultivo ilícito de hoja de coca

Author

Listed:
  • Jorge Luis Bazán

    (Pontificia Universidad Católica del Perú - Departamento de Ciencias)

  • Óscar Millones

    (Pontificia Universidad Católica del Perú - Departamento de economía)

Abstract

In classical econometric binary regression models, the logistic regression model has been used associated to the logit symmetric link. The purpose of this paper is to present binary regression models with rather asymmetric links —not yet available as commercial software—, when this asymmetry is more appropriate to the researcher. In addition, a utility program called BAYES-PUCP is implemented. BAYES-PUCP uses a bayesian approach with the program WinBUGS and will facilitate the writing of the syntax for the models reviewed. It also generates both the syntax and the structure of the data. The method is illustrated for a sample of farmers who consider the decision to eradicate illegal crops of coca leaf. Factors associated with this decision are also explored.

Suggested Citation

  • Jorge Luis Bazán & Óscar Millones, 2008. "Una clasificación de modelos de regresión binaria asimétrica: el uso del BAYES-PUCP en una aplicación sobre la decisión del cultivo ilícito de hoja de coca," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, issue 62, pages 17-32.
    • Handle: RePEc:pcp:pucrev:y:2008:i:62:p:17-32
    as

    Download full text from publisher

    File URL: http://revistas.pucp.edu.pe/index.php/economia/article/view/1176/1135
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Artur J. Lemonte & Jorge L. Bazán, 2018. "New links for binary regression: an application to coca cultivation in Peru," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 597-617, September.
    2. Artur J. Lemonte & Germán Moreno–Arenas, 2020. "Improved Estimation for a New Class of Parametric Link Functions in Binary Regression," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 84-110, May.

    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:pcp:pucrev:y:2008:i:62:p:17-32. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/depucpe.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.