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

Jorge Luis Bazán () and Óscar Millones ()
Additional contact information
Jorge Luis Bazán: Pontificia Universidad Católica del Perú - Departamento de Ciencias
Óscar Millones: Pontificia Universidad Católica del Perú - Departamento de economía

Revista Economía, 2008, issue 62, 17-32

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.

Keywords: asymmetric links; binary regression; bayesian inference; discrete choice econometric models; WinBUGS. (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://revistas.pucp.edu.pe/index.php/economia/article/view/1176/1135 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pcp:pucrev:y:2008:i:62:p:17-32

Access Statistics for this article

Revista Economía is currently edited by Luis García

More articles in Revista Economía from Fondo Editorial - Pontificia Universidad Católica del Perú Av. Universitaria 1801, San Miguel, Lima, Perú. Contact information at EDIRC.
Bibliographic data for series maintained by ().