Métodos cuantitativos para un modelo de regresión lineal con multicolinealidad: Aplicación a rendimientos de letras del tesoro

Artikel

It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained by using the Ordinary Least Squares (OLS) method are unstable. As a solution to this situation, in this paper we present the raised method, the ridge method and the orthogonal variables method as an alternative to the estimate by OLS. It is also shown that regression with orthogonal variables makes sense regardless of the existence of serious multicollinearity because it allows to answer questions which are not accessible when using the original model. These methodologies are applied to a data set of yields of treasury bills.

Object Details

• Language: Spanisch

References and Relationships

• Bibliographic citation: Journal: Revista de Métodos Cuantitativos para la Economía y la Empresa ; ISSN: 1886-516X ; Volume: 24 ; Year: 2017 ; Pages: 169-189 ; Sevilla: Universidad Pablo de Olavide

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
• Subject: regression models ; multicollinearity ; raised regression ; ridge regression ; regression with orthogonal variables

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gómez, Román Salmerón ; Martínez, Eduardo Rodríguez
• Event: Veröffentlichung
• (who): Universidad Pablo de Olavide
• (where): Sevilla
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/195386
• Last update: 28.11.2025, 8:43 PM CET