Persona: Rodríguez Sánchez, Ainara
Cargando...
Dirección de correo electrónico
arsanchez@cee.uned.es
ORCID
Fecha de nacimiento
Proyectos de investigación
Unidades organizativas
Puesto de trabajo
Apellidos
Rodríguez Sánchez
Nombre de pila
Ainara
Nombre
5 resultados
Resultados de la búsqueda
Mostrando 1 - 5 de 5
Publicación Nelson-Siegel Model and Multicollinearity(Springer, 2025-10-01) Rodríguez Sánchez, AinaraNelson-Siegel model is used for important decision making about monetary policy, among others. Numerous researchers are aware of the potential multicollinearity in the Nelson-Siegel model that can lead to unstable estimations and signs contrary to expectations if the model is estimated by ordinary least squares (OLS). Some authors have proposed fixing the shape parameter to avoid multicollinearity problems, but that change can lead to extremely smooth time series. On the other hand, other authors have proposed estimating the Nelson-Siegel model with the ridge regression that is traditionally applied to estimate models with collinearity as an alternative to OLS. For a correct application of the ridge regression, data should be standardized which can make difficult the interpretation of the estimated model. Also, the inference in ridge regression is controversial. Alternatively, this work proposes the application of the raise regression to mitigate multicollinearity in Nelson-Siegel model. This methodology can be applied with the original data and maintains the global characteristics of the original model. The contribution of this paper is illustrated with two different empirical examples for American and European treasuries.Publicación Obtaining a threshold for the stewart index and its extension to ridge regression(Springer , 2021) Rodríguez Sánchez, Ainara; Salmerón Gómez, Román; García García, Catalina; https://orcid.org/0000-0001-9925-9802The linear regression model is widely applied to measure the relationship between a dependent variable and a set of independent variables. When the independent variables are related to each other, it is said that the model presents collinearity. If the relationship is between the intercept and at least one of the independent variables, the collinearity is nonessential, while if the relationship is between the independent variables (excluding the intercept), the collinearity is essential. The Stewart index allows the detection of both types of near multicollinearity. However, to the best of our knowledge, there are no established thresholds for this measure from which to consider that the multicollinearity is worrying. This is the main goal of this paper, which presents a Monte Carlo simulation to relate this measure to the condition number. An additional goal of this paper is to extend the Stewart index for its application after the estimation by ridge regression that is widely applied to estimate model with multicollinearity as an alternative to ordinary least squares (OLS). This extension could be also applied to determine the appropriate value for the ridge factor.Publicación Revisiting the digital divide in Europe — The profile of those on the wrong side of the divide(ELSEVIER, 2026-04-07) Gómez Barroso, José Luis; Marbán Flores, Raquel; Rodríguez Sánchez, Ainara; Miragaya Casillas, CristinaHow deep is the digital divide in Europe today? What is the profile of those on the wrong side of the divide? This article provides answers to these two questions using data from the European Social Survey (round 10, data collected between 2020 and 2022) and conducting analyses using a probit regression model. It concludes that the digital divide, including the access divide, remains a problem in Europe. The prototype of the offline European would be someone who is not young, has little or no education, lives alone in a rural area, perceives their situation as financially difficult, is somewhat socially isolated, and has doubts about the benefits of communication. The profile of the person affected by the skills divide is not very different from that described above, although with some nuances: while women are less affected by the access divide, they are more affected by the skills divide; the larger the household size, the greater the likelihood of having lower digital proficiency; those “in education” are more skilled; capabilities increase with the number of hours spent in front of the screen.Publicación Enlarging of the Sample to Address Multicollinearity(Springer, 2025-04-16) Salmerón-Gómez, Román; García-García, Catalina Beatriz; Rodríguez Sánchez, AinaraThis paper analyzes the impact of sample enlargement on the mitigation of collinearity, concluding that it may mitigate the consequences of collinearity related to statistical analysis but not necessarily the numerical instability. This issue is important in teaching social sciences as it relates to one widely accepted solution for addressing multicollinearity. For a better understanding and illustration of the contribution made by this paper, two empirical examples and two simulations are presented and not highly technical developments are used.Publicación Estimating Ultra Long-Term Interest Rates with Raise Regression(Springer, 2026-01-16) Rodríguez Sánchez, Ainara; Zhang, Hairui; Ceuster, Marc J.K. De; Annaert, Jan; Consejería de Economía, Conocimiento, Empresas y Universidades de la Junta de AndalucíaAccurate estimation of ultra-long-term interest rates is essential for financial regulators, life insurance companies, and pension funds. The Nelson-Siegel model and its extension, the Svensson model, are widely used thanks to their parsimony and rich economic intuition. The level parameter in both models is a direct indicator of ultra-long-term rates. However, these models are subject to high nonlinearity when estimated as nonlinear models, or multicollinearity when estimated as linear models. As a result, estimated interest rates can be unstable, which undermines their practical use. In this paper, we employ raise regression to alleviate the estimation issue. Our results demonstrate superior accuracy compared to existing methods.