Work

Enlarging of the Sample to Address Multicollinearity

Year: 2025

Type: article

Abstract: This 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.

Source: Computational Economics

DOI: 10.1007/s10614-025-10920-5

Authors: Román Salmerón-Gómez, Catalina Beatriz García-García, Ainara Rodríguez-Sánchez

Institutions: Universidad de Granada, Universidad Nacional de Educación a Distancia

Language: English

Topic: Advanced Statistical Methods and Models

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,290

Funder: Universidad Nacional de Educación a Distancia