Revisiting the statistical specification of near-multicollinearity in the logistic regression model

Bebonchu Atems () and Jason Bergtold

Studies in Nonlinear Dynamics & Econometrics, 2016, vol. 20, issue 2, 199-210

Abstract: This paper revisits the statistical specification of near-multicollinearity in the logistic regression model. We argue that the ceteris paribus clause, which assumes that the maximum likelihood estimator of β remains constant as the correlation (ρ) between the regressors increases, invoked under the traditional account of near-multicollinearity is rather misleading. We derive the parameters of the logistic regression model and show that they are functions of ρ, indicating that the ceteris paribus clause is unattainable. Monte Carlo simulations confirm these findings and further show that: coefficient estimates and related statistics fluctuate in a non-symmetric, non-monotonic way as |ρ|→1; that the impact of near-multicollinearity is centered on the estimates of β; and that the impact on substantive inferences does not necessarily follow what the traditional account implies.

Keywords: logistic regression; model diagnostics; near-multicollinearity (search for similar items in EconPapers)
JEL-codes: C1 C2 C4 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1515/snde-2013-0052

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