The Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC) is one of the most popular direct methods for linear continuous-time system identification. Only recently, some optimal asymptotic properties of this method have been proven. Here we provide a comprehensive analysis of the convergence of the SRIVC method for over-parameterized models. The results we derive are used to discuss practical aspects of the method and to analyze the behavior of the normalized error variance norm, which is a central part in Young’s Information Criterion for model order selection. The theoretical findings are validated through simulation examples.