Abstract
In this paper ridge estimators are used to obtain preliminary estimates of the impulse response weights in the Box-Jenkins transfer function model. Five ridge estimators and the Equity estimator are evaluated in a Monte Carlo study covering 5000 different transfer function models. The results show that although the differences between the estimators in most cases are rather small, the Dempster et al estimator RIDGMand the estimator by Lawless and Wang are best in terms of low average and median squared deviations from the true coefficient vector. The k values by these estimators are most closely correlated with the optimal k (computed from known true values) and also give the highest frequency of lowest squared error and lowest frequency of highest squared error among the investigated estimators.