On ridge estimators for the negative binomial regression model

►Multicollinearity leads to high variance of estimated parameters of regression models. ►Using Monte Carlo simulations this is shown to hold for the negative binomial model. ►A ridge regression estimator is proposed to reduce the variance. ►Some methods of estimating the ridge parameter are suggested. ►The simulated results show that the ridge regression estimator reduces the variance.