The zero inflated Poisson regression model is very common when analysing economic data that comes in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression estimators and some methods of estimating the ridge parameter k for the non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error (MSE) and mean absolute error (MAE) are considered as performance criterion. The simulation study shows that some estimators are better than the commonly used maximum likelihood estimator and some other ridge regression estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for the practitioners.