Multicollinearity is an issue in the beta regression models that causes the variance of the ML estimator to be inflated. The Liu-type estimator is an appealing shrinkage strategy for reducing the influence of the multicollinearity problem. In the beta regression model, we suggest an almost unbiased Liu-type estimator as well as a modified version of the Liu-type estimator. Using a Monte Carlo simulation study and real data illustration, we investigate the performance of the suggested estimators. According to the results, the suggested estimators can provide a considerable improvement over other competitive estimators.
