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Dynamic panel data models have been widely used in analysing many economic relationships that are dynamic in nature and the inclusion of a lagged dependent variable among the regressors allows to characterize those dynamic relations. Generalized method of moments (GMM) that require to employ some moment conditions are frequently performed for estimating dynamic panel models. In this study, we propose an estimation procedure by adapting a weighted M-estimation in selecting tuning parameter to obtain efficient estimates for dynamic panel data models. The finite sample properties of the proposed method under various cross-sectional dimension and time dimension are illustrated by an extensive simulation study as well as a real-world example. Our records reveal that the proposed estimator outperforms the GMM estimators with lower mean squared errors under high persistency level of autoregressive parameter in dynamic panel models.