Абстрактный

New GMM Estimators for Dynamic Panel Data Models

Ahmed H. Youssef, Ahmed A. El-sheikh, Mohamed R. Abonazel

In dynamic panel data (DPD) models, thegeneralized method of moments (GMM) estimation gives efficient estimators. However, this efficiency is affected by the choice of the initial weighting matrix. In practice, the inverse of the moment matrix of the instruments has been used as an initial weighting matrix which led to a loss of efficiency. Therefore, we will present new GMM estimators based on optimal or suboptimal weighting matrices in GMM estimation. Monte Carlo study indicates that the potential efficiency gain by using these matrices. Moreover, the bias and efficiency of the new GMM estimators are more reliable than any other conventional GMM estimators