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New GMM Estimators for Dynamic Panel Data Models

机译:动态面板数据模型的新GMM估算器

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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.
机译:在动态面板数据(DPD)模型中,矩量的广义方法(GMM)估计可提供有效的估计器。但是,此效率受初始加权矩阵的选择影响。实际上,仪器的力矩矩阵的逆已被用作初始加权矩阵,这导致效率降低。因此,我们将基于GMM估计中的最佳或次优权重矩阵提出新的GMM估计器。蒙特卡洛研究表明,使用这些矩阵可以提高潜在的效率。而且,新的GMM估计器的偏差和效率比任何其他常规GMM估计器更可靠。

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