GMM estimation of linear panel data models with time-varying individual effects
GMM estimation of linear panel data models with time-varying individual effects
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DOI：
10.1016/s0304-4076(00)00083-x
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发表时间：
2001-04-01
影响因子：
6.3
通讯作者：
Schmidt, P
中科院分区：
文献类型：
--
作者：
Ahn, SC;Lee, YH;Schmidt, P
本文考虑的是面板数据模型，其中个体效应随时间变化。变异的时间模式是任意的，但对于所有个体来说都是相同的。因此，该模型允许人们控制所有个人都面临的随时间变化的不可观察因素（例如宏观经济事件）以及个人可能做出不同反应的情况。广义内估计量在对误差的强假设下是一致的。但它以通用的矩估计方法为主。这也许令人惊讶，因为广义内估计量是正态下的 MLE。评估了施加二阶矩误差假设所带来的效率增益：当回归量和效应弱相关时，效率增益是巨大的。 （三）。 2001 Elsevier Science S.A. 保留所有权利。
This paper considers models For panel data in which the individual effects vary over time. The temporal pattern of variation is arbitrary, but it is the same for all individuals. The model thus allows one to control for time-varying unobservables that are faced by all individuals (e.g., macro-economic events) and to which individuals may respond differently. A generalized within estimator is consistent under strong assumptions on the errors. but it is dominated by a generalized method of moments estimator. This is perhaps surprising, because the generalized within estimator is the MLE under normality. The efficiency gains from imposing second-moment error assumptions are evaluated: they are substantial when the regressors and effects are weakly correlated. (C). 2001 Elsevier Science S.A. All rights reserved.