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FIXED-EFFECTS DYNAMIC PANEL MODELS, A FACTOR ANALYTICAL METHOD

机译:固定效应动态面板模型,因子分析法

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We consider the estimation of dynamic panel data models in the presence of incidental parameters in both dimensions: individual fixed-effects and time fixed-effects, as well as incidental parameters in the variances. We adopt the factor analytical approach by estimating the sample variance of individual effects rather than the effects themselves. In the presence of cross-sectional heteroskedasticity, the factor method estimates the average of the cross-sectional variances instead of the individual variances. The method thereby eliminates the incidental-parameter problem in the means and in the variances over the cross-sectional dimension. We further show that estimating the time effects and heteroskedasticities in the time dimension does not lead tothe incidental-parameter bias even when T and N are comparable. Moreover, efficient and robust estimation is obtained by jointly estimating heteroskedasticities.
机译:我们考虑在两个维度上都存在偶然参数的情况下对动态面板数据模型的估计:各个固定效应和时间固定效应,以及方差中的偶然参数。我们通过估计单个效应而不是效应本身的样本方差来采用因子分析方法。在存在横截面异方差的情况下,因子方法估计横截面方差的平均值,而不是各个方差。因此,该方法消除了均值和横截面尺寸变化中的附带参数问题。我们进一步表明,即使在T和N可比的情况下,估计时间维度中的时间效应和异方差也不会导致偶然参数偏差。而且,通过联合估计异方差性可以获得高效且鲁棒的估计。

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