这是一种基于渐进理论的估计结果，适合T比较大的情况，在这种情况下对各种异方差和自相关情况具有良好的稳健性，而大N小T慎用(国内的数据恰恰这种情况居多)。

太谢谢您的回答~
想再打扰您下，我是55家公司5年数据，能够使用xtscc吗？

可以作为一种备用方法一并列上回归结果。

你说的适用于“大T小N”刚好和连玉君在其辅导资料中说的适用于“大N小T”相反。刚才help 了一下xtscc，似乎不太适用的是那些T过于小的样本。如果T也大，那么N无穷大应该也是适用的。 “The error structure is assumed to be heteroskedastic, autocorrelated up to some lag and possibly correlated between the groups (panels). These standard errors are robust to general forms of cross-sectional (spatial) and temporal dependence when the time dimension becomes large. Because this nonparametric technique of estimating standard errors places no restrictions on the limiting behavior of the number of panels, the size of the cross-sectional dimension in finite samples does not constitute a constraint on feasibility -- even if the number of panels is much larger than T.  Nevertheless, because the estimator is based on an asymptotic theory, one should be somewhat cautious with applying this estimator to panels that contain a large cross-section but only a short time dimension.”

适用于heteroskedasticity、autocorrelation与cross section dependence这三个问题存在的panel data，而你在xtreg fe后还要进行是否存在这三个问题的检定，检定结果如果没有cross section dependence的话，用xtscc得出的系数是inefficient的，那么应该用xtgls或者xtpcse法