Xtscc命令用于大N小T的数据还是大T小N的数据？

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help xtscc的结果如下，xtscc对N的数量没有具体要求？但是对于大N小T的数据使用xtscc要慎重？我们大都是大N小T，请问对于大N小T的数据有没有类似的综合性命令呢？谢谢！   



xtscc produces Driscoll and Kraay (1998) standard errors for coefficients estimated by pooled OLS/WLS or fixed-effects (within) regression. depvar is the dependent variable and
    varlist is an (optional) list of explanatory variables.

    The error structure is assumed to be heteroskedastic, autocorrelated up to some lag, and possibly correlated between the groups (panels). Driscoll-Kraay standard errors are robust to
    very general forms of cross-sectional ("spatial") and temporal dependence when the time dimension becomes large. This nonparametric technique of estimating standard errors does not
    place any restrictions on the limiting behavior of the number of panels. Consequently, 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. However, note that the estimator is based on large T asymptotics. Therefore, one should be somewhat cautious with
    applying this estimator to panel datasets with a large number of groups but a small number of observations over time.

    This implementation of Driscoll and Kraay's covariance estimator works for both, balanced and unbalanced panels, respectively. Furthermore, it is capable to handle missing values.

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关键词：xtscc coefficients observations respectively fixed-effect structure possibly produces standard general

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那段话的意思就是，如果N远大于T，使用XTSCC需要注意。