面板数据中FGLS或PCSE估计如何区别固定效应和随机效应

留念

学习了，谢谢！

路过踩一下，最近被这个整的很纠结%>_<%

rightperson 发表于 2009-10-28 21:07
厉害啊，还是连帮主厉害

难道，楼上的是传说中的那个连帮主？

执行xtpcse或xtgls命令时，如果没有个体虚拟变量，则为随机效应模型；如果加上个体虚拟变量，则为固定效应模型。

上贴也有用

对PCSE不太了解，不过看到的PCSE都是用于固定效应。FGLS一般是随机效应回归用。

A fixed group effect model examines group differences in intercepts, assuming the same slopes
and constant variance across entities or subjects. Since a group (individual specific) effect is
time invariant and considered a part of the intercept, i u is allowed to be correlated to other
regressors. Fixed effect models use least squares dummy variable (LSDV) and within effect
estimation methods. Ordinary least squares (OLS) regressions with dummies, in fact, are fixed
effect models.

A random effect model, by contrast, estimates variance components for groups (or times) and
error, assuming the same intercept and slopes. i u is a part of the errors and thus should not be
correlated to any regressor; otherwise, a core OLS assumption is violated. The difference
among groups (or time periods) lies in their variance of the error term, not in their intercepts. A
random effect model is estimated by generalized least squares (GLS) when the  matrix, a
variance structure among groups, is known. The feasible generalized least squares (FGLS)
method is used to estimate the variance structure when  is not known. A typical example is
the groupwise heteroscedastic regression model (Greene 2003). There are various estimation
methods for FGLS including the maximum likelihood method and simulation (Baltagi and
Cheng 1994).

详见Hun Myoung Park. Linear Regression Models for Panel Data Using SAS, Stata,
LIMDEP, and SPSS

mark

被这个搞死了都

受教了