同论文,看了一下这篇解答
https://www.stata.com/support/faqs/statistics/between-estimator/
个人理解,between指的是between subject,个体之间,
fe是为每一组增加与变量相关的截距项[α_1,α_2,...,α_n],通常是按横截面分组,即每个时间点上的截距不一样(其实也可以按个体分组);
be则是认为每个个体的斜率不一样;例如吃饭和体重的关系,小明吃一斤胖一斤,小红吃一斤可能胖十斤。
re则是假设上述个体效应、时间效应都是不相关的,随机的,为系数(包括截距、斜率)添加与独立分布的随机项ε_i,类似β_1+ε_1, α+ε_0,既然是随机项那就不能提取出来,其实就是假设系数对每个个体来说一样,那么如果做fe、be回归,得到的结果应该没有显著区别;
所以说re是假设fe的结果==be结果(并不是假设fe==be)后,对fe和be的混合:“The random-effects estimator, it turns out, is a matrix-weighted average of those two results. Under the assumption that b1 really does have the same effect in the cross-section as in the time-series—and that b2, b3, ... work the same way—we can pool these two sources of information to get a more efficient estimator.”
非计量专业,理解有错误请一定指正……


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