In this paper, we develop spectral and post-spectral estimators for grouped panel data models. Both estimators are consistent in the asymptotics where the number of observations $N$ and the number of time periods $T$ simultaneously grow large. In addition, the post-spectral estimator is $\sqrt{NT}$-consistent and asymptotically normal with mean zero under the assumption of well-separated groups even if $T$ is growing much slower than $N$. The post-spectral estimator has, therefore, theoretical properties that are comparable to those of the grouped fixed-effect estimator developed by Bonhomme and Manresa (2015). In contrast to the grouped fixed-effect estimator, however, our post-spectral estimator is computationally straightforward.
翻译:在本文中,我们为分组小组数据模型开发了光谱和光谱后测算器。在观测数量为N美元和时间周期数同时大幅增长的情况下,这两个测算器都是一致的。此外,后光谱测算器是连续和无间断的,在精密分离组的假设下平均为零,即使美元比美元低得多。因此,光谱后测算器的理论属性与Bonhomme和Manresa(2015年)开发的集成固定效应测算器的理论属性相似。然而,与组合固定效应测算器相比,我们的光谱后测算器是直截了当的。