论文标题
线性多维回归具有交互式固定效应
Linear Multidimensional Regression with Interactive Fixed-Effects
论文作者
论文摘要
本文研究了一个线性模型，用于具有未观察到的交互式固定效应的三个或更多维度的多维面板数据。主估计器使用双重DEBIAS方法，需要两个初步步骤。首先，该模型嵌入在二维面板框架中，其中Bai（2009）中的因子模型方法导致估计值一致但缓慢地收敛。第二步开发了加权 - 与多维固定效果的强大变化，并达到了一致性的参数速率。这与渐近正常估计值的双重性交程序相结合。实施这些方法以估计啤酒的需求弹性。
This paper studies a linear model for multidimensional panel data of three or more dimensions with unobserved interactive fixed-effects. The main estimator uses double debias methods, and requires two preliminary steps. First, the model is embedded within a two-dimensional panel framework where factor model methods in Bai (2009) lead to consistent, but slowly converging, estimates. The second step develops a weighted-within transformation that is robust to multidimensional interactive fixed-effects and achieves the parametric rate of consistency. This is combined with a double debias procedure for asymptotically normal estimates. The methods are implemented to estimate the demand elasticity for beer.
