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arXiv · 2209.11691

Linear Multidimensional Regression with Interactive Fixed-Effects

Hugo Freeman
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Abstract

This paper studies a linear model for multidimensional panel data of three or more dimensions with unobserved interactive fixed-effects. The main estimator uses a Neyman-orthogonal approach, 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. The estimator is shown to be asymptotically normal. The methods are implemented to estimate the demand elasticity for beer.

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Hugo Freeman. 2022-09-23. Linear Multidimensional Regression with Interactive Fixed-Effects. https://arxiv.org/abs/2209.11691

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