2018/12/19 by Victor Chernozhukov, Chernozhukov, Victor, Christian Hansen +5
Mathematics · #Advanced Statistical Methods and Models #FOS: Mathematics #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST) #math.ST #stat.TH
paper · pdf · doi:10.48550/arxiv.1812.08089
openalex publication_date 2018/12/19 · arxiv created 2019/09/04 · arxiv updated 2019/09/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study a panel data model with general heterogeneous effects where slopes are allowed to vary across both individuals and over time. The key dimension reduction assumption we employ is that the heterogeneous slopes can be expressed as having a factor structure so that the high-dimensional slope matrix is low-rank and can thus be estimated using low-rank regularized regression. We provide a simple multi-step estimation procedure for the heterogeneous effects. The procedure makes use of sample-splitting and orthogonalization to accommodate inference following the use of penalized low-rank estimation. We formally verify that the resulting estimator is asymptotically normal allowing simple construction of inferential statements for the individual-time-specific effects and for cross-sectional averages of these effects. We illustrate the proposed method in simulation experiments and by estimating the effect of the minimum wage on employment.