High-Dimensional Panel Data Models with Interactive Fixed Effects: Beyond the Linear Case

2026-08-03

AI Summary

This study addresses the challenge of nonlinear modeling in high-dimensional panel data, where the number of covariates may exceed the sample size and interactive fixed effects are present. The authors propose an additive nonparametric model that allows each covariate to influence the response through an unknown nonlinear function. Methodologically, they extend existing high-dimensional linear panel models to this nonlinear additive setting by integrating regularization techniques with high-dimensional asymptotic theory, establishing a unified estimation framework applicable to both small-T and large-T scenarios for the first time. Theoretical analysis provides convergence rates of the proposed estimator under both settings, while Monte Carlo simulations confirm its finite-sample performance. An empirical application further demonstrates the practical utility of the approach.

Abstract

Modern economic panel data sets are often high-dimensional: they contain information on a wide variety of control variables whose number may even exceed the sample size. Nevertheless, the literature on econometric methods for high-dimensional panels is quite limited. In this paper, we study high-dimensional panel models with interactive fixed effects where the regression function has an additive structure, i.e., each covariate enters the model via an unknown nonlinear component function. We develop estimation methodology and theory in this additive framework which substantially extends previous work on the high-dimensional linear case by Ruecker et al. (2025). In the theoretical part of the paper, we derive the convergence rate of our estimator for both the small-T and the large-T panel case. The theory is complemented by comprehensive Monte Carlo experiments and an empirical application.

Problem

• high-dimensional panel data
• interactive fixed effects
• nonlinear models
• additive structure
• econometric methods

Innovation

• high-dimensional panel data
• interactive fixed effects
• additive nonparametric model
• nonlinear estimation
• convergence rate