On time-varying panel data models with time-varying interactive fixed effects

Abstract

This paper introduces a time-varying (TV) panel data model with interactive fixed effects where both the coefficients and factor loadings are allowed to change smoothly over time. We propose a local version of the least squares and principal component method to estimate the TV coefficients, TV factor loadings, and common factors simultaneously. We provide a bias-corrected local least squares estimator for the TV coefficients and establish the limiting distributions and uniform convergence of the bias-corrected coefficient estimators, estimated factors, and factor loadings in the large N and large T framework. Based on the estimates, we propose three test statistics to gauge possible sources of TV features. We establish the limit null distributions and the asymptotic local power properties of our tests. Simulations are conducted to evaluate the finite sample performance of our estimates and tests. We apply our theoretical results to analyze the Phillips curve using the U.S. state-level unemployment rates and nominal wages, and document significant TV behavior in both the slope coefficient and factor loadings.