Rank-based test for slope homogeneity in high-dimensional panel data models

A large number of existing high-dimensional panel data analyses are established based on normal or nearly normal distribution assumptions, which may be not robust to severe departures of normality. Since the observed data may not follow the normal distribution in some specific applications, it is necessary to design robust tests to departures of normality. On this ground, we propose a rank-based score test for testing slope homogeneity in high-dimensional panel data regressions, where robust tests to departures of normality are still rare. Both theoretical and numerical results demonstrate the advantage of the proposed test in robustness to departures of normality.