2025/04/07 by Kurbucz, Marcell T., Garrido, Betsabé Pérez, Jakovác, Antal
#15B52 #62H25 #62M10 #Applications (stat.AP) #Computation (stat.CO) #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #G.3 #I.6.4 #Methodology (stat.ME)
paper · doi:10.48550/arxiv.2504.05297
This paper introduces the Eigenvalue-Based Randomness (EBR) test - a novel approach rooted in the Tracy-Widom law from random matrix theory - and applies it to the context of residual analysis in panel data models. Unlike traditional methods, which target specific issues like cross-sectional dependence or autocorrelation, the EBR test simultaneously examines multiple assumptions by analyzing the largest eigenvalue of a symmetrized residual matrix. Monte Carlo simulations demonstrate that the EBR test is particularly robust in detecting not only standard violations such as autocorrelation and linear cross-sectional dependence (CSD) but also more intricate non-linear and non-monotonic dependencies, making it a comprehensive and highly flexible tool for enhancing the reliability of panel data analyses.