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arXiv · 2504.05297

Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models

Marcell T. Kurbucz·Betsabé Pérez Garrido·Antal Jakovác
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Abstract

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.

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BibTeXRIS

Marcell T. Kurbucz, Betsabé Pérez Garrido, Antal Jakovác. 2025-04-07. Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models. https://doi.org/10.1016/j.ecosta.2026.03.002

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