Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866917383270039552 |
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| author | Kurbucz, Marcell T. Garrido, Betsabé Pérez Jakovác, Antal |
| author_facet | Kurbucz, Marcell T. Garrido, Betsabé Pérez Jakovác, Antal |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05297 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models Kurbucz, Marcell T. Garrido, Betsabé Pérez Jakovác, Antal Methodology Econometrics Applications Computation 62H25, 15B52, 62M10 G.3; I.6.4 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. |
| title | Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models |
| topic | Methodology Econometrics Applications Computation 62H25, 15B52, 62M10 G.3; I.6.4 |
| url | https://arxiv.org/abs/2504.05297 |