Testing the Exclusion Restriction in IV Models Using Non-Gaussianity: A LiNGAM-Based Approach
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866912965846892544 |
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| author | Delbianco, Fernando |
| author_facet | Delbianco, Fernando |
| contents | Instrumental variable (IV) methods rely critically on the exclusion restriction, which is untestable in exactly-identified models under standard assumptions. We propose a framework combining IV analysis with the LiNGAM method to test this restriction by exploiting non-Gaussianity in the data. Under non-Gaussian structural errors, the exclusion violation parameter is point-identified without additional instruments. Five complementary tests (bootstrap percentile, asymptotic normal, permutation, likelihood ratio, and independence-based) are introduced to assess the restriction under varying data conditions. Monte Carlo simulations and an empirical application to the Card (1995) dataset demonstrate controlled Type I error rates and reasonable power against economically relevant violations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_13505 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Testing the Exclusion Restriction in IV Models Using Non-Gaussianity: A LiNGAM-Based Approach Delbianco, Fernando Econometrics Instrumental variable (IV) methods rely critically on the exclusion restriction, which is untestable in exactly-identified models under standard assumptions. We propose a framework combining IV analysis with the LiNGAM method to test this restriction by exploiting non-Gaussianity in the data. Under non-Gaussian structural errors, the exclusion violation parameter is point-identified without additional instruments. Five complementary tests (bootstrap percentile, asymptotic normal, permutation, likelihood ratio, and independence-based) are introduced to assess the restriction under varying data conditions. Monte Carlo simulations and an empirical application to the Card (1995) dataset demonstrate controlled Type I error rates and reasonable power against economically relevant violations. |
| title | Testing the Exclusion Restriction in IV Models Using Non-Gaussianity: A LiNGAM-Based Approach |
| topic | Econometrics |
| url | https://arxiv.org/abs/2603.13505 |