Possibilistic Instrumental Variable Regression
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918297658720256 |
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| author | Steiner, Gregor Houssineau, Jeremie Steel, Mark F. J. |
| author_facet | Steiner, Gregor Houssineau, Jeremie Steel, Mark F. J. |
| contents | Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in practice. In this paper, we propose a novel method based on possibility theory that performs posterior inference on the treatment effect, conditional on a user-specified set of potential violations of the exogeneity assumption. Our method can provide informative results even when only a single, potentially invalid, instrument is available, offering a natural and principled framework for sensitivity analysis. Simulation experiments and a real-data application indicate strong performance of the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_16029 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Possibilistic Instrumental Variable Regression Steiner, Gregor Houssineau, Jeremie Steel, Mark F. J. Methodology Econometrics Statistics Theory Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in practice. In this paper, we propose a novel method based on possibility theory that performs posterior inference on the treatment effect, conditional on a user-specified set of potential violations of the exogeneity assumption. Our method can provide informative results even when only a single, potentially invalid, instrument is available, offering a natural and principled framework for sensitivity analysis. Simulation experiments and a real-data application indicate strong performance of the proposed approach. |
| title | Possibilistic Instrumental Variable Regression |
| topic | Methodology Econometrics Statistics Theory |
| url | https://arxiv.org/abs/2511.16029 |