Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915639003709440 |
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| author | Hué, Sullivan Laurent, Sébastien Aiounou, Ulrich Flachaire, Emmanuel |
| author_facet | Hué, Sullivan Laurent, Sébastien Aiounou, Ulrich Flachaire, Emmanuel |
| contents | Post-Double-Lasso is becoming the most popular method for estimating linear regression models with many covariates when the purpose is to obtain an accurate estimate of a parameter of interest, such as an average treatment effect. However, this method can suffer from substantial omitted variable bias in finite sample. We propose a new method called Post-Double-Autometrics, which is based on Autometrics, and show that this method outperforms Post-Double-Lasso. Its use in a standard application of economic growth sheds new light on the hypothesis of convergence from poor to rich economies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_21257 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso Hué, Sullivan Laurent, Sébastien Aiounou, Ulrich Flachaire, Emmanuel Econometrics Machine Learning Post-Double-Lasso is becoming the most popular method for estimating linear regression models with many covariates when the purpose is to obtain an accurate estimate of a parameter of interest, such as an average treatment effect. However, this method can suffer from substantial omitted variable bias in finite sample. We propose a new method called Post-Double-Autometrics, which is based on Autometrics, and show that this method outperforms Post-Double-Lasso. Its use in a standard application of economic growth sheds new light on the hypothesis of convergence from poor to rich economies. |
| title | Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso |
| topic | Econometrics Machine Learning |
| url | https://arxiv.org/abs/2511.21257 |