English(EN) Regression with Many Generated Controls

新回归方法利用AI生成控制变量解决潜在内生性问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

研究人员开发了一种线性回归方法，用于在充分的控制变量潜在不可观测时解决内生性问题。该方法利用AI/ML技术生成该潜在控制变量的多个代理变量。通过纳入一组丰富的生成控制变量，该方法无需验证数据即可对感兴趣的参数进行一致估计，为实践者提供了实用建议。 AI

影响为计量经济学引入了一种新颖的统计技术，该技术利用AI/ML来改进数据分析。

排序理由该条目是发表在arXiv上的学术论文，详细介绍了一种新的统计方法。[lever_c_demoted from research: ic=1 ai=0.7]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv stat.ML TIER_1 English(EN) · Timothy Christensen, Daniel Vebman · 2026-11-05 05:00

具有多个生成控制的回归

arXiv:2611.06855v1 Announce Type: cross Abstract: We consider linear regression when some covariates are endogenous, a variable sufficient to control for endogeneity exists but is latent, and the practitioner can generate many proxies for the latent control. For instance, one cou…