Doubly Robust Adaptive Conformal Inference for Causal Effects Under Temporal Dependence

Koukorinis, Andreas, Silva, Ricardo

arXiv.org Machine Learning 

We propose doubly robust adaptive conformal inference (DR-ACI), which constructs prediction intervals for doubly robust pseudo-outcomes under temporal dependence. Calibration targets the pseudo-outcome ψDRt; under estimator consistency, this yields asymptotically conservative CATE containment (Corollary 6). Temporal block cross-fitting preserves switch-coefficient mixing bounds and the DML product-bias rate up to an explicit coupling remainder.

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