A Sensitivity Analysis of the Surrogate Index Approach for Estimating Long-Term Treatment Effects

Fuente: arXiv
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Main Authors: Fan, Yanqin, Manzanares, Carlos A., Park, Hyeonseok, Qi, Yuan
Format: Preprint
Published: 2026
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author Fan, Yanqin
Manzanares, Carlos A.
Park, Hyeonseok
Qi, Yuan
author_facet Fan, Yanqin
Manzanares, Carlos A.
Park, Hyeonseok
Qi, Yuan
contents This paper develops a sensitivity analysis of the surrogacy assumption for the surrogate index approach in Athey et al. [2025b]. We introduce "Weighted Surrogate Indices (WSIs)," the analog of the surrogate index under the surrogacy assumption. We show that under comparability, the ATE on WSI identifies the ATE on the long-term outcome when a copula of the treatment and the long-term outcome conditional on baseline covariates and surrogates is known. When the copula is unknown, we establish the identified set of the ATE on the long-term outcome. Furthermore, we construct debiased estimators of the ATE for any given copula and develop asymptotically valid inference in both point-identified and partially identified cases. Using data from a poverty alleviation program in Pakistan, we demonstrate the importance of sensitivity checks as well as the usefulness of our approach.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00580
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Sensitivity Analysis of the Surrogate Index Approach for Estimating Long-Term Treatment Effects
Fan, Yanqin
Manzanares, Carlos A.
Park, Hyeonseok
Qi, Yuan
Econometrics
This paper develops a sensitivity analysis of the surrogacy assumption for the surrogate index approach in Athey et al. [2025b]. We introduce "Weighted Surrogate Indices (WSIs)," the analog of the surrogate index under the surrogacy assumption. We show that under comparability, the ATE on WSI identifies the ATE on the long-term outcome when a copula of the treatment and the long-term outcome conditional on baseline covariates and surrogates is known. When the copula is unknown, we establish the identified set of the ATE on the long-term outcome. Furthermore, we construct debiased estimators of the ATE for any given copula and develop asymptotically valid inference in both point-identified and partially identified cases. Using data from a poverty alleviation program in Pakistan, we demonstrate the importance of sensitivity checks as well as the usefulness of our approach.
title A Sensitivity Analysis of the Surrogate Index Approach for Estimating Long-Term Treatment Effects
topic Econometrics
url https://arxiv.org/abs/2603.00580