#causal inference
45 papers match
A Mathematical Framework for Topological Causal Data Analysis
Hugo Gobato Souto, Ioannis Diamantis
The paper proposes a mathematical framework called Topological Causal Data Analysis (TCDA) that integrates topological representations with causal inference, providing identificati…
Multi-channel Uplift Policy Learning
Changjian Liu, Tianyu Wang, Xiaoxuan Deng +7
The paper proposes ReAlloc, a causal teacher‑student framework for allocating fixed marketing budgets across multiple e‑commerce channels, using unbiased local gradients and long‑t…
Linear Estimation of Structural and Causal Effects for Nonseparable Panel Data
Victor Chernozhukov, Ben Deaner, Ying Gao +2
The paper proposes linear sieve estimators with bias‑corrected ridge regressions to identify structural and causal effects in nonseparable panel data models that feature time‑varyi…
Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches
Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15
The paper discusses how to improve precision in randomized clinical trials by using covariate adjustment, comparing traditional fixed parametric methods with flexible data‑adaptive…
Doubly Robust Estimators of Quantile Treatment Effects With Semiparametric Cumulative Probability Models
Hao Wu, Chun Li, Bryan E. Shepherd
The paper proposes doubly robust semiparametric methods based on cumulative probability models to estimate quantile treatment effects and related distributional measures, providing…
Nonfundamentalness or missing information ? Evidence from causal-noncausal VARs in macro-finance
Lison Christiaens, Julien Hambuckers, Alain Hecq
The paper examines whether noncausal dynamics in macro‑finance VAR models stem from true nonfundamental behavior or from omitted common information, introducing a factor‑filtered m…