Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators
Fuente:
arXiv
Saved in:
| Main Authors: | Klaassen, Sven, Rabenseifner, Jan, Kueck, Jannis, Bach, Philipp |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Estimation and Uniform Inference in Sparse High-Dimensional Additive Models
by: Bach, Philipp, et al.
Published: (2020)
by: Bach, Philipp, et al.
Published: (2020)
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data
by: Klaassen, Sven, et al.
Published: (2024)
by: Klaassen, Sven, et al.
Published: (2024)
Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
by: Schwarz, Philipp Alexander, et al.
Published: (2025)
by: Schwarz, Philipp Alexander, et al.
Published: (2025)
Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024)
by: Fuhr, Jonathan, et al.
Published: (2024)
Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)
by: Liu, Nan, et al.
Published: (2024)
Robust Matrix Estimation with Side Information
by: Agarwal, Anish, et al.
Published: (2026)
by: Agarwal, Anish, et al.
Published: (2026)
Sensitivity Analysis for Treatment Effects in Difference-in-Differences Models using Riesz Representation
by: Bach, Philipp, et al.
Published: (2025)
by: Bach, Philipp, et al.
Published: (2025)
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
by: Athey, Susan, et al.
Published: (2016)
by: Athey, Susan, et al.
Published: (2016)
A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
by: Singh, Aman
Published: (2026)
by: Singh, Aman
Published: (2026)
Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
by: Sert, Gözde, et al.
Published: (2025)
by: Sert, Gözde, et al.
Published: (2025)
Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation
by: Kato, Masahiro, et al.
Published: (2023)
by: Kato, Masahiro, et al.
Published: (2023)
Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study
by: Bach, Philipp, et al.
Published: (2024)
by: Bach, Philipp, et al.
Published: (2024)
Estimating the Value of Evidence-Based Decision Making
by: Abadie, Alberto, et al.
Published: (2023)
by: Abadie, Alberto, et al.
Published: (2023)
Multiply-Robust Causal Change Attribution
by: Quintas-Martinez, Victor, et al.
Published: (2024)
by: Quintas-Martinez, Victor, et al.
Published: (2024)
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)
by: Abadie, Alberto, et al.
Published: (2024)
Estimating Dyadic Treatment Effects with Unknown Confounders
by: Hoshino, Tadao, et al.
Published: (2024)
by: Hoshino, Tadao, et al.
Published: (2024)
Estimating Wage Disparities Using Foundation Models
by: Vafa, Keyon, et al.
Published: (2024)
by: Vafa, Keyon, et al.
Published: (2024)
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects
by: Ghassami, AmirEmad, et al.
Published: (2022)
by: Ghassami, AmirEmad, et al.
Published: (2022)
Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
by: Shirani, Sadegh, et al.
Published: (2025)
by: Shirani, Sadegh, et al.
Published: (2025)
Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
by: Sakaguchi, Shosei
Published: (2021)
by: Sakaguchi, Shosei
Published: (2021)
Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
by: Chen, Xiaohong, et al.
Published: (2021)
by: Chen, Xiaohong, et al.
Published: (2021)
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
by: Kato, Masahiro, et al.
Published: (2024)
by: Kato, Masahiro, et al.
Published: (2024)
Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
The Honest Truth About Causal Trees: Accuracy Limits for Heterogeneous Treatment Effect Estimation
by: Cattaneo, Matias D., et al.
Published: (2025)
by: Cattaneo, Matias D., et al.
Published: (2025)
A Note on Doubly Robust Estimator in Regression Discontinuity Designs
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
by: Adedayo, S. A.
Published: (2025)
by: Adedayo, S. A.
Published: (2025)
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Estimating Treatment Effects under Algorithmic Interference: A Structured Neural Networks Approach
by: Zhan, Ruohan, et al.
Published: (2024)
by: Zhan, Ruohan, et al.
Published: (2024)
Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs
by: Xiong, Ruoxuan, et al.
Published: (2024)
by: Xiong, Ruoxuan, et al.
Published: (2024)
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
by: Jin, Jikai, et al.
Published: (2024)
by: Jin, Jikai, et al.
Published: (2024)
xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
by: Polselli, Annalivia
Published: (2025)
by: Polselli, Annalivia
Published: (2025)
Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)
by: Arbour, David, et al.
Published: (2025)
Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring
by: Sullivan, Hué, et al.
Published: (2022)
by: Sullivan, Hué, et al.
Published: (2022)
Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
by: Ballinari, Daniele, et al.
Published: (2024)
by: Ballinari, Daniele, et al.
Published: (2024)
Data Fusion for Partial Identification of Causal Effects
by: Lanners, Quinn, et al.
Published: (2025)
by: Lanners, Quinn, et al.
Published: (2025)
Synthetic Potential Outcomes and Causal Mixture Identifiability
by: Mazaheri, Bijan, et al.
Published: (2024)
by: Mazaheri, Bijan, et al.
Published: (2024)
Applied Causal Inference Powered by ML and AI
by: Chernozhukov, Victor, et al.
Published: (2024)
by: Chernozhukov, Victor, et al.
Published: (2024)
A Causal Inference Framework for Data Rich Environments
by: Abadie, Alberto, et al.
Published: (2025)
by: Abadie, Alberto, et al.
Published: (2025)
Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Similar Items
-
Estimation and Uniform Inference in Sparse High-Dimensional Additive Models
by: Bach, Philipp, et al.
Published: (2020) -
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data
by: Klaassen, Sven, et al.
Published: (2024) -
Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
by: Schwarz, Philipp Alexander, et al.
Published: (2025) -
Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024) -
Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)