Entropy balancing is doubly robust
Not on the map. Why?
Abstract (arXiv)
Covariate balance is a conventional key diagnostic for methods used estimating causal effects from observational studies. Recently, there is an emerging interest in directly incorporating covariate balance in the estimation. We study a recently proposed entropy maximization method called Entropy Balancing (EB), which exactly matches the covariate moments for the different experimental groups in its optimization problem. We show EB is doubly robust with respect to linear outcome regression and logistic propensity score regression, and it reaches the asymptotic semiparametric variance bound when both regressions are correctly specified. This is surprising to us because there is no attempt to model the outcome or the treatment assignment in the original proposal of EB. Our theoretical results and simulations suggest that EB is a very appealing alternative to the conventional weighting estimators that estimate the propensity score by maximum likelihood.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jan 2015.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 3; 2023: 3; 2024: 4; 2025: 0; 2026: 1.
13 papers.
Sort:
- 2023Augmented balancing weights as linear regressioncited by 21
- 2021Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlapcited by 9
- 2021End-to-End Balancing for Causal Continuous Treatment-Effect Estimationcited by 9
- 2023Covariate balancing using the integral probability metric for causal inferencecited by 9
- 2024Debiased Collaborative Filtering with Kernel-Based Causal Balancingcited by 6
- 2022Outcome Assumptions and Duality Theory for Balancing Weightscited by 5
- 2024Differentially Private Covariate Balancing Causal Inferencecited by 5
- 2024Collaborative Heterogeneous Causal Inference Beyond Meta-analysiscited by 4
- 2024Causal Inference with Complex Treatments: A Surveycited by 3
- 2022Targeted Optimal Treatment Regime Learning Using Summary Statisticscited by 2
- 2022Estimating causal effects with optimization-based methods: A review and empirical comparisoncited by 1
- 2023Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimationcited by 0
- 2026Differentially Private Two-Stage Empirical Risk Minimization with Applications to Individualized Treatment Rule13 Feb 2026
- 2024Differentially Private Covariate Balancing Causal Inference18 Oct 2024
- 2024Causal Inference with Complex Treatments: A Survey19 Jul 2024
- 2024Debiased Collaborative Filtering with Kernel-Based Causal Balancing30 Apr 2024
- 2024Collaborative Heterogeneous Causal Inference Beyond Meta-analysis24 Apr 2024
- 2023Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimation14 Dec 2023
- 2023Covariate balancing using the integral probability metric for causal inference23 May 2023
- 2023Augmented balancing weights as linear regression27 Apr 2023
- 2022Outcome Assumptions and Duality Theory for Balancing Weights17 Mar 2022
- 2022Estimating causal effects with optimization-based methods: A review and empirical comparison28 Feb 2022
- 2022Targeted Optimal Treatment Regime Learning Using Summary Statistics17 Jan 2022
- 2021End-to-End Balancing for Causal Continuous Treatment-Effect Estimation27 Jul 2021
- 2023Augmented balancing weights as linear regressioncited by 21
- 2021Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlapcited by 9
- 2021End-to-End Balancing for Causal Continuous Treatment-Effect Estimationcited by 9
- 2023Covariate balancing using the integral probability metric for causal inferencecited by 9
- 2024Debiased Collaborative Filtering with Kernel-Based Causal Balancingcited by 6
- 2022Outcome Assumptions and Duality Theory for Balancing Weightscited by 5
- 2024Differentially Private Covariate Balancing Causal Inferencecited by 5
- 2024Collaborative Heterogeneous Causal Inference Beyond Meta-analysiscited by 4
- 2024Causal Inference with Complex Treatments: A Surveycited by 3
- 2022Targeted Optimal Treatment Regime Learning Using Summary Statisticscited by 2
- 2022Estimating causal effects with optimization-based methods: A review and empirical comparisoncited by 1
- 2023Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimationcited by 0
12 most cited of 13 All 13 (JSON)
- 2026Differentially Private Two-Stage Empirical Risk Minimization with Applications to Individualized Treatment Rule13 Feb 2026
- 2024Differentially Private Covariate Balancing Causal Inference18 Oct 2024
- 2024Causal Inference with Complex Treatments: A Survey19 Jul 2024
- 2024Debiased Collaborative Filtering with Kernel-Based Causal Balancing30 Apr 2024
- 2024Collaborative Heterogeneous Causal Inference Beyond Meta-analysis24 Apr 2024
- 2023Temporal-Spatial Entropy Balancing for Causal Continuous Treatment-Effect Estimation14 Dec 2023
- 2023Covariate balancing using the integral probability metric for causal inference23 May 2023
- 2023Augmented balancing weights as linear regression27 Apr 2023
- 2022Outcome Assumptions and Duality Theory for Balancing Weights17 Mar 2022
- 2022Estimating causal effects with optimization-based methods: A review and empirical comparison28 Feb 2022
- 2022Targeted Optimal Treatment Regime Learning Using Summary Statistics17 Jan 2022
- 2021End-to-End Balancing for Causal Continuous Treatment-Effect Estimation27 Jul 2021
12 newest of 13 All 13 (JSON)