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Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017

arXiv 1905.09515 ↗First posted 23 May 2019stat.ME stat.OTcited by 23

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Abstract (arXiv)

This brief note documents the data generating processes used in the 2017 Data Analysis Challenge associated with the Atlantic Causal Inference Conference (ACIC). The focus of the challenge was estimation and inference for conditional average treatment effects (CATEs) in the presence of targeted selection, which leads to strong confounding. The associated data files and further plots can be found on the first author's web page.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 May 2019.

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Citing papers per year: 2021: 2; 2022: 4; 2023: 3; 2024: 6; 2025: 2; 2026: 6.

23 papers.

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  1. 2022Evaluation Methods and Measures for Causal Learning Algorithmscited by 23
  2. 2025TabPFN: One Model to Rule Them All?cited by 10
  3. 2021Generating Synthetic Text Data to Evaluate Causal Inference Methodscited by 9
  4. 2024Stabilized Inverse Probability Weighting via Isotonic Calibrationcited by 8
  5. 2022Stochastic Tree Ensembles for Estimating Heterogeneous Effectscited by 7
  6. 2022A Mixing Time Lower Bound for a Simplified Version of BARTcited by 7
  7. 2023Consistent Optimal Transport with Empirical Conditional Measurescited by 6
  8. 2021Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimatorscited by 4
  9. 2023Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimationcited by 3
  10. 2024Very fast Bayesian Additive Regression Trees on GPUcited by 2
  11. 2026DoTime: A Synthetic Benchmark Generator for Interventional and Counterfactual Time Seriescited by 2
  12. 2022Estimating causal effects with optimization-based methods: A review and empirical comparisoncited by 1
11 more
  1. 2024Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimationcited by 1
  2. 2024IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmarkcited by 1
  3. 2024Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithmcited by 1
  4. 2025A Bayesian Additive Regression Tree Model for Learning Conditional Average Treatment Effects in Regression Discontinuity Designscited by 1
  5. 2026Tailoring Strictly Proper Scoring Rules for Downstream Tasks: An Application to Causal Inferencecited by 1
  6. 2023Partially Specified Causal Simulationscited by 0
  7. 2024Identifiable Latent Bandits: Leveraging observational data for personalized decision-makingcited by 0
  8. 2026Controllable Generative Sandbox for Causal Inferencecited by 0
  9. 2026Representation Learning for Semiparametric Causal Mediation Analysis under No Essential Heterogeneitycited by 0
  10. 2026When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guidecited by 0
  11. 2026What You Observe Determines How You Identify Causal Effects: Evaluating Causal Models across Observational Viewscited by 0