mlsanityData to 14 Oct 2026

The State of Applied Econometrics - Causality and Policy Evaluation

arXiv 1607.00699 ↗First posted 3 Jul 2016stat.ME econ.EMcited by 41

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Abstract (arXiv)

In this paper we discuss recent developments in econometrics that we view as important for empirical researchers working on policy evaluation questions. We focus on three main areas, where in each case we highlight recommendations for applied work. First, we discuss new research on identification strategies in program evaluation, with particular focus on synthetic control methods, regression discontinuity, external validity, and the causal interpretation of regression methods. Second, we discuss various forms of supplementary analyses to make the identification strategies more credible. These include placebo analyses as well as sensitivity and robustness analyses. Third, we discuss recent advances in machine learning methods for causal effects. These advances include methods to adjust for differences between treated and control units in high-dimensional settings, and methods for identifying and estimating heterogeneous treatment effects.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jul 2016.

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Citing papers per year: 2021: 5; 2022: 5; 2023: 6; 2024: 2; 2025: 10; 2026: 13.

41 papers.

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  1. 2021Causal Inference for Time series Analysis: Problems, Methods and Evaluationcited by 42
  2. 2021Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matterscited by 25
  3. 2022Validating Causal Inference Methodscited by 20
  4. 2021NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatmentscited by 14
  5. 2022Synthetically Controlled Banditscited by 8
  6. 2021The Local Approach to Causal Inference under Network Interferencecited by 6
  7. 2023Emoji Promotes Developer Participation and Issue Resolution on GitHubcited by 6
  8. 2026Generative AI collective behavior needs an interactionist paradigmcited by 6
  9. 2022Counterfactuals for the Futurecited by 5
  10. 2024Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameterscited by 5
  11. 2025Preliminary suggestions for rigorous GPAI model evaluationscited by 5
  12. 2022Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performancecited by 4
29 more
  1. 2023Causal Mediation Analysis with Multi-dimensional and Indirectly Observed Mediatorscited by 4
  2. 2024Spillover Detection for Donor Selection in Synthetic Control Modelscited by 4
  3. 2026Causal Foundation Models with Continuous Treatmentscited by 4
  4. 2023Differentially Private Synthetic Controlcited by 3
  5. 2025Falsification of Unconfoundedness by Testing Independence of Causal Mechanismscited by 3
  6. 2023Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountabilitycited by 2
  7. 2025What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundednesscited by 2
  8. 2022Cryptocurrency Valuation: An Explainable AI Approachcited by 1
  9. 2025Your Assumed DAG is Wrong and Here's How To Deal With Itcited by 1
  10. 2025STOAT: Spatial-Temporal Probabilistic Causal Inference Networkcited by 1
  11. 2026Econometric vs. Causal Structure-Learning for Time-Series Policy Decisions: Evidence from the UK COVID-19 Policiescited by 1
  12. 2026Invariant Causal Routing for Governing Social Norms in Online Market Economiescited by 1
  13. 2026Causal Foundation Modelscited by 1
  14. 2021Learning Generalized Causal Structure in Time-seriescited by 0
  15. 2023Bounded (O(1)) Regret Recommendation Learning via Synthetic Controls Oraclecited by 0
  16. 2023A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learningcited by 0
  17. 2025Body Discovery of Embodied AIcited by 0
  18. 2025XplainAct: Visualization for Personalized Intervention Insightscited by 0
  19. 2025Graph Distance Based on Cause-Effect Estimands with Latentscited by 0
  20. 2025Unbiased Platform-Level Causal Estimation for Search Systems: A Competitive Isolation PSM-DID Frameworkcited by 0
  21. 2025Counterfactual Forecasting of Human Behavior using Generative AI and Causal Graphscited by 0
  22. 2026Causal Discovery as Dialectical Aggregation: A Quantitative Argumentation Frameworkcited by 0
  23. 2026Trading Human Curation for Synthetic Augmentation in RLVRcited by 0
  24. 2026From Correlation to Causation in Lane Change Prediction for Automated Driving: A Causal Explanation Frameworkcited by 0
  25. 2026From Tokens to Policy: Causal and Interpretable Heterogeneous Treatment Effects Identificationcited by 0
  26. 2026A Survey on Federated Causal Discovery and Inferencecited by 0
  27. 2026Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSScited by 0
  28. 2026Counterfactual Optimal Action Trees (COAT): Interpretable Prescriptive Policies from Observational Datacited by 0
  29. 2026Evidence-Grounded Auditing of Identification Assumptions in Climate-Policy Causal Evaluationscited by 0