Causal Inference in Economics papers, 2023–2026

Key findings

• Causal Inference in Economics fell from 130 papers in 2023 to 27 in 2026, so interest is cooling.
• NeurIPS publishes the most Causal Inference in Economics work: 117 papers from 2023 to 2026, 64% of the four-venue total.
• The fastest-growing overlap is with Reinforcement Learning: papers tagged with both rose from 12 in 2023 to 10 in 2026.
• Among the 5 topics under Finance and Economics, it ranks #2 by 2026 paper count; the fastest grower in the group, Macro Forecasting, is up 8.0x versus 0.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Characterizing Underrepresentation in Generalizing Causal Survival Estimates
• ICML 2026Independent Component Discovery in Temporal Count Data
• ICLR 2026Ice Cream Doesn’t Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference
• CVPR 2026COPO Causal-Oriented Policy Optimization for Hallucinations of MLLMs
• NeurIPS 2025Causal Explanation-Guided Learning for Organ Allocation
• ICML 2025Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
• ICLR 2025Incremental Causal Effect for Time to Treatment Initialization
• NeurIPS 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
• ICML 2024Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness
• ICLR 2024Learning in reverse causal strategic environments with ramifications on two sided markets
• NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
• ICML 2023B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding
• ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
• CVPR 2023ECON: Explicit Clothed Humans Optimized via Normal Integration
• NeurIPS 2026Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
• ICML 2026Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
• ICLR 2026Foundation Models for Causal Inference via Prior-Data Fitted Networks
• NeurIPS 2025Pessimistic Data Integration for Policy Evaluation
• ICML 2025Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
• ICLR 2025Efficient Causal Decision Making with One-sided Feedback

All Causal Inference in Economics papers

117 papers, page 1 of 3

1. NeurIPS 2026Causal Representation Learning for Generalisable Recommendation
2. NeurIPS 2026Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
3. NeurIPS 2026Characterizing Underrepresentation in Generalizing Causal Survival Estimates
4. NeurIPS 2026Perception Without Engagement: Dissecting the Causal Discovery Deficit in LMMs
5. NeurIPS 2025A Unified Framework for the Transportability of Population-Level Causal Measures
6. NeurIPS 2025Causal Explanation-Guided Learning for Organ Allocation
7. NeurIPS 2025Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
8. NeurIPS 2025GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
9. NeurIPS 2025Pessimistic Data Integration for Policy Evaluation
10. NeurIPS 2025Treatment Effect Estimation for Optimal Decision-Making
11. NeurIPS 2024Efficient Policy Evaluation Across Multiple Different Experimental Datasets
12. NeurIPS 2024Learning Mixtures of Unknown Causal Interventions
13. NeurIPS 2024On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
14. NeurIPS 2024Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding
15. NeurIPS 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
16. NeurIPS 2023$p$-Poisson surface reconstruction in curl-free flow from point clouds
17. NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
18. NeurIPS 2023A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
19. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
20. NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
21. NeurIPS 2023Adversarial Counterfactual Environment Model Learning
22. NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
23. NeurIPS 2023Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
24. NeurIPS 2023Approximate inference of marginals using the IBIA framework
25. NeurIPS 2023Assumption violations in causal discovery and the robustness of score matching
26. NeurIPS 2023Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling
27. NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
28. NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
29. NeurIPS 2023Bounded rationality in structured density estimation
30. NeurIPS 2023C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
31. NeurIPS 2023CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
32. NeurIPS 2023Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments
33. NeurIPS 2023Causal Component Analysis
34. NeurIPS 2023Causal discovery from observational and interventional data across multiple environments
35. NeurIPS 2023Causal Discovery from Subsampled Time Series with Proxy Variables
36. NeurIPS 2023Causal Discovery in Semi-Stationary Time Series
37. NeurIPS 2023Causal Fairness for Outcome Control
38. NeurIPS 2023Causal Imitability Under Context-Specific Independence Relations
39. NeurIPS 2023Causal Interpretation of Self-Attention in Pre-Trained Transformers
40. NeurIPS 2023Causal normalizing flows: from theory to practice
41. NeurIPS 2023Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing
42. NeurIPS 2023Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
43. NeurIPS 2023Change point detection and inference in multivariate non-parametric models under mixing conditions
44. NeurIPS 2023CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
45. NeurIPS 2023Common Ground in Cooperative Communication
46. NeurIPS 2023Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
47. NeurIPS 2023Conformalized matrix completion
48. NeurIPS 2023Convex-Concave Zero-Sum Markov Stackelberg Games
49. NeurIPS 2023Counterfactual Evaluation of Peer-Review Assignment Policies
50. NeurIPS 2023Counterfactually Comparing Abstaining Classifiers

FAQ

How many Causal Inference in Economics papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

183 in total: 130 in 2023, 10 in 2024, 16 in 2025, 27 in 2026.

How many Causal Inference in Economics papers are at NeurIPS 2026?

NeurIPS 2026 has 4 Causal Inference in Economics papers, versus 6 the year before.

How many Causal Inference in Economics papers are at ICLR 2026?

ICLR 2026 has 5 Causal Inference in Economics papers, versus 4 the year before.

How many Causal Inference in Economics papers are at ICML 2026?

ICML 2026 has 17 Causal Inference in Economics papers, versus 6 the year before.

How many Causal Inference in Economics papers are at CVPR 2026?

CVPR 2026 has 1 Causal Inference in Economics papers.

Which conference publishes the most Causal Inference in Economics papers?

NeurIPS, with 117 papers from 2023 to 2026.