Research Paper#Causal Inference, Policy Evaluation, Instrumental Variables🔬 ResearchAnalyzed: Jan 3, 2026 16:49
Evaluating Counterfactual Policies with Instruments
Published:Dec 30, 2025 09:12
•1 min read
•ArXiv
Analysis
This paper addresses the problem of evaluating the impact of counterfactual policies, like changing treatment assignment, using instrumental variables. It provides a computationally efficient framework for bounding the effects of such policies, without relying on the often-restrictive monotonicity assumption. The work is significant because it offers a more robust approach to policy evaluation, especially in scenarios where traditional IV methods might be unreliable. The applications to real-world datasets (bail judges and prosecutors) further enhance the paper's practical relevance.
Key Takeaways
- •Provides a framework for evaluating counterfactual policies using instrumental variables.
- •Avoids the need for the IV monotonicity assumption.
- •Offers a computationally tractable approach for bounding policy effects.
- •Applies the framework to real-world examples (bail judges, prosecutors).
Reference
“The paper develops a general and computationally tractable framework for computing sharp bounds on the effects of counterfactual policies.”