Valid Inference on Functions of Causal Effects in the Absence of Microdata
원문 초록
Economists are often interested in functions of multiple causal effects, a leading example of which is evaluating a policy's cost-effectiveness. The benefits and costs might be captured by multiple causal effects and aggregated into a scalar measure of cost-effectiveness. Oftentimes, the microdata underlying these estimates is inaccessible; only published estimates and their corresponding standard errors are available. We provide a method to conduct inference on non-linear functions of causal effects when the only information available is the point estimates and their standard errors. We apply our method to inference for the Marginal Value of Public Funds (MVPF) of government policies.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
The kernel of graph indices for vector search
Model-Based Real-Time Pose and Sag Estimation of Overhead Power Lines Using LiDAR for Drone Inspection
PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket Conditioning
SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Employing self-supervised learning models for cross-linguistic child speech maturity classification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.