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Doubly Robust Identification of Causal Effects of a Continuous Treatment using Discrete Instruments
An alternative approach is to explore distributional changes in the treatment, where the first-stage restriction is treatment rank similarity.
Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data
While most treatment evaluations focus on binary interventions, a growing literature also considers continuously distributed treatments.
Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments
Utilizing a kernel-based doubly robust moment function and cross-fitting, we give high-level conditions under which the nuisance function estimators do not affect the first-order large sample distribution of the DML estimators.
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