Structural Representations and Identification of Marginal Policy Effects

2025/06/13 by Wang, Zhixin, Zhang, Yu, Zhang, Zhengyu
#Econometrics (econ.EM) #FOS: Economics and business

paper · doi:10.48550/arxiv.2506.11694

Abstract

This paper investigates the structural interpretation of the marginal policy effect (MPE) within nonseparable models. We demonstrate that, for a smooth functional of the outcome distribution, the MPE equals its functional derivative evaluated at the outcome-conditioned weighted average structural derivative. This equivalence is definitional rather than identification-based. Building on this theoretical result, we propose an alternative identification strategy for the MPE that complements existing methods.

Citations

• Unconditional Quantile Partial Effects via Conditional Quantile Regression
• Unconditional Effects of General Policy Interventions
• Unconditional Quantile Regression with High Dimensional Data
• Automatic Debiased Machine Learning of Causal and Structural Effects
• Non-separable Models with High-dimensional Data
• Locally Robust Semiparametric Estimation
• Inference on Directionally Differentiable Functions
• Nonparametric Identification in Panels using Quantiles

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• Marginal treatment effects in the absence of instrumental variables