Nonlinearity in Dynamic Causal Effects: Making the Bad into the Good, and the Good into the Great?

This paper was prepared as a comment on "Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly" by Michal Kolesár, Mikkel Plagborg-Møller. We make three comments, including a novel contribution to the literature, showing how a reasonable economic interpretation can potentially be restored for average-effect estimators with negative weights.<br/>

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Publication Details

Journal
Journal of Business and Economic Statistics
Published
2025-10-02
DOI
https://doi.org/10.1080/07350015.2025.2529327
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
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article

Nonlinearity in Dynamic Causal Effects: Making the Bad into the Good, and the Good into the Great?

Ning Wang, Toru Kitagawa, Mengshan Xu
Journal of Business and Economic Statistics
Advanced Causal Inference Techniques
article

Nonlinearity in Dynamic Causal Effects: Making the Bad into the Good, and the Good into the Great?

Ning Wang, Toru Kitagawa, Mengshan Xu
article en

Abstract

This paper was prepared as a comment on "Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly" by Michal Kolesár, Mikkel Plagborg-Møller. We make three comments, including a novel contribution to the literature, showing how a reasonable economic interpretation can potentially be restored for average-effect estimators with negative weights.<br/>

Journal of Business and Economic StatisticsVol. 43(4)
John Brown University (US), University of Mannheim (DE), University of Bristol (GB)
Openalex Percentile: Top 68%
Advanced Causal Inference Techniques
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