Causal Inference and High-Dimensional Models

ESEM
Presenter(s) Type Length Chair
Michael Pollmann Davide Viviano Yusuke Narita Martin Huber Phillip Heiler Contributed 24/08 10:00 UTC
120
mins
Yusuke Narita

Papers

(Listed in order of presenters above)

Causal Inference for Spatial Treatments

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Policy targeting under network interference

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Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules

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Double machine learning for sample selection models

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Decomposing Causal Effect Heterogeneity under Multiple Treatment Versions

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