Haruo KAKEHI

Publication

with Masahiro Kato, Masaaki Imaizumi, Kenichiro McAlinn, and Shota Yasui

International Conference on Learning Representations (ICLR) 2022  [arxiv] [OpenReview] 

[Abstract] We consider learning causal relationships under conditional moment restrictions. Unlike causal inference under unconditional moment restrictions, conditional moment restrictions pose serious challenges for causal inference. To address this issue, we propose a method that transforms conditional moment restrictions to unconditional moment restrictions through importance weighting using a conditional density ratio estimator. Then, using this transformation, we propose a method that successfully estimate a parametric or nonparametric functions defined under the conditional moment restrictions. We analyze the estimation error and provide a bound on the structural function, providing theoretical support for our proposed method. In experiments, we confirm the soundness of our proposed method. 

Working Paper

with Taisuke Otsu

with Yoko Ibuka, Ryuki Kobayashi, and Ryo Nakajima 

with Ryo Nakajima