Bounds on Causal Effects and Application to High Dimensional Data

@inproceedings{Li2022BoundsOC,
  title={Bounds on Causal Effects and Application to High Dimensional Data},
  author={Ang Li and Judea Pearl},
  booktitle={AAAI},
  year={2022}
}
  • Ang Li, J. Pearl
  • Published in AAAI 23 June 2021
  • Computer Science, Economics
This paper addresses the problem of estimating causal effects when adjustment variables in the back-door or front-door criterion are partially observed. For such scenarios, we derive bounds on the causal effects by solving two non-linear optimization problems, and demonstrate that the bounds are sufficient. Using this optimization method, we propose a framework for dimensionality reduction that allows one to trade bias for estimation power, and demonstrate its performance using simulation… 

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