Skip to main content
SearchLogin or Signup

Individualized Decision-Making Under Partial Identification: Three Perspectives, Two Optimality Results, and One Paradox

Forthcoming in August; Now Available: Just Accepted version

Published onJun 17, 2021
Individualized Decision-Making Under Partial Identification: Three Perspectives, Two Optimality Results, and One Paradox
·

Abstract

Unmeasured confounding is a threat to causal inference and gives rise to bi-ased estimates. In this paper, we consider the problem of individualized decision making under partial identification. Firstly, we argue that when faced with unmeasured con-founding, one should pursue individualized decision making using partial identification in a comprehensive manner. We establish a formal link between individualized decision making under partial identification and classical decision theory by considering a lower bound perspective of value/utility function. Secondly, building on this unified framework, we provide a novel minimax solution (i.e., a rule that minimizes the maximum regret for so-called opportunists) for individualized decision making/policy assignment. Lastly, we provide an interesting paradox drawing on novel connections between two challenging domains, i.e., individualized decision making and unmeasured confounding. Although motivated by instrumental variable bounds, we emphasize that the general framework proposed in this paper would in principle apply for a rich set of bounds that might be available under partial identification.

Just Accepted - Preview

6/17/21: To preview this content, click below for the Just Accepted version of the article. This peer-reviewed version has been accepted for its content and is currently being copyedited to conform with HDSR’s style and formatting requirements.

Comments
0
comment

No comments here