Never Too LATE: A Fully Stochastic Update to the Potential Outcome Framework
永远不晚：潜在结果框架的完全随机化更新AI 解读 ↓
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永远不晚：潜在结果框架的完全随机化更新
- 研究问题
- 当个体潜在结果表现为概率而非确定结果时，如何定义服从程度与局部处理效应，并解释通常的工具变量估计目标？
- 方法与思路
- 作者在各自的小概率空间中以伯努利参数表示随机潜在结果，借助因果贝叶斯网络分解规则连接观测量，并定义 DATE。
- 材料陈述的贡献
- 摘要称，在改写后的类似 LATE 假设下，服从程度加权平均处理效应 DATE 等于通常 IV 估计目标，经典 LATE 是确定性特例。
- 阅读关注点
- 应核对 DATE 的权重与目标人群、随机框架下各项识别假设，以及贝叶斯网络分解如何连接反事实概率与可观测分布。
- 阅读边界
- 这是 arXiv 预印本，不能据此认定已同行评审或期刊接收；摘要未列出完整假设，不能据此把所有 IV 应用都解释为已识别 DATE。
原文摘要
In the classic potential outcome framework, the local average treatment effect (LATE) and its identification via an instrumental variable are stated in a deterministic setting at the individual level: each individual has settled potential outcomes such as ``cured if treated''. Several authors have proposed working instead with \emph{stochastic} potential outcomes -- counterfactual probabilities of the form ``the chance of being cured if treated'' -- but the integration of stochastic potential outcomes with the LATE machinery raises an issue. It is a metaphysical issue: in a stochastic setting, the standard joint-probability definitions of compliers and the LATE assume what I will call the \emph{unique-parallel-universe view}, which asserts that, in any genuinely possible state of the world, every counterfactual condition settles a unique determinate outcome even when the underlying causal disposition is irreducibly chancy. The statistician Dawid (2000) doubts the plausibility of this view; the philosopher Lewis (1973) develops a reductio argument against it. I propose a fully stochastic update to the Rubin causal model that drops the assumption of the unique-parallel-universe view: stochastic potential outcomes are introduced as Bernoulli parameters in their own (small) probability spaces, and are connected to observables via the factorization rule of a causal Bayes net. Within this framework, I define a Degree-of-compliance-weighted Average Treatment Effect (DATE) and prove that, under assumptions analogous to those used for the LATE but rewritten for the fully stochastic setting, the DATE equals the usual IV estimand. The classic LATE identification result emerges as a deterministic special case. Existing IV practice can therefore be reinterpreted: it has been estimating the DATE all along, in a general stochastic setting, without assuming the unique-parallel-universe view.