发表机构
Toyo University（东洋大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究在固定效应模型中刻画面板条件作用的识别特征，证明双向固定效应吸收未识别方向，并提出基于任期指标的双向回归纠正偏差，通过模拟和实证数据验证。
AI 中文摘要
面板条件作用，即先前调查参与对回答的因果效应，可能随任期而变化。在时期、进入队列和任期的单元格均值加性模型下，我们刻画了交错面板在其观测支持上能识别条件作用路径的哪些特征，以及未识别部分如何影响常见的面板估计量。路径的识别集是单元格设计核的任期投影的仿射平移，路径的线性泛函恰好在其湮灭该投影时被识别。它总是包含一个仿射方向，并且当进入队列共享一个步长时，包含周期方向，在观测增量的连通性条件下这些方向穷尽该识别集；此时该步长上的二阶差分可被识别，而当步长大于1时，普通一阶差分通常不可识别。在招募条件下，中断的时间表（如当前人口调查（CPS）的四-八-四轮换）能区分每次访谈的常数增量与每个日历月的常数增量，而任何等间隔时间表都无法做到这一点。我们给出了在平台期、进入波次负对照或有界队列漂移下恢复的支持条件。第二组结果将识别与回归联系起来：双向固定效应吸收所有未识别方向，因此剩余的条件作用偏差是归一化不变的且本身可识别，而带有任期指标的双向回归在残差秩条件下纠正该偏差。当事件时间与任期对齐时，条件作用使事件研究系数偏移一个已知的路径线性泛函，从而在没有预期效应的情况下产生事前趋势；识别曲率的界约束这些偏移。模拟验证了这些恒等式，一个19波日本面板说明了支持计算，已发表的CPS月内样本指数给出了一个描述性而非识别性的例子。
英文摘要
Panel conditioning, the causal effect of prior survey participation on responses, can vary with tenure. Under an additive model of cell means in period, entry cohort, and tenure, we characterize which features of the conditioning path a staggered panel identifies on its observed support, and how the unidentified component affects common panel estimators. The identified set of the path is an affine translate of the tenure projection of the cell design's kernel, and a linear functional of the path is identified exactly when it annihilates that projection. It always contains an affine direction and, when the entry cohorts share a stride, periodic directions, which exhaust it under a connectivity condition on observed increments; second differences at that stride are then identified, and ordinary ones generally are not when the stride exceeds one. Under a recruitment condition, an interrupted schedule such as the four-eight-four rotation of the Current Population Survey (CPS) distinguishes a constant increment per interview from one per calendar month, which no equally spaced schedule can. We give support conditions for recovery under a plateau, entry-wave negative controls, or bounded cohort drift. A second set of results links identification to regression: two-way fixed effects absorb every unidentified direction, so the remaining conditioning bias is normalization-invariant and itself identified, and a two-way regression with tenure indicators corrects it under a residual-rank condition. When event time is aligned with tenure, conditioning shifts event-study coefficients by a known linear functional of the path, producing pre-trends without anticipation; bounds on identified curvature bound those shifts. Simulations verify the identities, a 19-wave Japanese panel illustrates the support calculations, and published CPS month-in-sample indices give a descriptive, not identifying, example.
Comments76 pages, 2 figures. Replication archive: https://github.com/sokubo/paper-panel-conditioning-replication (tag paper-v1.0)
