Identification of non-additive fixed effects models: Is the return to teacher quality homogeneous?
非加性固定效应模型的识别:教师质量回报是否同质?AI 解读 ↓
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AI 根据所提供的论文材料归类:摘要明确讨论面板固定效应识别、处理变量交互及教师质量效应异质性。
非加性固定效应模型的识别:教师质量回报是否同质?AI 解读 ↓
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Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for parameters of interest in this model under both strict and weak exogeneity assumptions. The key identification insight is that other periods’ treatment variables are instruments for the unobserved fixed effects. We apply our proposed estimator to matched student-teacher data used to estimate value-added models of teacher quality. We show that the common assumption that the return to teacher quality is the same for all students is rejected by the data. We also present evidence that No Child Left Behind-era school accountability raised the effectiveness of teacher quality for lower performing students.