Informational asymmetries between employers may inhibit optimal worker mobility. However, researchers rarely observe shocks to employers’ information. I exploit two school districts’ adoptions of value-added (VA) measures of teacher effectiveness—informational shocks to some, but not all, employers—to provide direct tests of asymmetric employer learning. I develop a learning model and test its predictions for teacher mobility. I find that adopting VA increases within-district mobility of high-VA teachers, while low-VA teachers move out of district to uninformed principals. These patterns are consistent with asymmetric employer learning. This sorting from widespread VA adoption exacerbates inequality in access to effective teaching.

中文翻译：

---

公共和私人雇主学习：来自采用教师增值的证据

雇主之间的信息不对称可能会阻碍工人的最佳流动。但是，研究人员很少观察到对雇主信息的冲击。我利用两个学区采用增值（VA）衡量教师效能的方法（对部分但不是全部雇主的信息冲击）来提供对不对称雇主学习的直接测试。我开发了一个学习模型，并测试了其对教师流动性的预测。我发现采用VA可以增加高VA老师在区域内的流动性，而低VA老师则从学区外移到不知情的校长。这些模式与不对称的雇主学习相一致。广泛采用VA的这种分类加剧了获得有效教学机会方面的不平等。