A Model of Asymmetric Employer Learning with Testable Implications
构建了一个非对称雇主学习模型，通过工资回归检验雇主私人学习对工资的影响，发现非对称学习对工资的影响至少与公开学习相当，并解释了为何相同特征的工人工资不同。
This paper helps close the gap between theory and empirical evidence in the literature on asymmetric employer learning. If an employer's private learning is reflected in a worker's wage and one employer's private information is transmitted to the next when the worker makes a job-to-job transition, then asymmetric employer learning will appear in wage regressions as learning over an employment spell. Extending previous work that assumes all learning takes place publicly, this paper develops wage regressions that test for both asymmetric employer learning and public learning. The empirical results, including tests of alternative explanations, are consistent with asymmetric employer learning's having at least as much of an effect on wages during an employment spell as does public learning. The model developed in this paper illustrates how the story suggested by the empirical work might unfold. It shows that outside firms can profitably compete with a better-informed employer through bidding wars, even when the worker is equally productive in all firms. Furthermore, this competition results in different wages for workers with the same publicly observable characteristics, a result that previous models of asymmetric learning have not produced.