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.

We estimate a matching model of teachers and elementary schools with rich data on teachers' applications and principals' ratings from a large, urban district in North Carolina. Both teachers’ and principals’ preferences deviate from those that would maximize the achievement of economically disadvantaged students: teachers prefer schools with fewer disadvantaged students, and principals' ratings are weakly related to teacher effectiveness. In equilibrium, these two deviations combine to produce a surprisingly equitable current allocation, where teacher quality is balanced across advantaged and disadvantaged students. To close achievement gaps, policies that address deviations on one side alone are ineffective or harmful, while policies that address both could substantially increase the achievement of disadvantaged students.