Teacher Effectiveness and Policy Designs on Teachers' Labor Market
The effectiveness of teachers has been a focal point of many educational policies, such as teacher accountability policies, teacher performance pay schemes, and measures to recruit and retain effective teachers in schools with more disadvantaged students. A major complication for successfully implementing these policies is the fact that teacher effectiveness is not easily observable. This project first examines how providing more transparent information about teacher effectiveness may affect teacher-school sorting patterns and the achievement of students from different backgrounds. Then, the project investigates how to improve the design of policies, such as teacher performance pay schemes, when teacher effectiveness becomes transparent information.
By exploiting the differential implementation timing of a rigorous teacher evaluation system and a merit pay system in a large school district, as well as changes in specific components of each policy over time, this project first analyzes how teacher sorting across schools, teacher effort, and student outcomes responds to these policy changes. Reducing information friction may, on the one hand, enhance assortative teacher-school sorting and widen the achievement gap across schools with different compositions of students. On the other hand, it may induce teachers to exert more effort and encourage effective teachers to enter the market. Therefore, it is possible to improve both overall student achievement and educational equality with well-designed policy interventions. The second part of this project builds and estimates an equilibrium model of the teachers’ labor market with information friction, exploiting policy variation for identification. The estimated model is used to study counterfactual policy interventions that are supplemented with teacher evaluation programs, such as the design of a cost-effective merit pay system that rewards teachers for being effective and for teaching in disadvantaged schools.
Supported by the National Science Foundation grant #1947674
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