Measuring Returns to Experience Using Supervisor Ratings of Observed Performance: The Case of Classroom Teachers

Working Paper: NBER ID: w30888

Authors: Courtney A. Bell; Jessalynn K. James; Eric S. Taylor; James Wyckoff

Abstract: We study the returns to experience in teaching, estimated using supervisor ratings from classroom observations. We describe the assumptions required to interpret changes in observation ratings over time as the causal effect of experience on performance. We compare two difference-in-differences strategies: the two-way fixed effects estimator common in the literature, and an alternative which avoids potential bias arising from effect heterogeneity. Using data from Tennessee and Washington, DC, we show empirical tests relevant to assessing the identifying assumptions and substantive threats—e.g., leniency bias, manipulation, changes in incentives or job assignments—and find our estimates are robust to several threats.

Keywords: returns to experience; teacher performance; classroom observations; causal inference

JEL Codes: I20; J24; M50


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Teaching Experience (A29)Performance Ratings (G24)
Change in Observation Ratings (C29)Teaching Experience (A29)
Veteran Comparison Teachers (J45)Returns to Experience (Y60)
True Performance Mapping (C59)Years of Experience (C41)
Leniency Bias (D91)Performance Ratings (G24)
Changes in Observation Rubrics (C90)Performance Ratings (G24)

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