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

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Bibliographic Details
Title: Measuring Returns to Experience Using Supervisor Ratings of Observed Performance: The Case of Classroom Teachers
Language: English
Authors: Courtney Bell, Jessalynn James (ORCID 0000-0001-6765-2642), Eric S. Taylor, James Wyckoff
Source: Journal of Policy Analysis and Management. 2025 44(1):12-44.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 33
Publication Date: 2025
Document Type: Journal Articles
Reports - Evaluative
Descriptors: Lesson Observation Criteria, Teaching Experience, Teacher Evaluation, Supervisors, Supervisory Methods, Teachers, Statistical Bias, Test Reliability, Context Effect, Robustness (Statistics)
Geographic Terms: Tennessee, District of Columbia
DOI: 10.1002/pam.22584
ISSN: 0276-8739
1520-6688
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.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1456394
Database: ERIC
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Description
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.
ISSN:0276-8739
1520-6688
DOI:10.1002/pam.22584