From Candidate to Classroom: Research-Based Practices for Recruiting and Hiring Highly-Effective Teachers
Category: Staffing, Finance, and Operations
Policymakers need timely, local information about teacher turnover to make informed decisions, yet turnover data are typically several years out of date and lack the context to assess whether a district's turnover is high or low relative to similar districts. We assemble district-level teacher turnover data from every state from 2003-04 to 2024-25, along with education, labor market, and economic predictors from 2000-01 to 2024-25, and use them to nowcast turnover in the current school year. We then classify each nowcasted turnover to be lower, higher, or similar to peer districts with comparable turnover trends. We can precisely and accurately classify contemporaneous turnover using pre-trends. Fewer than 1% of districts show turnover inconsistent with their classification. The nowcast also yields national estimates, with turnover rising to 14.6% in 2025-26 before declining to 13.2% in 2026-27.
Keywords
teacher turnover, nowcasting, educator labor market, national estimate, district estimate
Education level
Document Object Identifier (DOI)
10.26300/bfdg-md22
