Uncorrelated

Labour economics

Mathematics education

Statistics

Chromatography

Social psychology

Public relations

Personnel selection

Teacher quality

Pedagogy

Scope (computer science)

Selection (genetic algorithm)

Economics

Computer science

Business

Public sector

Job satisfaction

Psychology

Mathematics

Management

Political science

Demographic economics

Operations management

Artificial intelligence

Job performance

Economy

Chemistry

Programming language

Metric (unit)

Sample (material)

Selection bias

Journal of Public Economics

Selecting more productive employees among a pool of job applicants can be a cost-effective means of improving organizational performance and may be particularly important in the public sector. We study the relationship among applicant characteristics, hiring outcomes, and job performance for teachers in the Washington DC Public Schools. Applicants' academic background (e.g., undergraduate GPA) is essentially uncorrelated with hiring. Screening measures (written assessments, interviews, and sample lessons) help applicants get jobs by placing them on a list of recommended candidates, but they are only weakly associated with the likelihood of being hired conditional on making the list. Yet both academic background and screening measures strongly predict teacher job performance, suggesting considerable scope for improving schools via the selection process.

Teacher applicant hiring and teacher performance: Evidence from DC public schools