Panel: Using Data to Understand and Inform Teacher Hiring

Friday, November 3, 2017: 8:30 AM-10:00 AM
Water Tower (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Panel Organizers:  Kristine West, St. Catherine University
Panel Chairs:  Aaron Sojourner, University of Minnesota
Discussants:  Dan Goldhaber, University of Washington and Jason Grissom, Vanderbilt University

Do Early-Offers Equal Better Teachers?
Kristine West, St. Catherine University, Lesley Lavery, Macalester College and Caitlyn Keo, University of Minnesota

School and Teacher Preferences: Evidence from a Multi-stage Internal Labor Market
Napat Jatusripitak, Aaron Sojourner and Elton Mykerezi, University of Minnesota

Predicting Work Outcomes Using Prehire Work History: Who Is Fit to Teach?
Sima Sajjadiani, Aaron Sojourner, John Kammeyer-Mueller and Elton Mykerezi, University of Minnesota

It is now widely recognized that teachers are the most important in school predictor of student achievement.  Given the importance of teachers in improving student achievement and other long-run life outcomes, hiring and retaining effective teachers while ensuring that the hiring process is fair and access to quality teaching is equitable should be a policy priority for school districts. There are a number of challenges to reach these goals. First, teacher effectiveness is difficult to measure with a single metric and high quality multi-faceted information is not always available to a hiring committee. Second, even if we can identify effective teachers, when given the opportunity to register preferences, they tend to sort to schools that serve relatively advantaged students. Third, school leaders must often adhere to district-directed hiring policies and timelines which themselves are often influenced by collective bargaining agreements that may advantage a teacher's seniority over measures of quality (whether they be informed by econometrics or relationships).  Although there are many challenges inherent in selecting, hiring, and retaining a diverse, high-quality teacher workforce, the research in this session will demonstrate how combining new and better data on teacher hiring with innovative econometric techniques can shed light on opportunities for school districts to improve their teacher hiring.

One paper exploits data on a district’s internal labor market (i.e. the teacher bidding process) to model the interaction of district and teacher preferences over school and applicant characteristics. A second paper combines data from external hiring records and the Bureau of Labor Statistic’s O*NET system to investigate what variables that are visible at the time of hire are correlated with later classroom effectiveness. A third paper examines the impact of a policy change that led to offers being extended to promising applicants very early in the hiring cycle in hopes of securing these potentially high quality teachers before they were hired by surrounding districts. The final paper in this session also examines teacher hiring but uses data from a different setting. This paper uses confidential data collected biennially by the Equal Employment Opportunity Commission (EEOC) to examine the impact of court mandated affirmative action programs on teacher hiring.

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