How Did It Get This Way? Disentangling Sources of Teacher Quality Gaps Across Two States

• In Event: The Effects of District Human Resource Policies for Schools, Teachers, and Students

Abstract

1.Objectives or purposes

We study the extent to which three different processes—the hiring of new teachers into open teaching positions, the movement of teachers between schools and districts, and the attrition of teachers from different types of schools—contribute to teacher quality gaps (TQGs) between advantaged and disadvantaged schools.

2.Perspective(s) or theoretical framework

There is mounting descriptive evidence of substantial TQGs in U.S. public schools. Recent evidence from longitudinal data on public schools from North Carolina and Washington (Goldhaber, Quince, & Theobald, 2016) demonstrates that TQGs have existed in every available year of data in each state and for each observable measure of student disadvantage (i.e., race/ethnicity and poverty level) and teacher quality (i.e., experience, licensure test scores, and value added). All three processes discussed above have been well-studied in the teacher labor market literature, but we do not know how important each process is in contributing to TQGs.

3.Methods, techniques, or modes of inquiry

To disentangle the contribution of each of these processes to overall TQGs, we adopt a three-stage empirical approach. First, we estimate the relationships between different measures of teacher quality (experience, licensure test scores, and value added) and the probability that teachers are hired into, move between, or leave schools that serve different percentages of disadvantaged students (measured by race/ethnicity and poverty level). Second, we develop a dynamic model of the evolution of TQGs that is a function of all three processes described above and builds on a simpler model described in detail in Goldhaber, Lavery, and Theobald (2016). Finally, we use the estimated relationships from step 1 and the dynamic model developed in step 2 to quantify the contribution of each process to overall TQGs through simulations described in Goldhaber et al. (2016).

4.Data sources, evidence, objects, or materials

We use longitudinal data on students, teachers, and schools from two focal states—North Carolina and Washington—in which each measure of teacher quality (experience, licensure test scores, and value added) and student disadvantage (race and poverty level) is available for a long time panel.

5.Results and/or substantiated conclusions or warrants for arguments/point of view

Preliminary results suggests that all three processes contribute to TQGs between advantaged and disadvantaged schools, though the relative importance of each process varies by measure of teacher quality. Specifically, patterns in teacher mobility and attrition are particularly important in explaining TQGs by teacher experience and value added, while patterns in teacher hiring explain most of the observable TQGs by teacher licensure test scores.

6. Scientific or scholarly significance of the study or work

Final results from this study will inform the process that policymakers should seek to influence to close TQGs. For example, if patterns in teacher hiring explain most of the TQGs, policymakers could develop recruitment policies to attract high-quality teachers to disadvantaged schools. But if patterns in teacher attrition drive the observed inequities, policymakers may wish to focus on retention policies designed to keep high-quality teachers in disadvantaged schools.

Authors

• Dan Goldhaber, American Institutes for Research

• Vanessa Quince, University of Washington

• Roddy Theobald, American Institutes for Research