Teacher Labor Supply in Chicago’s Public Schools

Mimi Engel
Vanderbilt University

While we know that disadvantaged students are more likely to be taught by less qualified teachers, we know little about whether this disparity is caused by decisions on the part of teachers or school administrators. It is difficult to parse out the extent to which the unequal distribution of teachers across schools results from supply (teachers’ preferences and decisions to apply to jobs in particular districts or schools) or demand-related factors (principals’ hiring preferences or district rules and regulations). 

A recent study that I conducted with Brian Jacob and F. Chris Curran is the first to provide evidence on prospective teachers’ revealed, as opposed to reported (survey or interview), preferences. Over the past decade, the Chicago Public Schools (CPS) Department of Human Resources has implemented a comprehensive array of events and services aimed at recruiting teachers into the district including large district-wide job fairs. We compile and analyze a unique data set that contains information on which schools prospective teachers chose to do initial interviews with at these job fairs to explore the distribution of the teacher applicant pool within a large urban district.

We find that CPS schools serving fewer disadvantaged students (as measured by the percentage of students eligible for free or reduced-price lunch) have larger numbers of initial applicants per vacancy and that this measure of disadvantage is more consistently predictive of number of applicants per vacancy than are other school demographic characteristics such as student racial/ethnic composition, academic achievement, or the percentage of students with limited English proficiency. We also find the geographic location of the school to be an important predictor of applications. Further we find that school location and proximity to candidates’ homes is very important; candidates are more likely to apply to schools that are close to where they live. In fact candidates are 40 percent less likely to apply to a school that is five kilometers—just over three miles—further from their homes.

We also find that preferences for school characteristics vary by applicant characteristics, with African American candidates more likely to apply to schools serving a larger proportion of African American students and Hispanic candidates more likely to be interested in schools serving larger concentrations of students with limited English proficiency. Finally, we find that applicants with undergraduate degrees in mathematics or science (five percent of the applicant sample) are more likely to apply to schools serving more academically proficient students. Importantly, this systematic sorting results in there being far fewer applicants to some schools than others.

The current study provides evidence that within large urban districts, the extent to which school leaders encounter staffing difficulties is likely to be highly variable. The number of applicants per school varies dramatically by school characteristics and across CPS regions. Our results indicate that district-level recruitment efforts are unlikely to provide sufficient applicants to the most geographically isolated schools and those schools that serve the largest concentrations of students from disadvantaged backgrounds.

Many schools—whether because they are situated in less geographically desirable locations, because they serve the most disadvantaged student populations, or a combination of these factors—are likely to experience a shortage of applicants.  This suggests that targeted efforts to direct a larger number of qualified applicants to hard-to-staff schools could have important benefits. 

The full study (gated) is in Mimi Engel, Brian A. Jacob and F. Chris Curran, New Evidence on Teacher Labor Supply, American Educational Research Journal, February 2014, vol. 51, no. 1, 36-72.

Suggested citationEngel, M. (2014, April). Teacher labor supply in Chicago’s public schools [Commentary]. Policy Analysis for California Education.