Indiana University SPEA Edward J. Bloustein School of Planning and Public Policy University of Pennsylvania AIR American University

Panel Paper: More Than Demographics: School Rankings Based on Teacher Preferences

Thursday, November 12, 2015 : 1:45 PM
Tequesta (Hyatt Regency Miami)

*Names in bold indicate Presenter

Lindsay Fox, Stanford University
This is the first paper to present a ranking of schools that is based on teachers’ revealed preferences for where they would like to teach. Using data from New York City, I rank the district’s elementary schools in each of its five boroughs. The Open Market Transfer System in New York City captures teachers’ applications to transfer schools, and I integrate the information from all of these applications to create the rankings. Similar methods have been used to rank chess players (e.g. Elo 1978) and top tier higher education institutions (Avery, Glickman, Hoxby, and Metrick 2012), but this is the first study to apply these methods to the K-12 education setting. I present baseline rankings in which school desirability is assumed to be unidimensional, and then I explore whether school desirability is multidimensional. I divide the teachers into policy-relevant subgroups based on race and a variety of measures of teacher quality including years of experience, competitiveness of their undergraduate college, their certification exam (LAST) score, and their certification pathway. I then compute the rankings separately for each type of teacher to assess whether teachers with different characteristics systematically rank schools differently.

Next, I investigate how these rankings are associated with school characteristics. Some studies have looked at the determinants of teachers’ career decisions, but most use work history data and are thus unable to separate teacher preferences from the school hiring process (notable exceptions are Boyd, Lankford, Loeb, Ronfeldt, and Wyckoff 2010 and Barbieri, Rossetti, and Sestito 2011). Using the same applications-to-transfer dataset that was used to create the rankings, I model whether a teacher applies to a specific school as a function of school characteristics. My study builds on prior literature that focuses mainly on demographic and academic features of schools by including measures of school working conditions. These items come from the New York City school surveys that are administered each year to its teachers, parents, and students. Preliminary findings generally affirm previous studies showing that teachers prefer to teach in schools with lower proportions of traditionally underserved populations. However, I examine the amount of variation in the rankings that is explained by observable school characteristics and find that there are many schools that look less attractive based on observables but that teachers rank highly. The findings from this study provide some information to schools about what drives teacher preferences but also suggests that there is a substantial amount that remains unexplained. Nonetheless, by making themselves more attractive, possibly through improvements to malleable school features such as working conditions, schools may be able to hire and retain higher quality teachers.