Introduction

Recent research has established that teachers matter for student achievements (Rivkin, Hanushek, Kain, 2005, Rothstein, 2010, Chetty, Friedman, Rockoff, 2014, Chetty, Friedman, Rockoff, 2014, etc.). On the basis of this evidence, policy in the US has, sometimes controversially, moved towards hiring and firing teachers on the basis of measurable impacts on student test scores (see for example, discussion in Hanushek, 2009, Thomsen, 2014, Rothstein, 2015, Adnot, Dee, Katz, Wyckoff, 2017). Teacher turnover has potential benefits (e.g. James and Wyckoff 2020) because it is the mechanism by which teachers gain a variety of experience, new ideas and talents are brought into schools, and productive teacher-school matches are formed. However, there are also potential costs for students and schools when teachers move: leavers take school-specific knowledge and experience with them, new arrivals may need extra training, they take time to assimilate and gain much needed school-specific human capital, and there are also administrative costs imposed by turnover. The overall presumption amongst policymakers is that teacher turnover has, on average, adverse impacts on student performance. Turnover of teachers is also a perennial concern for parents, particularly when it occurs during the period when students are studying for important exams. However, despite the popular importance of this issue, there are relatively very few quality studies that investigate it empirically, the recent exceptions being: Ronfeldt et al. (2013), Hanushek et al. (2016), Atteberry et al. (2017). There are even fewer studies that investigate the potential channels through which turnover may be disruptive or examine organisational responses to mitigate potential negative effects of turnover. The lack of quality data has made the task of investigating turnover and performance in education, and more generally in the public sector, challenging.

Our analysis of teacher turnover is based on a unique dataset that links the teacher workforce in England to students’ achievement records, by school and teaching subject categories, over five cohorts. Using these data, we investigate the effects of teacher entry into schools on the final qualifications of students in the subjects taught by those teachers. The paper contributes to the literature in a number of ways: we improve on the rather limited existing international evidence on the causal impact of teacher turnover, investigate potential mechanisms through which turnover can affect student performance, and provide evidence on how schools respond to mitigate the disruption effects of turnover.

Our first key finding is that students experiencing high teacher turnover do less well in their end-of-school exams. The effects are small, though non-negligible relative to other factors that have been found to affect student achievement. A 10 percentage points increase in teacher annual entry rate reduces student point scores in their GCSE exam (the standardized test at the end of secondary school) by around 0.5% of one standard deviation. Hence, a standard deviation change in entry rate (14%) leads to a standardised effect size of 0.8% of a standard deviation. This result is similar to that found in studies of teacher turnover in the US (e.g. Ronfeldt, Loeb, Wyckoff, 2013, Hanushek, Rivkin, Schiman, 2016). Students in the middle of the ability distribution, proxied by primary school grades, are the ones most affected by turnover.1 Examining potential mechanisms through which turnover affects achievement, we show that it is new teachers’ lack of school-specific human capital that matters. General teaching experience does not play a role (in contrast to the findings in Hanushek et al. 2016). Other channels, such as changes in teacher quality, or other teacher characteristics, do not seem to play a role either. We also find that schools do respond to mitigate the negative effects of turnover: new teachers, particularly if they are new to the profession, are less likely to teach in high stakes grades. Our main estimates are, thus, a lower bound on the causal impacts of randomly assigning new teachers to students.2

The rest of the paper is structured as follows: the next section explains how our paper contributes to the literature on teacher mobility; Section 3 outlines our empirical strategy; Section 4 describes the education institutional setting in the UK and the dataset; Section 5 presents our main regression results, with Section 5.2 investigating the robustness of the analysis; Section 5.3 presents results on the potential channels that drive the negative impact of turnover and examines the actions schools take to mitigate these disruptive effects; Section 6 concludes.