We describe the levels, trends, and patterns of school closure and restructuring in the United States from 1991 to 2019 across all sectors using a near census of K–12 schools. Focusing on the years with the best available data, 2014–18, we find that the annual closure rate of charter, private, and traditional public schools (TPSs) were 5.1, 2.9, and 0.9 percent, respectively. The annual restructuring rates are 2.0 percent for charter schools and 0.6 percent for TPSs. Regression analysis shows that these differences in closure and restructuring rates by sector drop slightly after controlling for student and school characteristics. The strongest predictor of increased closures is low student enrollment, especially in private schools. In charter and traditional public schools, achievement measures predict closure and restructuring nearly as strongly as enrollment. While racial and income composition are weaker predictors of closure/restructuring, that they predict at all, after controlling for many other factors, raises some equity concerns. We also discuss ways in which the forces behind closure/restructuring may be difficult to uncover with this type of quantitative analysis.

Given scarce resources for evaluation, we recommend that education researchers more frequently conduct comprehensive randomized trials that generate evidence on how, why, and under what conditions interventions succeed or fail in producing effects. Recent experience evaluating a randomized need-based financial aid intervention highlights some of our arguments and guides our outline of the circumstances under which the examination of mechanisms and heterogeneous impacts is particularly important. Comprehensive experiments can enhance research productivity by increasing the number of theories both tested and generated and can advance policy and practice by exploring the conditions under which interventions will be most successful in scale up. Paradoxically, while the emphasis on average treatment effects is typically associated with efficiency-minded economists, we argue that the approach is often inefficient from the standpoints of science and policy.

The vast majority of research and policy related to teacher quality focuses on the supply of teachers and ignores teacher demand. In particular, the important role of school principals in hiring teachers is rarely considered. Using interviews of school principals in a midsized Florida school district, we provide an exploratory mixed methods analysis of the teacher characteristics principals prefer. Our findings contradict the conventional wisdom that principals undervalue content knowledge and intelligence. Principals in our study ranked content knowledge third among a list of twelve characteristics. Intelligence does appear less important at first glance, but this is apparently because principals believe all applicants who meet certification requirements meet a minimum threshold on intelligence and because some intelligent teachers have difficulty connecting with students. More generally, we find that principals prefer an “individual mix” of personal and professional qualities. They also create an “organizational mix,” hiring teachers who differ from those already in the school in terms of race, gender, experience, and skills, and an “organizational match,” in which teachers have similar work habits and a high propensity to remain with the school over time. Because of tenure rules, many principals also prefer less experienced (untenured) teachers, even though research suggests that they are less effective.

Annual student testing may make it possible to measure the contributions to student achievement made by individual teachers. But would these “teacher value-added” measures help to improve student achievement? I consider the statistical validity, purposes, and costs of teacher value-added policies. Many of the key assumptions of teacher value added are rejected by empirical evidence. However, the assumption violations may not be severe, and value-added measures still seem to contain useful information. I also compare teacher value-added accountability with three main policy alternatives: teacher credentials, school value-added accountability, and formative uses of test data. I argue that using teacher value-added measures is likely to increase student achievement more efficiently than a teacher credentials-only strategy but may not be the most cost-effective policy overall. Resolving this issue will require a new research and policy agenda that goes beyond analysis of assumptions and statistical properties and focuses on the effects of actual policy alternatives.