Education Inputs and Human Capital Production (2014)

Economists have long studied the role of education spending, schools, and teachers in the production of human capital. The recent availability of detailed datasets and powerful computing has permitted researchers to present more conclusive evidence regarding these topics. In this summary, I describe my recent work on these issues. I first discuss my work on the basic question of whether increased resources for school districts improve students' long-run outcomes. I then narrow down the unit of analysis and discuss the effect of individual schools and particular school policies. Finally, I look inside schools and discuss my research on the role of teachers in promoting student learning. The Importance of School Spending? Since the Coleman Report (1) (1966) showed that variation in school resources was unrelated to variation in student outcomes, researchers have questioned whether increased school spending actually improves students' short- and long-run outcomes. The existing evidence on the effect of school spending on student outcomes used test scores as the main outcome and yielded mixed results. Moreover, because there is mounting evidence that focusing on test scores may miss important effects on longer-run outcomes, the effect of school spending on long-run outcomes was unknown. In recent work, (2) Rucker Johnson, Claudia Persico, and I revisit the basic question of money matter? We compile a panel of high-frequency school spending data linked to detailed information on the passage of state school-finance reforms. We then link the spending and reform data to detailed, nationally representative data on children born between 1955 and 1985 and followed through 2011 to study the effect of the reform-induced changes in school spending on long-run adult outcomes. We use the timing of the passage of court-mandated reforms as an exogenous shifter of school spending across cohorts within the same district. We find that a 20 percent increase in per-pupil spending each year for all 12 years of public school for children from poor families leads to about 0.9 more completed years of education, 25 percent higher earnings, and a 20 percentage-point reduction in the annual incidence of adult poverty. In contrast, we find small effects for children from non-poor families. We present several patterns to support a causal interpretation of the estimates. We reconcile our findings with the mixed results in the existing literature by showing that even with a rich set of controls, relying on potentially endogenous changes in school spending will lead one to infer incorrectly that there is no relationship between school spending and student outcomes. Using higher-quality data and an improved methodology, our findings provide new, compelling evidence that money does matter and that increased school spending can meaningfully improve the longer-run outcomes of affected children. Effective Schools and School Policies Related to the question of whether school spending matters is the question of what kinds of education spending matter. A natural way to determine this is to identify the kinds of schools and programs that improve student outcomes. However, because students and parents typically select to schools and neighborhoods, it is often difficult to attribute differences in outcomes across schools to the schools themselves. In a series of papers, I employ data from Trinidad and Tobago to address these selection issues. At the end of primary school, students take an exam and submit an ordered list of four secondary school choices. The students' scores and choices are used to assign them to secondary schools using a serial dictatorship algorithm. Specifically, the highest-scoring student is assigned to their top choice, the next-highest-scoring student is assigned to their top choice among remaining schools, and so on until all school slots are filled. This algorithm creates many test score cut-offs such that students who have the same set of school choices and very similar test scores are assigned to different schools solely because some scored just above a cut-off while the others did not. …