Improving School Accountability Measures

A growing number of states are using annual school-level test scores as part of their school accountability systems. We highlight an under-appreciated weakness of that approach the imprecision of school-level test score means -- and propose a method for better discerning signal from noise in annual school report cards. For an elementary school of average size in North Carolina, we estimate that 28 percent of the variance in 5th grade reading scores is due to sampling variation and about 10 percent is due to other non-persistent sources. More troubling, we estimate that less than half of the variance in the mean gain in reading performance between 4th and 5th grade is due to persistent differences between schools. We use these estimates of the variance components in an empirical Bayes framework to generate filtered' predictions of school performance, which have much greater predictive value than the mean for a single year. We also identify evidence of within-school heterogeneity in classroom level gains, which suggests the importance of teacher effects.

Estimating Returns to Schooling When Schooling is Misreported

We propose a general method of moments technique to identify measurement error in self-reported and transcript-reported schooling using differences in wages, test scores, and other covariates to discern the relative verity of each measure. We also explore the implications of such reporting errors for both OLS and IV estimates of the returns to schooling. The results cast a new light on two common findings in the extensive literature on the returns to schooling: sheepskin effects' and the recent IV estimates, relying on natural experiments' to identify the payoff to schooling. First, respondents tend to self-report degree attainment much more accurately than they report educational attainment not corresponding with degree attainment. For instance, we estimate that more than 90 percent of those with associate's or bachelor's degrees accurately report degree attainment, while only slightly over half of those with 1 or 2 years of college credits accurately report their educational attainment. As a result, OLS estimates tend to understate returns per year of schooling and overstate degree effects. Second, because the measurement error in educational attainment is non-classical, IV estimates also tend to be biased, although the magnitude of the bias depends upon the nature of the measurement error in the region of educational attainment affected by the instrument.