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A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures for noncredit courses are reported to IPEDS but enrollments are not. This exclusion inflates any per FTE student figure calculated from IPEDS, in particular expenditures and revenues. A 2021 IPEDS Technical Review Panel (TRP #62) acknowledged this problem and moved campus institutional research offices a step closer to reporting noncredit enrollment data (RTI International, 2021). This article is the first to provide some numbers on the magnitude of this problem. It covers eight states--California, Iowa, New Jersey, New York, North Carolina, South Carolina, Tennessee, and Virginia. Data on noncredit community college enrollments were made available from system offices in all states. In addition, discussions were held at both the system level and the campus level to verify the data and assumptions. Figures provided by states were merged with existing IPEDS data at the campus and state levels, and then were adjusted to account for noncredit enrollments. The results provide evidence that calculations using IPEDS data alone overestimate the resources that community colleges have to spend on each student, although distortions vary greatly between states and among colleges in the same state. The results have important implications for research studies and college benchmarking.

Performance evaluation may change employee effort and decisions in unintended ways, for example, in multitask jobs where the evaluation measure captures only a subset of (differentially weights) the job tasks. We show evidence of this multitask distortion in schools, with teachers allocating effort across students (tasks). Teachers are evaluated based on student test scores; students who fail the test are retested 2-3 weeks later; and only the higher of the two scores is used in the teachers' evaluations. This retesting feature creates a sharp difference in the returns to teacher effort directed at failing versus passing students, even though both barely failing and barely passing students have arguably equal educational claim on (returns to) teacher effort. Using RD methods, we show that students who barely fail the end of school-year "t" math test, and are then retested, score higher one year later ("t"+1) compared to those who barely pass. This difference in scores occurs during the four years of the retest policy, but not in the years before or after. We find no evidence that the results arise from retesting "per se," or from changes in students' own behavior alone. The results suggest teachers give more effort to some students (tasks) simply because of the evaluation system incentives.

While instructional time is viewed as crucial to learning, little is known about the effectiveness of reducing absences relative to increasing the number of school days. In this regard, this paper jointly estimates the effect of absences and length of the school calendar on test score performance. Using administrative data from North Carolina public schools, we exploit a state policy that provides variation in the number of days prior to standardized testing and find substantial differences between these effects. Extending the school calendar by ten days increases math and reading test scores by only 0.8% and 0.2% of a standard deviation, respectively; a similar reduction in absences would lead to gains of 5.8% and 3% in math and reading. We perform a number of robustness checks including utilizing u data to instrument for absences, family-year fixed effects, separating excused and unexcused absences, and controlling for a contemporaneous measure of student disengagement. Our results are robust to these alternative specifications. In addition, our findings indicate considerable heterogeneity across student ability, suggesting that targeting absenteeism among low performing students could aid in narrowing current gaps in performance. Four tables and one figure are appended.