- Matthew P. Steinberg
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Matthew P. Steinberg
In spring 2020, nearly every public school in the U.S. closed at the onset of the Covid-19 pandemic. Existing evidence suggests that initial decisions to re-open schools for in-person instruction were generally unrelated to Covid case and death rates. Instead, local political partisanship and teachers union strength were better predictors of school re-opening status in fall 2020. We replicate and extend these analyses using data collected over the entire 2020-21 academic year. We demonstrate that Covid case and death rates were, in fact, meaningfully related to initial rates of in-person instruction. We also show that all three of these factors—Covid, partisanship, and teachers unions—became less predictive of in-person instruction as the school year continued. Conversely, the relationship between prior student achievement and the rate of in-person instruction increased in salience. We then leverage data from two nationally representative surveys of Americans’ attitudes toward education and identify an as-yet-undiscussed factor that predicts in-person instruction: pre-pandemic public support for increasing teacher salaries. We speculate that education leaders were better able to manage the logistical and political complexities of school reopenings in communities with greater support for educators.
We synthesize and critique federal fiscal policy during the Great Recession and Covid-19 pandemic. First, the amount of aid during both crises was inadequate to meet policy goals. Second, the mechanisms used to distribute funds was disconnected from policy goals and provided different levels of aid to districts with equivalent levels of economic disadvantage. Third, data tools are missing making it difficult to understand whether funds were used to meet policy goals. Details for these results are provided along with policy recommendations.
In 2009, the federal government passed the American Recovery and Reinvestment Act (ARRA) to combat the effects of the Great Recession and state revenue shortfalls, directing over $97 billion to school districts. In this chapter, we draw lessons from this distribution of fiscal stimulus funding to inform future federal intervention in school finance during periods of economic downturn. We find that district spending declined by $945 per pupil per year following the Great Recession, particularly after a stimulus funding cliff when ARRA funding declined. Spending declines varied more within than across states, while stimulus funding was directed to districts through pre-Recession state funding formulae which varied in their relative progressivity. Spending losses were greater in districts serving fewer shares of students qualifying for free or reduced-price lunch or special education services, in districts with higher-achieving students, and in districts with greater levels of spending prior to the Great Recession; declines were unassociated with district’s racial/ethnic composition, the share of English language learners, or a district’s reliance on state aid. We conclude by identifying different stimulus policy targets and with recommendations regarding the magnitude and distribution of future federal fiscal stimulus funding, lessons relevant to the COVID-19-induced recession and beyond.
Personnel evaluation systems have historically failed to identify and remediate low-performing teachers. In 2012, Chicago Public Schools implemented an evaluation system that incorporated remediation and dismissal plans for low-rated teachers. Regression discontinuity estimates indicate that the evaluation reform increased the exit of low-rated tenured teachers by 50 percent. The teacher labor supply available to replace low-rated teachers was higher performing on multiple dimensions, and instrumental variables estimates indicate that policy-induced exit of low-rated teachers significantly improved teacher quality in subsequent years. Policy simulations show that the teacher labor supply in Chicago is sufficient to remove significantly more low-performing teachers.
Principals shape the academic setting of schools. Yet, there is limited evidence on whether principal professional development improves schooling outcomes. Beginning in 2008-09, Pennsylvania’s Inspired Leadership (PIL) induction program required that newly hired principals complete targeted in-service professional development tied to newly established state leadership standards within five years of employment. Using panel data on all Pennsylvania students, teachers, and principals, we leverage variation in the timing of PIL induction across principal-school cells and employ difference-in-differences and event study strategies to estimate the impact of PIL induction on teacher and student outcomes. We find that PIL induction increased student math achievement through improvements in teacher effectiveness, and that the effects of PIL induction on teacher effectiveness were concentrated among the most economically disadvantaged and urban schools in Pennsylvania. Principal professional development had the greatest impact on teacher effectiveness when principals completed PIL induction during their first two years in the principalship. We also find evidence that teacher turnover declined in the years following the completion of PIL induction. We discuss the implications of our findings for principal induction efforts.
We leverage an obscure set of rules in Texas’s school funding formula granting some districts additional revenue as a function of size and sparsity. We use variation from kinks and discontinuities in this formula to ask how districts spend additional discretionary funds, and whether these improve student outcomes. A $1,000 annual increase in foundation funding, or 10% increase in expenditures, yields a 0.1 s.d. increase in reading scores and a near 0.08 increase in math. In addition, dropout rates decline, graduation rates marginally increase, as does college enrollment and to a smaller degree graduation. These gains accrue in later grades and largely among poorer districts. An analysis of budget allocations reveals that additional funding only marginally affects budget shares.