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The COVID-19 pandemic has been a seismic and on-going disruption to K-12 schooling. Using test scores from 5.4 million U.S. students in grades 3-8, we tracked changes in math and reading achievement across the first two years of the pandemic. Average fall 2021 math test scores in grades 3-8 were .20-27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores decreased by .09-.18 SDs. Achievement gaps between students in low-poverty and high-poverty elementary schools grew by .10-.20 SDs, primarily during the 2020-21 school year. Observed declines are more substantial than during other recent school disruptions, such as those due to natural disasters.
Families and governments are the primary sources of investment in children, proving access to basic resources and other developmental opportunities. Recent research identifies significant class gaps in parental investments that contribute to high levels of inequality by family income and education and, potentially, to inequality in children’s development. State-level public investments in children and families have the potential to reduce class inequality in children’s developmental environments by affecting parents’ behavior. Using newly assembled administrative data from 1998-2014, linked to household-level data from the Consumer Expenditure Survey, we examine how public sector investment in income support, health and education is associated with the private expenditures of low and high-SES parents on developmental items for children. Are class gaps in parental investments in children narrower in contexts of higher public investment for children and families? We find that more generous public spending for children and families is associated with significantly narrower class gaps in private parental investments. Moreover, we find that equalization is driven by bottom up increases in low-SES household spending for the progressive investments of income support and health, and by top down decreases in high-SES household spending for the universal investment of public education.
Recent expansions of child tax, food assistance and health insurance programs have made American families’ need for a robust social safety net highly evident, while researchers and policymakers continue to debate the best way to support families via the welfare state. How much do children – and which children – benefit from social spending? Using the State-by-State Spending on Kids Dataset, linked to National Vital Statistics System birth data from 1998-2017, we examine how state-level child spending affects infant health across maternal education groups. We find that social spending has benefits for both low birth weight and preterm birth rates, especially among babies born to mothers with less than a high school education. The stronger benefits of social spending among lower-educated families lead to meaningful declines in educational gaps in infant health as social spending increases. Finally, mediation analyses suggest that social spending benefits infant health through mothers’ increased access to prenatal services, as well as improvements in health behaviors. Our findings are consistent with the idea that a strong local welfare state benefits child health and increases equality of opportunity, and that spending on non-health programs is equally beneficial for child health as investments in health programs.
Recent state policy efforts have focused on increasing attainment among adults with some college but no degree (SCND). Yet little is actually known about the SCND population. Using data from the Virginia Community College System (VCCS), we provide the first detailed profile on the academic, employment, and earnings trajectories of the SCND population, and how these compare to VCCS graduates. We show that the share of SCND students who are academically ready to reenroll and would benefit from doing so may be substantially lower than policy makers anticipate. Specifically, we estimate that few SCND students (approximately three percent) could fairly easily re-enroll in fields of study from which they could reasonably expect a sizable earnings premium from completing their degree.
We use novel data on disciplinary referrals, including those that do not lead to suspensions, to better understand the origins of racial disparities in exclusionary discipline. We find significant differences between Black and white students in both referral rates and the rate at which referrals convert to suspensions. An infraction fixed-effects research design that compares the disciplinary outcomes of white and non-white students who were involved in the same multi-student incident identifies systematic racial biases in sentencing decisions. On both the intensive and extensive margins, Black and Hispanic students receive harsher sentences than their white co-conspirators. This result is driven by high school infractions and mainly applies to “more severe” infractions that involve fights or drugs. Reducing racial disparities in exclusionary discipline will require addressing underlying gaps in disciplinary referrals and the systematic biases that appear in the adjudication process.
School buses may be a critical education policy lever, breaking the link between schools and neighborhoods and facilitating access to school choice. Yet little is known about the commute for bus riders, including the average length of the bus ride or whether long commutes harm academic outcomes. We begin to fill this gap using data from New York City to explore the morning commutes of over 120,000 bus riders. We find that long bus rides are uncommon and that those with long bus rides are disproportionately Black and more likely to attend charter or district-choice schools. We find deleterious effects of long bus rides on attendance and chronic absenteeism of district-choice students.
Half of kindergarten teachers split children into higher and lower ability groups for reading or math. In national data, we predicted kindergarten ability group placement using linear and ordinal logistic regression with classroom fixed effects. In fall, test scores were the best predictors of group placement, but there was bias favoring girls, high-SES (socioeconomic status) children, and Asian Americans, who received higher placements than their scores alone would predict. Net of SES, there was no bias against placing black children in higher groups. By spring, one third of kindergartners moved groups, and high-SES children moved up more than their score gains alone would predict. Teacher-reported behaviors (e.g., attentiveness, approaches to learning) helped explain girls’ higher placements, but did little to explain the higher placements of Asian American and high-SES children.
Underrepresented minority (URM) college students have been steadily earning degrees in relatively less-lucrative fields of study since the mid-1990s. A decomposition reveals that this widening gap is principally explained by rising stratification at public research universities, many of which increasingly enforce GPA restriction policies that prohibit students with poor introductory grades from declaring popular majors. We investigate these GPA restrictions by constructing a novel 50-year dataset covering four public research universities' student transcripts and employing a staggered difference-in-difference design around the implementation of 29 restrictions. Restricted majors’ average URM enrollment share falls by 20 percent, which matches observational patterns and can be explained by URM students’ poorer average pre-college academic preparation. Using first-term course enrollments to identify students who intend to earn restricted majors, we find that major restrictions disproportionately lead URM students from their intended major toward less-lucrative fields, driving within-institution ethnic stratification and likely exacerbating labor market disparities.
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.
We examine the effects of disseminating academic performance data—either status, growth, or both—on parents’ school choices and their implications for racial, ethnic, and economic segregation. We conduct an online survey experiment featuring a nationally representative sample of parents and caretakers of children age 0-12. Participants choose between three randomly sampled elementary schools drawn from the same school district. Only growth information—alone and not in concert with status information—has clear and consistent desegregating consequences. Because states that include growth in their school accountability systems have generally done so as a supplement to and not a replacement for status, there is little reason to expect that this development will influence choice behavior in a manner that meaningfully reduces school segregation.