Specifically, Dee analyzes student data from California’s Central Valley, one of the highest-profile targets of raids on immigrant communities. Although schools themselves were not subject to the January raids, many workplaces and other previously protected spaces became targets during this period. With data from five school districts, Dee uses regression to compare absences in January and February 2025 to absences in 2022–23, 2023–24, and the earlier part of the 2024–25 school year. In total, the sample includes 2,234 daily counts of student absences from the five districts, four of which allowed for breakdown by grade levels served within the district (pre-K, elementary, middle, and high school). Dee’s regression models control for several factors: pre-existing differences in attendance among the districts; the impact of “events” that may separately impact attendance (e.g., the last day before a vacation, holidays like Day of the Dead); and previous variations among each school year, month, and day of the week (e.g., absenteeism may be higher on Fridays than other days).
The findings are grim. In the period from January 8 (the day after the Central Valley raids began) to the end of February, overall absenteeism was 22 percent higher than would otherwise be expected, even with controls and in the context of the pre-existing absenteeism crisis . Although Dee does not identify the districts for safety reasons, he does confirm that those closest to the largest raids saw the highest rates of absenteeism. Also worth noting is that the raids did not continue throughout this time period, but the high absenteeism rates did; this finding indicates that the fear surrounding raids—and its impact on attendance—creates an impact that extends beyond the raids’ duration.