Intergenerationally penalized? The long-term wage consequences of parental joblessness

Household Joblessness in U.S. Metropolitan Areas during the COVID-19 Pandemic: Polarization and the Role of Educational Profiles

The authors use Current Population Survey 2016 to 2021 quarterly data to analyze changes in household joblessness across metropolitan areas in the United States during the coronavirus disease 2019 pandemic. The authors first use shift-share analysis to decompose the change in household joblessness into changes in individual joblessness, household compositions, and polarization. The focus is on polarization, which is the result of the unequal distribution of individual joblessness across households. The authors find that the rise in household joblessness during the pandemic varies strongly across U.S. metropolitan areas. The initial stark increase and subsequent recovery are due largely to changes in individual joblessness. Polarization contributes notably to household joblessness but to varying degree. Second, the authors use metropolitan area–level fixed-effects regressions to test whether the educational profile of the population is a helpful predictor of changes in household joblessness and polarization. They measure three distinct features: educational levels, educational heterogeneity, and educational homogamy. Although much of the variance remains unexplained, household joblessness increased less in areas with higher educational levels. The authors show that how polarization contributes to household joblessness is shaped by educational heterogeneity and educational homogamy.

Uneven impacts of COVID-19 on the attendance rates of secondary school students from different socioeconomic backgrounds in Australia: A quasi-experimental analysis of administrative data

This paper contributes to the growing body of research that demonstrates uneven impacts of the COVID-19 pandemic on educational outcomes of students from different socioeconomic status (SES) backgrounds. We evaluate the early impacts of COVID-19 on student attendance in secondary school and show how these impacts depend on students' SES. We employ a quasi-experimental design, using difference-in-differences (DiD) estimation extended to incorporate third-order differences over time between low-SES and other students, and pre- versus during-COVID-19, leveraging robust administrative data extracted from the registers of the Tasmanian Department of Education. Using data from multiple cohorts of secondary school students in government schools in Tasmania (N = 14,135), we find that while the attendance rates were similar pre- and during-COVID-19 for high-SES students, there was a significant drop in attendance rates during COVID-19 among socioeconomically disadvantaged students, demonstrating the more pronounced impacts of COVID-19 for these students. The findings demonstrate that even "relatively short" lockdowns, as those in Tasmania in 2020 (30-40 days of home learning), can significantly affect the learning experiences of students from socioeconomically disadvantaged backgrounds. We discuss the implications of this for future pandemic planning in educational policy and practice and how this needs to be addressed in Australia's COVID-19 recovery.