Racial Differences in Time at Work Not Working

Abstract

Racial differences in effort at work, if they exist, can potentially explain race-based wage/earnings disparities in the labor market. The authors estimate specifications of time spent on non-work activities at work by Black and White males and females with data from the American Time Use Survey. Estimates reveal that trivially small differences occur between non-Hispanic Black and non-Hispanic White males in time spent not working while on the job that disappear entirely when correcting for non-response errors. The findings imply that Black–White male differences in the fraction of the workday spent not working are either not large enough to partially explain the Black–White wage gap, or simply do not exist at all.

Time Use and Subjective Well-Being of Multiple Jobholders: Evidence From the American Time Use Survey

“…Research has consistently shown that race-based earnings disparities exist in labor markets with White workers earning more on average. Darity et al (2022) use ATUS data to show that Black and White workers spend statistically equal time at work on nonwork activities, so wage discrepancies cannot be explained by shirking. In this article, I find that MJHs work similar hours across race and ethnicity, so the experiences of working more than one job are not likely to explain race-based earning discrepancies.…”

The forest behind the tree: Heterogeneity in how U.S. Governor’s party affects black workers

“…Borah and Basu (2013) present an application of conditional and unconditional quantile that leads to different results. Darity Jr. et al (2021b) also use the unconditional quantile regression to analyse the heterogeneous causal effect of race on labor market outcomes. It is important to note both methods are based on continuous distributions.…”

“…(2012) (which would have been our preferred estimation method), or unconditional quantile as in Darity Jr. et al (2021b). 5 Thus, we have formed four quantiles subgroups based on total annual earnings, three quantiles subgroups based on total annual hours worked, and twelve subgroups by crossing quantiles hours worked and annual earnings.…”

“…It is important to note both methods are based on continuous distributions. The presence of masses probabilities on the distribution of earnings and total hours worked prevents the used quantile regression for RDD as in Frandsen et al (2012) (which would have been our preferred estimation method), or unconditional quantile as in Darity et al (2021). 5 Thus, we have formed four quantiles subgroups based on total annual earnings, three quantiles subgroups based on total annual hours worked, and twelve subgroups by crossing quantiles hours worked and annual earnings.…”

Whiteness hurts society: How whiteness shapes mental, physical, and social health outcomes

“…For instance, whiteness propagates the meritocratic illusion that all people have equitable opportunities to succeed and achieve the American Dream if they exert sufficient individual effort (Efird & Lightfoot, 2020; Malat et al., 2018). Yet, decades of empirical evidence reveal that marginalized and minoritized populations (especially those at the intersections of multiple marginalized identities) disproportionately bear the burden of adverse social outcomes and relatively poor health (Bailey et al., 2017; Darity et al., 2022; Geronimus et al., 2020; Kwate & Meyer, 2010; Pearson, 2008; Viruell‐Fuentes et al., 2012; Williams et al., 2019), so much so that the Centers for Disease Control and Prevention (CDC) named racism a public health crisis (CDC, 2021b). However, novel research (which we detail below) suggests that there is variation in the ways that whiteness affects White Americans: whiteness benefits the most privileged, while simultaneously hurting less privileged White individuals and society at large.…”