We examine immigrant mens employment stability during the Great Recession and its aftermath using a longitudinal approach that draws on data from the Survey of Income and Program Participation (SIPP), a nationally representative panel survey of U.S. residents. Discrete-time event-history models are used to estimate male immigrants relative risk of experiencing an involuntary job loss or underemployment, defined as working less than full-time involuntarily. The analysis also investigates differences in job stability by immigrant documentation status. Undocumented immigrants are identified using a logical allocation method augmented with external information about whether the respondent was successfully matched with administrative data. We find that immigrants are at significantly higher risk of involuntary job loss, and especially of underemployment relative to native-born workers. Undocumented immigrants face a greater risk of adverse job transitions, particularly underemployment in the first part of the recession. When demographic and job characteristics are taken into account, immigrant-native and documented-undocumented differences attenuate but remain in many instances. A comparison of our findings with those from an earlier nonrecessionary period from 2004 to 2006 suggests that immigrants higher risk of employment instability may be attributed to the recession.

Whether immigrants and their descendants are catching up socioeconomically with the rest of society is a fundamental question in the study of immigrant assimilation. In this paper, we examine the progress that Hispanic immigrant men make catching up with the earnings of later-generation Whites across generations. We rely on data from multiple years of the Current Population Survey linked with individuals tax earnings. This unique dataset allows us to overcome some important limitations of previous studies that employ a synthetic generation approach in which individuals born approximately one generation earlier are used as proxies for actual parents. Our matching strategy also enables us to identify the exact third generation and evaluate the contribution of ethnic attrition to estimates of intergenerational mobility. Second-generation Hispanic men are found to experience lower mobility than later-generation Whites for most values of parental earnings. However, their lower mobility can be explained by their immigrant parents lower education levels. In contrast, third-generation Hispanic men experience lower mobility even after accounting for parental education and ethnic attrition. This finding is consistent with a stalling or reversal in the socioeconomic progress of Hispanics beyond the second generation.

A growing body of sociological research has shown that racial identification is not only fluid, but crucially depends on other individual- and societal-level factors. When such factors are also associated with socioeconomic outcomes such as earnings, estimates of the disadvantage experienced by individuals because of how they identify racially obtained from standard regression models may be biased. We illustrate this potential bias using data from a large-scale survey conducted by the Mexican census bureau. This survey is the first by the government agency since the country's independence to include a question on black identification. We find evidence of a substantial bias in estimates of racial disadvantage. Results from our initial models treating racial self-identification as an exogenous predictor indicate that black men have higher earnings than non-black men. However, when we use an instrumental variables model that treats racial self-identification as endogenous, that is, as a function of the same unobserved characteristics as individuals' earnings, we find a significant negative effect of black identification on earnings. While previous studies have acknowledged the endogeneity of race, ours is the first to explicitly model racial self-identification as an endogenous predictor to obtain an unbiased estimate of its effect on individuals' socioeconomic conditions.

The United States has experienced a dramatic rise in opioid addiction and opioid overdose deaths in recent years. We investigate the effect of the opioid epidemic at the local level on nonmarital fertility using aggregate- and individual-level analyses. Opioid overdose death rates and prescriptions per capita are used as indicators of the intensity of the opioid epidemic. We estimate area fixed-effects models to test the effect of the opioid epidemic on nonmarital birth rates obtained from vital statistics for 2000-2016. We find an increase in nonmarital birth rates in communities that experienced a rise in opioid overdose deaths and higher prescription rates. Our analyses also show that the local effect of the opioid epidemic is not driven by a reduction in marriage rates and that marital birth rates are unaffected. Individual-level data from the ACS 2008-2016 are then used to further assess the potential causal mechanisms and to test heterogeneous effects by education and race/ethnicity. Our findings suggest that the opioid epidemic increased nonmarital birth rates through social disruptions primarily affecting unmarried women but not through changes in their economic condition.

We investigate the impact of the COVID-19 epidemic on gender disparities in three employment outcomes: labor force participation, full-time employment, and unemployment. Using data from the monthly Current Population Survey, in this research note we test individual fixed-effects models to examine the employment status of women relative to that of men in the nine months following the onset of the epidemic in March of 2020. We also test separate models to examine differences between women and men based on the presence of young children. Because the economic effects of the epidemic coincided with the summer months, when womens employment often declines, we account for seasonality in womens employment status. After doing so, we find that womens full-time employment did not decline significantly relative to that of men during the months following the beginning of the epidemic. Gender gaps in unemployment and labor force participation did increase, however, in the early and later months of the year, respectively. Our findings regarding womens labor force participation and employment have implications for our understanding of the long-term effects of the health crisis on other demographic outcomes.