Xuan Jiang

Bio: Xuan Jiang is an academic researcher from Ohio State University. The author has contributed to research in topics: Unemployment & Recession. The author has an hindex of 4, co-authored 11 publications receiving 269 citations. Previous affiliations of Xuan Jiang include Purdue University.

Determinants of Disparities in Covid-19 Job Losses

Abstract: We make several contributions to understanding the socio-demographic divide in early labor market responses to the U.S. COVID-19 epidemic and its policies, benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanics, younger workers, and those with high school degrees and some college. Between April and May, all the demographic subgroups considered regained some employment. Re-employment in May was broadly proportional to the employment drop that occurred through April, except for Blacks who experienced a smaller rebound. Further, we show that compared to the 2001 recession and the Great Recession, employment losses in the early COVID-19 recession were smaller for groups with very low or very high (vs. medium) education. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Third, we find pre-COVID-19 sorting of workers into occupations and industries along demographic lines can explain a sizeable portion of the gender, race, and ethnic gaps in new unemployment. For example, while women did suffer more job losses than men, their disproportionate pre-epidemic sorting into remote work compatible occupations shielded women from what would have been even larger employment losses during the epidemic. However, there remain substantial gaps in employment losses across groups that cannot be explained by socio-economic differences. We find some larger gaps in labor market impacts when we consider the “employed but absent from work” measure present in the CPS, in addition to the more traditional employment and unemployment measures. We conclude with a discussion of policy lessons and future research needs implied by the disparities in early labor market losses from the COVID-19 crisis.

Is the Cure Worse than the Problem Itself? Immediate Labor Market Effects of COVID-19 Case Rates and School Closures in the U.S

Abstract: The relationship between population health and measures of economic well-being and economic activity is a long standing topic in health economics (Preston, 1975; Cutler, Deaton, and Lleras-Muney, 2006; Ruhm, 2000). The conceptual issues in analyzing the complicated link between health and economic well-being are central to understanding the implications of the COVID-19 epidemic in the United States The public health shock of the epidemic has direct economic impacts, but the mitigation policies governments are using to control the spread of the virus may also damage economic activity. We estimate how state job market conditions respond to state COVID-19 infections and school closures, which are the earliest of the major mitigation policies. Mitigation policies and local epidemiological conditions explain some of the variation in unemployment patterns. However, the historically unprecedented increase in new UI claims during the weeks of March 15-21 and March 22-28 was largely across-the-board and occurred in all states. This suggests most of the economic disruption was driven by the health shock itself. Put differently, it appears that the labor market slowdown was due primarily to a nationwide response to evolving epidemiological conditions and that individual state policies and own epidemiologic situations have had a comparatively modest effect.

Determinants of Disparities in Early COVID-19 Job Losses.

Abstract: This study examines the sociodemographic divide in early labor market responses to the U.S. COVID-19 epidemic and associated policies, benchmarked against two previous recessions. Monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanic individuals, younger workers, and those with a high school diploma or some college. Between April and May, the demographic subgroups considered regained some employment. Reemployment in May was broadly proportional to the employment drop that occurred through April, except for Black individuals, who experienced a smaller rebound. Compared to the 2001 recession and the Great Recession, employment losses in the early COVID-19 recession were smaller for groups with low or high (vs. medium) education. We show that job loss was greater in occupations that require more interpersonal contact and that cannot be performed remotely, and that pre-COVID-19 sorting of workers into occupations and industries along demographic lines can explain a sizable portion of the demographic gaps in new unemployment. For example, while women suffered more job losses than men, their disproportionate pre-epidemic sorting into occupations compatible with remote work shielded them from even larger employment losses. However, substantial gaps in employment losses across groups cannot be explained by socioeconomic differences. We consider policy lessons and future research needs regarding the early labor market implications of the COVID-19 crisis.

Planting the Seeds for Success: Why Women in STEM Do Not Stick in the Field

Abstract: Women are underrepresented in both STEM college majors and STEM jobs. Even with a STEM college degree, women are significantly less likely to work in a STEM occupation than their male counterparts. This paper investigates whether men and women possess different ability distributions and examines how much the gender gap in major choice and job choice can be explained by gender differences in ability sorting. I use Purdue University's administrative data that contain every Purdue student's academic records linked to information on their first job. I apply an extended Roy model of unobserved heterogeneity allowing for endogenous choice with two sequential optimizing decisions: the choice between a STEM and non-STEM major and the choice between a STEM and non-STEM job. I find that abilities are significantly weaker determinants of major choice for women than for men. High-ability women give up $13,000{$20,000 in annual salary by choosing non-STEM majors. Those non-STEM high-ability women make up only 5.6% of the female sample, but their total gains|had they made the same decision as men|explain about 9.4% of the gender wage gap. Furthermore, the fact that female STEM graduates are less likely to stay in STEM is unrelated to the differences in ability sorting. Instead, women's home region may be important in women's job decisions; female STEM graduates who return to their home state are more likely to opt out of STEM.

Lifestyle and mental health disruptions during COVID-19.

Abstract: Using a longitudinal dataset linking biometric and survey data from several cohorts of young adults before and during the COVID-19 pandemic ([Formula: see text]), we document large disruptions to physical activity, sleep, time use, and mental health. At the onset of the pandemic, average steps decline from 10,000 to 4,600 steps per day, sleep increases by 25 to 30 min per night, time spent socializing declines by over half to less than 30 min, and screen time more than doubles to over 5 h per day. Over the course of the pandemic from March to July 2020 the proportion of participants at risk for clinical depression ranges from 46% to 61%, up to a 90% increase in depression rates compared to the same population just prior to the pandemic. Our analyses suggest that disruption to physical activity is a leading risk factor for depression during the pandemic. However, restoration of those habits through a short-term intervention does not meaningfully improve mental well-being.