On Covid-19: New Implications of Job Task Requirements and Spouse's Occupational Sorting

Abstract

The Covid-19 pandemic has disrupted working life in many ways, the negative consequences of which may be distributed unevenly under lockdown regulations. In this paper, we construct a new set of pandemic-related indices from the Occupational Information Network (O*NET) using factor analysis. The indices capture two key dimensions of job task requirements: (i) the extent to which jobs can be adaptable to work from home; and (ii) the degree of infection risk at workplace. The interaction of these two dimensions help identify which groups of workers are more vulnerable to income losses, and which groups of occupations pose more risk to public health. This information is crucial for both designing appropriate supporting programs and finding a strategy to reopen the economy while controlling the spread of the virus. In our application, we map the indices to the labor force survey of a developing country, Thailand, to analyze these new labor market risks. We document differences in job characteristics across income groups, at both individual and household levels. First, low income individuals tend to work in occupations that require less physical interaction (lower risk of infection) but are less adaptable to work from home (higher risk of income/job loss) than high income people. Second, the positive occupational sorting among low-income couples makes them less able to partially insure themselves. Consequently, low-income families tend to face a disproportionately larger risk of income/job loss from lockdown measures. In addition, the different exposure to infection and income risks between income groups can play an important role in shaping up the timing and optimal strategies to unlock the economy.

Estimation of differential occupational risk of COVID‐19 by comparing risk factors with case data by occupational group

“…One early study used differential telework ability and essential worker distribution to identify negative labor shocks by occupation, 31 while another examined the same outcome using physical proximity predictors from O*NET 32 . Other studies have used O*NET data to create indices reflecting the ease of remote work, and concluded that the economic burden of COVID‐19 falls disproportionately on low income workers, 33,34 women, and workers with low educational attainment 35 . These economic outcomes represent variable social determinants of health that are crucial in understanding the differential impact of COVID‐19 on individuals and populations 36 and may lend support to social insurance as a means to reduce hardship in particularly vulnerable workers 37 …”

The Income and Consumption Effects of COVID‐19 and the Role of Public Policy*

“…To analyse factors driving differences in labour market outcomes, we focus on three sources of risk. We adopt the physical proximity and location flexibility factors from Lekfuangfu et al (2020), who construct these indices from O*NET using factor analysis. 11 The indices are continuous measures of location flexibility (or ability to work from home) and physical proximity for each of 900 detailed occupations, reflecting that these features are unlikely to be binary (as also noted by Adams-Prassl et al (2020b)).…”

“…Joyce and Xu (2020) and Blundell et al (2020) document the characteristics of workers employed in sectors most likely to be affected by lockdown measures, based on pre-pandemic employment patterns. Hicks, Faulk and Devaraj (2020) study the physical proximity of occupations and Dingel and Neiman (2020) analyse work location flexibility, while Lekfuangfu et al (2020) and Mongey, Pilossoph and Weinberg (2020) consider the interaction between these two factors. Del Rio-Chanona et al (2020) provide a quantitative prediction of both supply and demand across wage levels.…”

Implications of COVID-19 on the Labor Market of Saudi Arabia: The Role of Universities for a Sustainable Workforce

“…Similarly, the fear of losing jobs or working on reduced wages has created further career shocks among skilled and unskilled workers [4]. However, Lekfuangfu et al observed that the rate at which people are becoming unemployed does not follow a universal pattern, as both workers' knowledge and their flexibility to work from home play a dominant role in their employment opportunities [5]. However, the phenomenon of working from home has categorized the labor market into "good jobs" and "bad jobs"; due to this, the balance of employment is unfairly skewed in favor of those who possess the right kind of skills compared to workers in roles whose nature prohibits remote working [6].…”