Does Job Quality Affect Occupational Mobility?

Leaving the Labor Force

Figure 2 displays the rate at which a worker transitions out of the labor force by job quality quartile. Again, this rate varies by job quality. Workers in the lowest-quality occupations leave the labor force at rates that are roughly 3.5 to 4 times that of workers in the highest-quality occupations. From 2010 to 2021, workers in the lowest-quality occupations left the labor force 4.5 percent of the time, on average, while workers in the highest-quality occupations left the labor force 1.2 percent of the time. This rate has increased since 2010, especially for lower-quality occupations. The rate at which workers in the lowest-quality occupations left the labor force increased by 0.8 percentage points from 2010 (4.1 percent) to 2021 (4.9 percent). The three higher-quality job quartiles saw smaller increases of 0.6, 0.1, and 0.2 percentage points, respectively. Again, contrary to the Great Resignation narrative, the increase in the rate at which a worker leaves the labor force has been ongoing. Moreover, only workers in lower-quality jobs saw upticks in 2020.

Becoming Unemployed

Figure 3 shows the rate at which a worker transitions into unemployment by job quality quartile. Consistent with the first two occupational mobility metrics, the rate at which a worker transitions into unemployment varies by job quality. Workers in lower-quality occupations transition into unemployment at higher rates than workers in higher-quality occupations. The transition into unemployment rates follow the business cycle: steady declines in the rates from 2010 to 2019, followed by an increase in 2020 and decline in 2021, with lower-quality occupations showing larger swings than higher-quality occupations. Workers in the lowest-quality occupations saw the rate into unemployment increase by 2.8 percentage points from 2019 to 2020, compared to the increase of 0.6 percentage points that workers in the highest-quality occupations saw. In 2021, rates remained above prepandemic levels for all quartiles, with the largest differences in the lowest-quality occupations (0.3 percentage points).

Changing Occupations

The final occupational mobility metric I examine is the rate at which workers in the lowest-quality occupations move to other employment—either to another lowest-quality occupation or into a higher-quality occupation. Figure 4 presents the rates at which workers in the lowest-quality occupations transition into a different lowest-quality occupation and into a higher-quality occupation (quartiles 2, 3, and 4). Both outcomes are relatively infrequent (less than 5 percent) but have become increasingly more likely since 2010. The rate at which workers moved to another lowest-quality occupation showed a slight upward trend from 2010 to 2018, followed by an increase in 2019 to 4.5 percent. The increase is attributed to a decrease in the rate at which workers remained in the same occupation as labor market conditions tightened. The rate has since settled to 3.1 percent in 2021. The rate at which a worker moved into a higher-quality occupation steadily increased from 2010 to 2015, after which upward mobility slowed but has since picked up in 2019; the rate reached 4.8 percent in 2021. Again, these trends began prior to the pandemic.

Exploring the series of occupational mobility metrics for workers highlights the value of looking at labor market data with a job quality lens. There is a positive enough correlation between higher-quality occupations and higher rates of workers’ remaining in the same occupation (and labor force in general) that improving job quality is likely an additional solution for employers to consider in response to hiring and retention challenges.

These metrics also highlight how daunting navigating the labor market can be for workers in the lowest-quality jobs. In 2021, nearly 9 out of 10 workers in the lowest-quality jobs remained in the same lowest-quality jobs (85.4 percent) or in different lowest-quality jobs (3.1 percent). Workers in the lowest-quality occupations are just as likely to leave the labor force altogether (4.9 percent) as they are to move into a higher-quality occupation (4.8 percent). And workers with the lowest-quality jobs transition into unemployment at four times the rate of workers in the highest-quality jobs (1.8 vs. 0.4 percent).⁶

Which Worker Characteristics Are Associated with Specific Occupational Mobility Outcomes?

To further understand job mobility outcomes for workers in the lowest-quality occupations, it can be helpful to examine the characteristics of workers there. Each of the four occupational mobility outcomes described above can be used to explore which worker characteristics are associated with specific outcomes for workers in the lowest-quality occupations. I’ve incorporated the worker characteristics listed in Table 2 into a series of logistic regression models to do this portion of the analysis. I’ve also included year variables to further support the observation that the occupational mobility trends started prior to the COVID-19 pandemic. Results included in the following figures contain an average effect for each variable and are relative to the omitted category for each group of variables.⁷

There are a few observations that emerge from this part of the analysis:

• The importance of education is highlighted across the occupational mobility outcomes. Higher rates of educational attainment are associated with a greater likelihood of both staying in the labor market and transitioning into a higher-quality occupation.
• There is evidence that some industry sectors, such as construction and manufacturing, hold more promise for a worker’s upward mobility than others. Unfortunately, those industry sectors that employ the highest shares of workers in the lowest-quality occupations, such as retail sales, healthcare, and social services, and accommodation and food services, do not fall into this category.
• Older workers are more likely to stay in the labor market, yet they are less likely to move into a higher-quality occupation.
• Gender and racial disparities are present in occupational mobility outcomes, but a worker’s gender or race tends to have smaller effects than other worker characteristics. However, the data suggest that women and workers of color may be more sensitive to job quality than their counterpart
• As mentioned above, the observed occupational mobility trends have been ongoing since the mid-2010s.

Characteristics of Workers Who Stay in the Same Occupation

Figure 5 presents worker characteristics as they relate to workers who stay in the same lowest-quality occupation. Looking at the rate at which they stay (x axis), it is clear that no one worker characteristic is a dominating factor for remaining in the same occupation, but there are a few characteristics worth mentioning. Being a head of household (4.1 percent more likely than those who are not heads of households), holding a 2-year degree (3.1 percent more likely than a worker without a high school diploma), and being employed in the retail trade, healthcare and social assistance, and accommodation and food service sectors (3.2 percent more likely than a worker in the public sector) are associated with remaining in the same occupation. Also noteworthy (if somewhat hidden by the relatively small average effect) is age; an older worker (45 years old) is 3.7 percent more likely than a younger worker (25 years old) to remain in the same occupation.

Alternatively, factors related to race, industry, and time are associated with not remaining in the same occupation. Black (2.7 percent less likely than other races), Asian (1.7 percent less likely than other races), and Hispanic (1.6 percent less likely than non-Hispanic workers) workers are less likely to remain in the same occupation. Similarly, those employed in construction are 2.6 percent less likely than public-sector workers to remain in the same occupation. And workers have become less likely over time to remain in the same occupation, especially in the last three years (2019–2021).

Characteristics of Workers Who Leave the Labor Force

Figure 6 shows which characteristics have a larger impact on workers’ leaving the labor force. Race and time are associated with workers being more likely to leave the labor force. Asian (21.5 percent) and Black (20.1 percent) workers are more likely to leave the labor force than workers of other races. And starting in 2015, workers have been more likely than workers in 2010 to leave the labor force. Important worker characteristics associated with remaining in the labor force include age, gender, education, head of household, and industry. An older worker (45 years old) is 32.6 percent less likely to leave the labor force than a younger worker (25 years old). Male workers are 35.1 percent less likely to leave the labor force than female workers. Higher rates of educational attainment are also associated with greater attachment to the labor force; workers with a 2-year degree or a 4-year degree are more than 45 percent less likely to leave the labor force than a worker without a high school diploma. A head of household is 47.9 percent less likely than a worker who is not head of household to leave the labor force. Workers in several industry sectors—manufacturing; wholesale trade; retail trade; utilities; finance, insurance, and real estate; and healthcare and social assistance—are at least 20 percent more likely than public-sector workers to remain in the labor force. And workers with young children in the home are 14 percent less likely to leave the labor force than a worker without young children in the home.

Characteristics of Workers Who Become Unemployed

Figure 7 shows that for workers transitioning into unemployment, the business cycle and a few notable worker characteristics are important. Examining the transitions by year highlights the cyclical nature of unemployment; transitioning into unemployment became less likely during the 2010s, more likely in 2020 when there was a recession, and again less likely in 2021 as the economy began to recover and business activity increased. Relatedly, the industry sector in which a worker is employed also influences how likely they are to transition into unemployment. Workers in agricultural and farming, construction, and professional and business services are 48.7 percent, 60.1 percent, and 39.4 percent, respectively, more likely than workers in the public sector to become unemployed. Alternatively, workers in healthcare and social assistance (33.7 percent); finance, insurance, and real estate (27.9 percent); and retail trade (25.3 percent) are less likely than public-sector workers to transition into unemployment. There are also some familiar demographic patterns related to unemployment. Workers with lower rates of educational attainment are more likely to become unemployed. Younger workers (25 years old) are 29.7 percent more likely to transition into unemployment than an older worker (45 years old). Black workers are 11.2 percent more likely to transition to unemployment than workers of other races. An unmarried worker is 32.2 percent more likely to become unemployed than a married counterpart, while workers with young children in the home are 14.5 percent more likely than workers without young children to transition into unemployment.

Workers Who Transition into Other Lowest-Quality Occupations

Figure 8 shows how worker characteristics relate to workers’ transitioning into different lowest-quality occupations. The importance of educational attainment is once again highlighted, as workers with lower rates of educational attainment are more likely to take another lowest-quality occupation. Time is also important, as workers have been more likely to move from one lowest-quality job to another starting in the mid-2010s, reaching 53.7 percent more likely in 2019. The industry sector in which a worker is employed also influences the likelihood of moving to another lowest-quality occupation; workers in construction (43.0 percent), information (26.3 percent), other services (26.1 percent), agriculture and farming (24.6 percent), and educational services (22.2 percent) are less likely to move to another lowest-quality occupation than workers in the public sector. In terms of race and ethnicity, Hispanic (31.8 percent), Asian (19.9 percent), and Black (15.0 percent) workers are more likely to move into a different lowest-quality occupation than workers of other races.

Workers Who Transition from Lowest-Quality Occupations to Higher-Quality Occupations

Figure 9 concludes the set of occupational mobility metrics by showing which worker characteristics relate to workers moving from lowest-quality occupations to higher-quality occupations. Workers with higher rates of educational attainment are more likely to move into a higher-quality occupation, and this effect gets larger as educational attainment increases. For example, workers with a high school diploma (12.1 percent), some college (17.8 percent), a 2-year degree (29.0 percent), and a 4-year degree (60.8 percent) are more likely to transition into a higher-quality occupation than a worker without a high school diploma. Workers in certain industry sectors are more likely to move into higher-quality jobs, too; workers in construction, manufacturing, utilities and finance, and insurance and real estate are all more than 20 percent more likely than workers in the public sector to move into a higher-quality occupation. Conversely, workers in the agriculture and farming (20.9 percent); retail trade (19.5 percent); educational services (35.4 percent); healthcare and social assistance (18.1 percent); arts, entertainment, and recreation (44.0 percent); accommodation and food services (45.8 percent); and other services (48.1 percent) sectors are less likely than workers in the public sector to move into a higher-quality occupation. Unfortunately, these same sectors employ 75 percent of workers in the lowest-quality occupations. Disparities are present in terms of gender but not in terms of race. Male workers are 22.3 percent more likely than female workers to move into a higher-quality occupation. Black (16.7 percent) and Asian (14.8 percent) workers are more likely than workers of other races to find a higher-quality occupation, while the results for white workers are not statistically significant. The likelihood of moving into a higher-quality occupation has increased over time and currently stands at 28.0 percent more likely in 2021 than in 2010.

Conclusion

This analysis adds to a growing body of research about job quality and shows that it is an important dimension of the labor market to consider. Workers—especially those in the lowest-quality occupations—are affected by job quality. Those in the lowest-quality occupations tend to be less attached to employment and the labor market, a situation which suggests that employers might consider improving job quality in response to hiring and retention challenges. Furthermore, it has been shown that these are not new developments related to the pandemic but rather ongoing labor market trends. Taking job quality into consideration reveals that even when the unemployment rate is low, workers in the lowest-quality occupations can face bleak labor market prospects. Moreover, it is also suggested that the industry sectors predominantly employing workers in the lowest-quality jobs may limit a worker’s ability to move into a higher-quality job.