The Demographics of the Coronavirus Crisis: Impacts at the Front Line of the “Leisure and Hospitality” Sector

The Demographics of the Coronavirus Crisis: Impacts at the Front Line of the “Leisure and Hospitality” Sector

The Demographics of the Coronavirus Crisis: Impacts at the Front Line of the “Leisure and Hospitality” Sector

PWBM · · 6 min read
The Demographics of the Coronavirus Crisis: Impacts at the Front Line of the “Leisure and Hospitality” Sector

The economic downturn due to coronavirus has disproportionately harmed workers in the leisure and hospitality businesses, such as restaurants and bars—these workers tend to be less-educated and lower-income.


The coronavirus pandemic has led to a large disruption in economic activity, which has disproportionately harmed workers that rely on in-person interaction in the leisure and hospitality industries. Related businesses include food service, bars, performing arts and spectator sports, and more.1 The figures below use recent data from the Current Population Survey to compare the income and demographics of these workers to those in other industries.2 Compared to workers in other industries, leisure and hospitality workers tend to be lower-income, younger, and less educated. They also tend to be Hispanic, non-white, and female.

Figure 1 shows that about 65 percent of workers in the leisure and hospitality sector are in the bottom two income quintiles. Compared to all other industries, workers in leisure and hospitality are about twice as likely to be in the lowest income quintile and 68 percent more likely to be in the second income quintile.

Figure 1. Distribution of Leisure/Hospitality Workers and All Other Workers by Income Levels

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Figure 1

Source: Current Population Survey — Annual Social and Economic Supplement (CPS - ASEC) (2017 - 2019), IPUMS-CPS, University of Minnesota, https://ipums.org/.

Note: For example, 36.4 percent of leisure and hospitality workers fall in the bottom 20 percent of the income distribution (first quintile), while 18.3 percent of workers in all other industries fall in the first quintile.

This difference in incomes coincides with differences in several demographic variables:3

Figure 2 shows that leisure and hospitality workers tend to be younger than their peers in other industries. Roughly 43 percent of leisure and hospitality workers are under the age of 30, compared to 21 percent of those in other industries. Younger workers are more likely to be low-income due to lifecycle effects, which explains some but not all of the difference in incomes. Additionally, low-income and younger workers are both less likely to have emergency savings.

Figure 2. Distribution of Leisure/Hospitality Workers and All Other Workers by Age

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Figure 2

Source: Current Population Survey — Annual Social and Economic Supplement (CPS - ASEC) (2017 - 2019), IPUMS-CPS, University of Minnesota, https://ipums.org/.

Note: For example 3.3 percent of leisure and hospitality workers are age 25, while 2.2 percent of workers in all other industries are age 25.

Figure 3 shows that leisure and hospitality workers tend to have fewer years of education than their peers in other industries. About half of workers in leisure and hospitality industries have a high school degree or less, compared to less than a third of those in other industries. Less-educated workers are at greater risk of unemployment and have lower expected future earnings.

Figure 3. Distribution of Leisure/Hospitality Workers and All Other Workers by Educational Attainment

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Figure 3

Source: Current Population Survey — Annual Social and Economic Supplement (CPS - ASEC) (2017 - 2019), IPUMS-CPS, University of Minnesota, https://ipums.org/.

Note: For example 14 percent of leisure and hospitality workers have less than a high school education, while 7 percent of workers in all other industries have less than a high school education.

Additionally, leisure and hospitality workers are less likely to be white, more likely to be Hispanic, and more likely to be female. About 24 percent of leisure and hospitality workers are Hispanic and 54 percent are white, compared to about 17 percent and 64 percent, respectively, of workers in other industries. More than half of leisure and hospitality workers are female compared to 46 percent of those in other industries.

The significance of the leisure and hospitality sector in state-level economies varies considerably. Figure 4 shows that most states have between six and 11 percent of their workforces in leisure and hospitality industries, but two states stand out: Hawaii, with about 16 percent of its workforce in leisure and hospitality, and Nevada with about 21 percent. These states with high shares of leisure and hospitality employment can be expected to see greater immediate losses in economic activity.

Figure 4. Share of Workers in the Leisure/Hospitality Sector, by State

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Figure 4

Source: Current Population Survey — Annual Social and Economic Supplement (CPS - ASEC) (2017 - 2019), IPUMS-CPS, University of Minnesota, https://ipums.org/.

Although the coronavirus pandemic will have widespread health and economic costs, businesses and workers in leisure and hospitality might see disproportionate disruption and hardship. Our above analysis shows that workers in these industries are more likely to be in demographic groups that were already lower income and less educated before coronavirus. Additionally, certain states’ workforces are more heavily concentrated in the leisure and hospitality sector.

More information on the living arrangements of leisure and hospitality workers.

Austin Herrick conducted this analysis, and Kody Carmody wrote this report, under the supervision of Diane Lim and Richard Prisinzano. Mariko Paulson produced the charts for the PWBM website.


  1. We use “leisure and hospitality” as defined in the Bureau of Labor Statistics’ leisure and hospitality supersector, consisting of Census industry codes 8560, 8570, 8580, 8590, 8660, 8670, 8680, and 8690.  ↩

  2. Current Population Survey — Annual Social and Economic Supplement (CPS - ASEC) (2017 - 2019), IPUMS-CPS, University of Minnesota, https://ipums.org/.  ↩

  3. Due to sample size concerns, we don't tabulate across categories and cannot say how much of the variation in income is explained by demographics.  ↩