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Small Business Workforce Trends in the Quarantine Economy (April 2020)

Daniel Sternberg Head of Data Science, Gusto 
Small Business Workforce Trends in the Quarantine Economy - April 2020 - Gusto

Gusto enables more than 100,000 small businesses across the United States to take care of their teams with full-service payroll, benefits, compliance, expert HR, and more.

Our COVID-19 Small Business Resource Hub has legislation updates, advice, and support.

This report analyzes leading indicators and changes to employment at small businesses for the full month of April 2020. Our findings show that small businesses remain in critical condition as a result of the necessary government actions to reduce the spread of COVID-19. Furlough rates significantly increased, and we continue to see high rates of layoffs and reduction in hours, combined with lower than usual hiring rates. 

However, data from the second half of April provides initial evidence of stabilization, with layoff rates returning to levels lower than the initial peak of the crisis in early April. Also, hiring rates are starting to return to pre-COVID levels. This stabilization may be due to many factors, including small businesses who received Paycheck Protection Program (PPP) loans rehiring employees in order to meet forgiveness requirements, the start of limited business operations that require modest rehiring, and plans in some states to reopen certain types of businesses in early May. 

Payroll data is a leading indicator of where the small business economy is headed, and this report suggests that we are in a critical period for understanding how the crisis will affect small businesses going forward. Our data indicates that small business employment is no longer in a free fall. But given the losses in employment since March, if PPP loans run out, and/or if many businesses rehire only a fraction of their employees, we could easily see the economic impact deepen and expand further. Gusto will continue to look at leading indicators, including rehiring, pace of job loss and furloughs, as well as changes to wages in order to track the true impact of this crisis on small businesses over the coming months. 

The findings reported below represent data points with meaningful sample sizes[1], but based on the distribution of Gusto’s customers, they may not be fully representative of the industry and geographic breakdown of small businesses across the United States.

Key Report Findings

  • Driven by significantly increased furlough rates, net reduction in small business headcount and lost wages continued into April ‘20. Gusto data shows that furloughs increased by 138% from March ‘20 to April ‘20. Additionally, furloughs accounted for 42% of total lost wages in April ‘20, compared to only 22% in March ‘20.
  • Small business headcount remains in critical condition, but late April provided the first early signs of stabilization since peak layoffs. The week of April 27 saw a 72% increase in the hiring rate compared to the week of April 6, which was the lowest point. Five states saw a positive net change in headcount of approximately 1% or more across the full month of April ‘20.
  • Workers who are making less are being hit harder by lost wages. Hourly employees averaged 26% less pay in April ‘20 compared to previous months, while salaried workers experienced a 4% average reduction in wages. Additionally, hourly workers are being furloughed nearly five times more frequently (397%) than salaried employees. 

April ’20 Small Business Trends

As the crisis began to unfold in mid-March, small business workers experienced a substantial reduction in hours as state shutdowns shuttered businesses and led employers to take actions to lower their payroll costs. The reduction in employee worked hours was the biggest contributor to reducing earned wages in March ‘20.

As the COVID crisis moved through April, we’ve seen evidence that employers have taken cost-cutting action beyond merely reducing hours for their employees. The country continued to see large numbers of unemployment claims over the month, and the recently released Labor Department jobs report also showed a decline of 20.2 million jobs in April, the largest drop in non-farm payrolls in the report’s history. 

Below, Table 1 compares employer actions between March ‘20 and April ‘20 to the same period last year.  Most notable in this month’s reporting are the jumps in furlough and terminations in April ‘20 compared to the same period last year, as well as compared to our March ‘20 reporting.  

Table 1. Rates of employer actions affecting employee wages for March 2019 and March 2020 as compared to the previous month.


March ‘19April ‘19March ‘20April ’20
Furlough rate3.7%3.0%4.5%10.7%
Reductions in hours9.4%10.4%13.8%12.2%
Termination rate4.0%7.6%7.9%10.7%
Layoff rateN/A (not captured)N/A (not captured)3.0%4.8%
Net change in headcount+1.5%+3.2%-3.7%-4.7%

Substantial increase in furlough rates

Furloughs are measured separately from more permanent headcount reduction like terminations and layoffs. These employees are still listed on employer payrolls, but are not logging any hours and don’t earn any wages (although employees are eligible to file with their state for unemployment benefits, and employers may continue to provide benefits such as health insurance). In April ’20, we saw a 3.6x year-over-year overall increase in employees who were furloughed (10.7% versus 3.0%) and more than double the rate seen in March of this year (4.5%). 

Moreover, where reduced hours was the greatest contributor to the reduction in employee earnings in March ‘20 (accounting for nearly 65% of the overall reduction in wages for employees in March), by April only 37% of the reduction in earnings was explained by workers on reduced hours. Employers’ shift towards furloughing and layoffs in April resulted in 62% of the reduction in worker earnings caused by furloughs (42%) and outright terminations (19%). When we reported in March, furloughs only explained 22% of wage reduction, and 13% came from terminations.

Hourly workers hit harder than salaried employees

As previously reported by Gusto, lower-income hourly workers appear to be bearing the brunt of the impact of the COVID-19 economic downturn. This month our data reflects that nearly 17% of hourly employees were furloughed between February and April of ‘20 (a 3.8x increase over the same period last year), whereas only 3.4% of salaried employees were furloughed (compared to 1.3% last year, a 2.6x increase)[2]

Hourly workers were also more likely to be terminated and have reduced hours than their salaried counterparts, as shown in Tables 2a and 2b below.

Tables 2a, 2b. Rates of employer actions affecting employee wages for April 2019 and April 2020 as compared to February of the respective year, split by hourly and salaried. 

2a. April 2019


HourlySalaried
Furlough rate4.5%1.3%
Reductions in hours16.7%4.2%
Termination rate10.6%4.7%

2b. April 2020


HourlySalaried
Furlough rate16.9% (3.8x YoY)3.4% (2.6x YoY)
Reductions in hours18.6% (1.1x YoY)5.3% (1.3x YoY)
Termination rate15.0% (1.4x YoY)6.2% (1.3x YoY)

Overall reduction in wages

Gusto’s payroll data provides a lens into the actions small businesses have taken to control their costs during this extraordinary period of time. In April ’20, we saw a 10% gap in overall wages paid to small business employees compared to what we would expect based on previous months and year-over-year comparisons. Again, the gap was most extreme for hourly workers.  Hourly employees averaged 26% less pay in April ‘20 compared to previous months and the same month last year, whereas salaried workers only experienced a 4% average reduction in wages.

Changes in staffing levels

Small business headcount continued to decline in April, with a 1% overall reduction for the month, for a total reduction of 4.7% in the two months since the COVID crisis began. Our March report showed a 3.8% net reduction in headcount during the month, driven by a >1,000% increase in layoffs and an 11% reduction in hiring. Figure 1 shows the net change in headcount and hiring termination and layoff statistics by month since January 2019[3]

Figure 1. Monthly net change in headcount and hiring, termination and layoff statistics. 

April Report - Fig1

The continued reduction in headcount in April was driven by a combination of heightened layoffs (1.8%, a 39% reduction from March, but still a 580% increase over February) and an even lower hiring rate than in March (4.2%, 14% lower than March and 24% lower than February). While overall termination rates fell nearly to pre-COVID levels (5.2% for April, which is only slightly above April 2019 at 5.0%), over half of this reduction came from declining voluntary terminations (2.2% for April, versus 3.6% March and 3.2% in February). The decline in voluntary terminations suggests that workers who are currently employed are less likely to look for new job opportunities—and also highlights the lack of these opportunities.

Meanwhile, employers are increasingly rehiring former employees. Prior to COVID, in most months rehires made up 8–10% of all hires, increasing to up to 15% during the holiday season. In April, rehires made up 22% of all hires. Figure 2 shows the rate of rehires as a proportion of hires for each month since January, 2019.

Figure 2. Rehires as a percentage of hires. 

April Report - Fig2 updated

On a weekly basis, we saw small continued declines in headcount during the weeks of March 30 through the week of April 13, but the most recent two weeks have shown some net headcount growth. Given the April furlough rates discussed above, however, wages and hours worked may still be continuing to decline. Figure 3 shows the weekly net change in headcount and hiring, termination, and layoff statistics from the week of March 2 through the week of April 27.

Figure 3. Weekly net change in headcount and hiring, termination and layoff statistics.

April report - Fig 3

The drivers of the growth in headcount are a decline in the layoff rate from the current peak week of the crisis and a recovery in hiring that was partially driven by rehiring. While layoff rates have fallen, they remain above their pre-COVID baseline. During the week of April 27, the layoff rate was 0.26%, still nearly four times the pre-COVID layoff rates in February and early March, which hovered between 0.06–0.08%, but far lower than the peak the week of March 23 (1.32%). The hiring rate for the week of April 27 was 1.4%, a 72% increase over the low point the week of April 6, and in the range of the weeks immediately before the layoff spike began (1.3–1.4%). This increase was partially driven by rehiring, which represented nearly 26% of all hires the week of April 27, up from 8–10% in the weeks immediately preceding the crisis.

Meanwhile, voluntary terminations have remained low even as hiring has recovered over the past two weeks. Along with the rehiring trend, this suggests that the hires businesses have made in the past two weeks have been increasingly drawing from the pool of unemployed workers. 

Given that we’ve only seen headcount growth for the past two weeks, it’s certainly too early to know whether these changes will be short-lived or long-lasting. In addition, more research is needed to understand what is driving the increases in hiring and reductions in layoff rates. In some cases, businesses that obtained Paycheck Protection Program loans may be rehiring and avoiding layoffs in order to fulfill the forgiveness requirements of the program. In other cases, businesses may have found ways to shift their business models that require them to do some limited hiring. In the case of PPP, if the reach of the program is wide enough and long-lasting enough, we might see significant continued rehiring over the coming weeks. If, on the other hand, these trends are more driven by shifts to different business models that rely on more limited staffing, we might expect this growth to level off quickly.

Industry Trends

Small businesses in some industries that were less affected by the crisis in March showed some modest gains in April. The industries with at least 1,000 Gusto customers with the greatest gains were:

  1. Facilities (+2.3%)
  2. Finance (+0.5%)
  3. Consulting (+0.4%)
  4. Wholesale (+0.2%)
  5. Construction (+0.2%)

Many other industries continued to shed headcount at significant rates in April, including some who saw larger headcount declines in April compared to March. In particular, Finance, Accounting, and Non-Profits showed larger declines in the month. Figure 4 compares the net change in headcount for March and April across all industries with at least 1,000 Gusto customers. Table A1 in the Appendix provides hiring, termination, and layoff statistics across these industries for the month of April, and Table A2 shows statistics for the last week of April.

Figure 4. Net change in headcount for March and April by industry.

April Report - Fig4

Following the overall trend, most industries actually began to see increases in headcount over the last two weeks of April, including many of the hardest hit industries that depend on foot traffic (though Tourism saw no increases). For example, Retail saw a 1.3% net increase in headcount in the last two weeks of April, while Food & Beverage saw a net increase of approximately 1%. Figure 5 shows the cumulative net change in headcount for some of the most heavily affected industries on Gusto over the course of the crisis, compared to all others.

Figure 5. Cumulative change in headcount since the week of March 2nd across heavily affected industries, and all others.

April Report - Fig5 updated

Geographic Trends

State and local responses to the crisis shifted over the course of April, and the hiring and layoff trends reflect these local decisions. Multiple states, especially in the Southeast, issued stay-at-home or shelter-in-place ordinances that began in early April. Later in the month, many of these orders expired or partial reopenings were announced.

These two directions complicate our understanding of the monthly data for April. Overall, headcount increased in 10 states with over 1,000 employees on Gusto for the month, while it declined in all other states. The largest percentage increases were in Kansas, Kentucky, Nebraska, Ohio, and Utah, which all had near or above 1% increases in headcount for the month. As of the end of April, all of these states have announced partial reopenings for early May.

The largest percentage declines were in Delaware, Alaska, New York, Vermont, and Washington, which all declined by more than 2%. Of these states, only Alaska has reported a partial reopening. Figure 6 below shows net change in headcount by state ranked for the month of April, compared to each state’s net change in March (for states with at least 1,000 employees on Gusto).

Figure 6. Net percentage change in headcount for March and April by state.

April Report - Fig6

Most states started to show positive headcount growth rates in the last two weeks of April. Nearly all states had more hiring than terminations for the week of April 27—the only exceptions were New York (-0.4%), Delaware (-0.2%), and Virginia (less than -0.1%). At the same time, layoff rates remained above their pre-COVID baselines for all but a handful of states. Figure 7 below shows the net headcount change in prior crisis weeks compared to the week of April 27 for all states with at least 1,000 employees on Gusto.

Figure 7: Cumulative percent headcount change for all crisis weeks before 4/27, compared to the change the week of 4/27.

April Report - Fig7 updated

Greater hiring rates across states were associated with higher rates of rehires as a proportion of total hires (r = .41) and higher voluntary termination rates (r = 0.37). These correlations suggest that businesses in some states are more likely to be rehiring former employees, either because of PPP loans or an expected need for more workers, and that some states have more liquid job markets.

State-level plans to start partial or complete reopening also were correlated with greater rebounding in headcount in the last week of April, as would be expected, though many states that did not announce broad reopening plans also showed some gains. A record of these plans was obtained from the New York Times. The average net gain in headcount for states that had announced phased reopening was 0.5%, versus 0.2% for states that have not announced such plans.

Many of the same states that announced reopenings were also the last to announce shelter-in-place or stay-at-home ordinances, and in a few cases did not pass any such ordinances. As a result, we also saw lower overall declines in these states during the trough in these states. Figure 8 below shows weekly change in headcount for states that have announced plans to reopen versus those that had not.

Figure 8: Weekly net change in headcount for states that announced partial reopenings versus those that did not.

April Report - Fig8

Table A3 in the appendix also provides hiring, termination, and layoff statistics for the 50 most populous Metropolitan Areas.

Business Size

In April we continued to see larger declines in headcount among businesses with larger numbers of employees. Table 4 shows these effects for companies of different sizes.

Table 4. Layoff rates for employers of different sizes (# of employees) in April.

SizeTerminationsLayoffs% Change in Terminations% Change in layoffsNet change in headcount
0-44.211.64-0.130.12-0.81
5-95.091.63-0.38-0.42-1.12
10-245.041.49-0.52-0.58-1.02
25-495.431.62-0.56-0.68-1.59
50+7.113.24-0.37-0.23-3.39

About Gusto

Gusto is a modern, online people platform that helps small businesses take care of their teams. In addition to full-service payroll, Gusto offers health insurance, 401(k)s, compliance and expert HR, and more. The company serves over 100,000 businesses nationwide and has offices in Denver, New York City, and San Francisco.

Appendix 

Table A1: Hires, terminations, and layoffs per 100 employees for the month of April ‘20 by industry, ranked by net change in headcount by industry.

IndustryHiresTermsLayoffs% Change in terms  vs. March% Change in layoffs vs. MarchNet change in headcount
Arts & Entertainment2.7272.29-38%-32%-4.28
Sports & Recreation3.167.432.4-46%-47%-4.26
Food & Beverage5.819.413.57-53%-58%-3.6
Other Personal Services3.696.873.15-32%-13%-3.19
Accounting2.585.352.3211%239%-2.77
Education3.385.692.28-22%-3%-2.31
Communications2.724.933.05-37%11%-2.22
Salon & Spa2.314.471.64-66%-71%-2.16
Non-Profits & Associations2.24.191.14-10%50%-1.98
Other Professional Services4.625.782.09-37%-19%-1.16
Real Estate3.324.221.24-32%-41%-0.9
Healthcare & Social Assistance4.064.681.37-40%-36%-0.62
Legal2.633.130.75-28%-42%-0.5
Transportation7.758.152.78-20%-26%-0.39
Manufacturing5.025.162.11-40%-45%-0.14
Technology3.423.361.25-20%3%0.06
Retail6.316.251.97-42%-51%0.07
Insurance3.773.630.84-34%-43%0.14
Construction5.725.551.46-29%-30%0.17
Wholesale4.464.241.82-48%-54%0.21
Consulting4.614.191.53-31%-14%0.42
Finance3.63.121.07-41%-46%0.49
Facilities11.69.261.79-25%-31%2.34

Table A2: Hires, terminations, and layoffs per 100 employees for the week of April 27, 2020, ranked by net change in headcount by industry.

IndustryHiresTermsLayoffs% Change in hires vs. March% Change in terminations vs. March% Change in layoffs vs. MarchNet change in headcount
Education1.112.120.7139%54%-18%-1.01
Non-Profits & Associations0.560.940.13-4%97%89%-0.38
Other Personal Services1.31.380.5523%70%150%-0.08
Arts & Entertainment110.4534%40%116%0
Other Professional Services1.711.690.4371%69%11%0.02
Salon & Spa1.281.250.5691%147%338%0.03
Communications0.920.880.2978%79%33%0.04
Accounting0.860.770.0629%-33%-88%0.09
Sports & Recreation1.551.430.2946%-9%-14%0.11
Finance0.830.680.23%-9%6%0.15
Legal0.860.570.119%-14%48%0.29
Real Estate1.020.720.1633%8%-15%0.3
Technology0.970.660.236%2%-8%0.31
Transportation2.31.940.3520%47%-3%0.36
Insurance1.130.750.055%5%-56%0.39
Manufacturing1.61.190.3817%11%56%0.41
Consulting1.510.950.2131%21%-3%0.56
Healthcare & Social Assistance1.440.870.1339%22%0%0.57
Retail1.741.120.20%7%-3%0.62
Construction1.751.080.226%-7%-22%0.67
Food & Beverage2.51.770.4952%22%48%0.73
Wholesale1.590.730.1743%-11%-34%0.86
Facilities3.632.040.356%34%-2%1.59

Table A3: Hires, terminations, and layoffs per 100 employees across the most populous 50 Metropolitan Statistical Areas for the month of April 2020, ranked by net change in headcount.

IndustryHiresTermsLayoffs% Change in terms vs. March% Change in layoffs vs. MarchNet change in headcount
Buffalo-Cheektowaga-Niagara Falls, NY2.959.977.580.314.86-7.02
Indianapolis-Carmel-Anderson, IN4.427.623.84-0.040.89-3.2
Seattle-Tacoma-Bellevue, WA3.656.692.62-0.31-0.34-3.04
Pittsburgh, PA4.717.754.64-0.131.49-3.03
New York-Newark-Jersey City, NY-NJ-PA3.456.392.89-0.47-0.36-2.94
New Orleans-Metairie, LA4.477.221.23-0.37-0.82-2.75
Orlando-Kissimmee-Sanford, FL3.546.091.06-0.26-0.46-2.55
San Jose-Sunnyvale-Santa Clara, CA2.715.232.41-0.110.4-2.52
Charlotte-Concord-Gastonia, NC-SC3.966.383.42-0.041.18-2.42
Las Vegas-Henderson-Paradise, NV5.287.293.45-0.31-0.21-2.01
Richmond, VA3.85.721.35-0.41-0.57-1.93
Minneapolis-St. Paul-Bloomington, MN-WI3.975.891.19-0.31-0.63-1.92
Austin-Round Rock, TX4.185.992.48-0.28-0.18-1.81
Detroit-Warren-Dearborn, MI4.135.863.34-0.250.62-1.72
Raleigh, NC3.425.021.81-0.20.98-1.6
Milwaukee-Waukesha-West Allis, WI3.725.281.21-0.27-0.19-1.56
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD3.645.162.19-0.54-0.62-1.52
Jacksonville, FL4.666.132.130.23.19-1.48
Rochester, NY3.264.732.42-0.190-1.47
Houston-The Woodlands-Sugar Land, TX4.215.551.73-0.38-0.37-1.34
Baltimore-Columbia-Towson, MD3.334.671.1-0.36-0.24-1.34
Sacramento–Roseville–Arden-Arcade, CA3.644.941.21-0.3-0.57-1.3
Chicago-Naperville-Elgin, IL-IN-WI4.025.231.96-0.34-0.26-1.21
San Francisco-Oakland-Hayward, CA3.654.831.87-0.4-0.38-1.18
Oklahoma City, OK4.65.751.41-0.19-0.27-1.15
Riverside-San Bernardino-Ontario, CA3.935.052.4-0.270.22-1.12
Providence-Warwick, RI-MA3.84.871.9-0.29-0.4-1.07
Columbus, OH5.296.121.17-0.33-0.62-0.83
Portland-Vancouver-Hillsboro, OR-WA3.974.81.67-0.51-0.69-0.83
San Diego-Carlsbad, CA3.594.391.7-0.57-0.42-0.79
Denver-Aurora-Lakewood, CO4.45.171.79-0.42-0.45-0.77
Birmingham-Hoover, AL2.833.570.15-0.45-0.7-0.74
Los Angeles-Long Beach-Anaheim, CA3.644.381.82-0.45-0.44-0.74
Phoenix-Mesa-Scottsdale, AZ4.715.331.25-0.37-0.35-0.62
St. Louis, MO-IL7.167.772.140.280.8-0.61
Miami-Fort Lauderdale-West Palm Beach, FL4.364.861.2-0.55-0.64-0.5
Atlanta-Sandy Springs-Roswell, GA3.74.171.1-0.47-0.47-0.46
San Antonio-New Braunfels, TX5.035.321.29-0.41-0.45-0.3
Washington-Arlington-Alexandria, DC-VA-MD-WV3.854.121.3-0.52-0.61-0.27
Memphis, TN-MS-AR6.766.982.13-0.030.52-0.22
Hartford-West Hartford-East Hartford, CT4.064.240.43-0.57-0.91-0.17
Salt Lake City, UT5.415.51.91-0.3-0.56-0.09
Dallas-Fort Worth-Arlington, TX5.265.231.46-0.43-0.430.02
Tampa-St. Petersburg-Clearwater, FL5.825.761.34-0.34-0.320.07
Kansas City, MO-KS5.395.160.99-0.38-0.660.23
Boston-Cambridge-Newton, MA-NH4.173.561.19-0.53-0.640.61
Cincinnati, OH-KY-IN4.273.641.08-0.41-0.570.63
Nashville-Davidson–Murfreesboro–Franklin, TN7.055.942.06-0.37-0.151.11
Virginia Beach-Norfolk-Newport News, VA-NC5.333.820.67-0.30.341.51
Louisville/Jefferson County, KY-IN5.73.623.07-0.67-0.112.08
Cleveland-Elyria, OH7.443.550.89-0.53-0.393.9

Methodology

The analyses described in this report were based on two separate datasets obtained from Gusto’s small business payroll, benefits, and HR applications. The first dataset used payroll data to capture employee hours, wages, and furloughing (Work Reduction & Furlough). The second dataset used data from employers hiring and terminating employees (Hiring & Termination).

Work Reduction & Furlough

Employees in our dataset were labeled as furloughed if they were employed for the entirety of February, March, and April (had no termination effective during that time), and either 1) had earned money in the final paycheck of the preceding month but had not earned money in the final paycheck of the following month (e.g. final paycheck of February was non-zero, and the final paycheck of March was $0), or 2) met the definition for part 1 and also continued to earn $0 on payrolls in the subsequent month, thereby on a continued furlough. Our furlough data in this April report only looks at furloughs that were active in April and were instigated in March or April, not furloughs that began earlier and have continued through this period.

Non-terminated, non-furloughed employees were labeled as work reduced for the April report if the total hours of their April paychecks were less than 90% of the hours on their February (used as a benchmark for pre-COVID) paychecks. This calculation was done for both 2019 and 2020, where 2019 was used to represent the counterfactual case (what would have happened).

Presumed COVID-related differences were calculated by subtracting the rates of termination, furlough, and work reduction in 2019 from the same numbers in 2020. This rate difference was used to calculate the number of additional employees affected by each cost-saving strategy. The average dollars saved per affected employee was calculated as the difference between total February and March payrolls, divided by the number of employees, for each type of affected employee, and this dollar amount was multiplied by the COVID-related count of impacted employees to calculate the total dollars saved by each strategy.

Hiring & Termination:

A given employee on Gusto can have multiple “employments,” since an employer can potentially hire, terminate, and rehire the same employee multiple times. In our Hiring & Termination dataset, a hire corresponded to an employer creating a new employment with a hiring date, and a termination corresponded to the entry of a termination date for a given employment. Layoffs corresponded to terminations where the employer listed the reason for the termination as a layoff” (one of the choices from a standardized list in Gusto’s termination flow). In order to capture a more time-sensitive view of employer activities, we recorded hires, terminations, and layoffs on the date that they were entered into the system, rather than their effective date. Terminations are also coded as voluntary or involuntary

Employee hires, layoffs, and terminations were aggregated weekly and monthly for a given company and work location. Hiring, termination, and layoff rates reported in this document are based on the number of times each event occurred in a given week or month, divided by the number of employees who were employed at the beginning of the period.

Locations reported in this document are based on the most recent work location associated with the employee. Industries reported in this document are based on self-report from customers within Gusto’s product.


[1] Values provided in this report were only included for categories (e.g., state, industry, metropolitan area) where we had at least 1,000 employees.

[2] This report compares exempt and nonexempt workers, and excludes the smaller category of “salaried non-exempt” from the analysis.

[3] This report adds separate voluntary and involuntary termination rates throughout most figures. Termination reasons are only available consistently since February 2020.

Daniel Sternberg
Daniel Sternberg Daniel Sternberg leads the Data Science team at Gusto. Daniel is passionate about using Gusto’s payroll and employment data to help small businesses thrive. Prior to joining Gusto, Daniel earned a PhD in Cognitive Psychology, studying human learning first academically and then in industry. He lives in San Francisco with his wife and daughter.

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