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Small Business Workforce Trends in the Quarantine Economy, October ’20

Sarah Gustafson Data Scientist, Gusto 
Small Business Workforce Trends in the Quarantine Economy, October '20 - Gusto

This post was co-authored by Sarah Gustafson & Luke Pardue.

With the arrival of cold weather, COVID-19 cases spiking in many parts of the country, and diminished prospects of immediate government relief, small businesses are facing a winter unlike any other—and they are doing so at a time when their economic position is historically fragile.

New proprietary data from Gusto—the people platform offering full-service payroll, benefits, compliance, and expert HR services for 100,000+ small businesses nationwide—for the month of October ‘20 shows that small business headcount growth remains low with just a 1.4% increase from September ‘20. This marks the fourth straight month of growth below 1.5%, and cold weather threatens to wipe out many of the recent job gains since March and in the coming months. A recent Gusto analysis found that without additional aid, 1.4 to 2.8 million jobs in the US are at risk from the arrival of winter. 

This report analyzes leading indicators and changes to employment at small businesses for the full month of October 2020. The findings reported below represent data points with meaningful sample sizes, 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 Findings

  • Recovery remains subdued, putting the economy in a precarious position heading into winter: Small business headcount growth has become stagnant: +1.4% in October; 1.1% in September; +1.0% in August; and +1.2% in July. Additionally, re-hiring of furloughed workers has largely stalled as business owners wait to see what winter has in store. For workers who have been furloughed at all since the pandemic began, only 36% have returned to work and 21% of those remain in limbo and are still furloughed.
  • Cities in the Southeast experienced the strongest headcount growth in October: 7 of the top 10 cities that saw the biggest growth are located in the South. Memphis has topped the list for 2 straight months in headcount growth with +4.53% in October and +3.54% in September.  
  • Headcount growth in 2020 remains 50% lower than prior years: Headcount across all industries dropped precipitously in spring ‘20, bottoming out at -5% in early April. By October ‘20, headcount had recovered to +5% above pre-COVID levels, but small businesses still have not nearly made up for ground lost due to the pandemic: when looking at headcount growth in 2020 versus expectations based on the 3 prior years of data, this year’s headcount is 50% behind where it should be.  

October ’20 Small Business Trends

Workers on Furlough 38% Higher than Last Year

Table 1 below shows the month-by-month employment outcome for workers who were employed in February of 2019 and 2020. Furlough rates, termination rates, and the rate of workers experiencing a reduction in hourly pay rate of 10% or more have remained persistently higher than the same period last year since spring. 

Of workers who were employed prior to COVID in February ‘20, 5% of those workers are furloughed as of October ‘20. While this furlough rate has continued to come down from the peak in April ‘20 (9.5%), it still remains elevated compared to a typical year. The furlough rate observed in October ‘20 is 38% higher than the furlough rate in October of last year. 

Table 1. Rates of employer actions affecting employee wages for 2019 and 2020 as compared to February of the same year.

table1

Furloughs in 2020 Lasting Longer than Furloughs in the Past

For workers who have been furloughed since March ‘20, only 36% have returned to work by October ‘20. A startling number of workers furloughed this year remain in limbo as of October; 21% of workers furloughed since March are still furloughed. Table 2 below shows the employment outcomes for furloughed workers in 2020 versus 2019. We can assume that 2019 is representative of a more “normal” economy, and therefore it can be used as the counterfactual for if the pandemic had not occurred. The rate of workers remaining furloughed by October 2019 was only 16%, indicating that the rate of furloughed workers remaining in furlough is 32% higher than last year. 

Terminations have been a less likely outcome resulting from a furlough in 2020, probably due in part to PPP loans that allowed employers to bring their workers back quickly in the spring. This also reflects the “wait and see” mentality of employers who may not have clarity on whether they will eventually be able to rehire their furloughed employees due to the pandemic and uncertainty around additional government aid.

Table 2.  Employment Outcomes by October for Workers Furloughed Between March & September in 2020 and 2019.

table2

Terminations and Hires Both Fall in October

As shown by the top black line in Figure 1 below, overall small business headcount remains subdued with monthly growth up slightly from overall headcount growth in September.  

The top line of Figure 1 below shows the month-over-month percent change in overall headcount across small businesses—October grew by +1.4% (September was +1.1%, August was +0.9%). The bottom panel of Figure 1 charts the components of the net hiring rate: hirings and terminations. Both the hiring rate and termination rates among small businesses fell in October, although the termination rate fell slightly more, leading to a rise in the net hiring rate.

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

fig1

Typical Seasonal Trends in Hiring & Terminations in Q4 2020s

Based on employment data over the last several years, we generally expect to see a seasonal decline in employee turnover (reduction in both hiring and terminations) from October through December, followed by a spike in turnover in January.  

One month into the fourth quarter, these seasonal trends have indeed re-appeared, although there remains significant uncertainty surrounding the future path of hiring and terminations. As the temperature drops, COVID-19 case counts spike around the country, and further government aid appears unlikely in the near-term, employers may be less able than ever to be able to maintain their workforce.  

Figure 2 below shows both hiring and termination rates (6.1% and 4.7%, respectively) are down in October ‘20 compared to the same month last year. Hiring is down -2% relative to October ‘19, and terminations are much lower than the same month last year (-15% lower than October ‘19).  

Figure 2.  Monthly net change in headcount and hiring, termination, and layoff statistics: 2017-present

fig2

Gains in Employment Remain Below Expectations 

Between March and October, headcount overcame a deep deficit to surpass its pre-COVID levels by 5.8% (as shown in the 2020 line in black in Figure 3). However, 5.8% is still far below the growth we would expect in a typical year. In fact, it’s 50% lower than the prior 3-year average headcount growth between March and October. 

Figure 3. Cumulative % change in headcount between the beginning of March and end of October from 2017-2020.

fig3

Many Industries Still Have Not Made Up Headcount Losses

Headcount growth in those industries hit hardest by the pandemic remains slow. Employment in Arts & Entertainment, Food & Beverage, Salon & Spa, Sports & Recreation, and Tourism are still operating with fewer employees than they were at the beginning of March. Salon & Spa has fared the best since July, nearly recovering to pre-pandemic headcount levels.

Headcount among Accommodations employers continued its post-Labor Day decline. This dip in number of workers is reflective of a seasonal trend, but the impact of this wave of layoffs is especially stark given that Accommodations employment in summer 2020 was already extremely hampered by the pandemic.

Retail, which has seen +8.4% overall growth in headcount compared to early March, has fared better than many other non-desk-based industries. Its growth eclipsed that of the catch-all “All Other” bucket (comprising sectors such as Technology, Legal, Professional Services, Construction, etc.), many of them desk-based and less reliant on foot traffic, which have fared better and have experienced +8.2% growth on average since March.  

Figure 4. Cumulative change in headcount since the week of March 2, 2020 across industries heavily affected by COVID and all others.

fig4

Winter Threatens Recoveries in Retail, Food & Beverage

The threat posed by colder weather is particularly acute in two industries that have experienced dramatically different recoveries over 2020. Figure 5 plots the cumulative change in headcounts relative to March—as in Figure 4—but compares this year’s trend to 2019, as a measure of industry-specific potential growth.  

Retail businesses (left panel) were hit hard during the initial phases of this pandemic as non-essential businesses were forced to shutter and state and local governments instituted capacity restrictions. Within the first month of the pandemic, this industry experienced a 5% drop in headcount. However, as businesses adjusted services and customers returned, the retail industry recovered quickly and has been able to rebound significantly, almost completely catching up to the growth rate seen in 2019.

On the other hand, Food & Beverage (left panel) saw a drop in headcount of over 15% in one month. Although most sectors of the economy have experienced modest growth since March, employment in Food & Beverage has been much slower than in Retail, with headcount still 158% below the growth rate seen in 2019. 

The economic progress in both industries, however, is threatened by both the drop in temperature and spiking COVID-19 case counts in many parts of the county. Retailers, bars, and restaurants made adjustments that relied in large part on outdoor, socially-distant spaces during spring and summer. As the weather cools down across much of the country and many businesses do not have funds for a new round of adjustments, these businesses could be forced to shed many jobs gained back since March. Previous Gusto analysis found that, without additional aid, 1.4-2.8 million jobs across the country are at risk from the arrival of winter. 

Cumulative changes in headcount for 2019 and 2020 across additional industries are provided in Appendix Table A4. 

Figure 5: Comparing Recovery Trends in Two Industries: Headcount Growth Relative to March, for years 2019 and 2020.  

fig5

Industry Trends

Small business headcount grew again across nearly all industries in October, at a pace largely similar to those seen in September and August. A few industries saw a reduction in headcount in August compared to September (Accommodations and Government), and Education returned to small headcount growth after contracting in August and September. On the whole, companies across industries are growing. Some of the largest gains were made in the following industries:

  1. Other Professional Services (+2.5%)
  2. Retail (+2.2%)
  3. Transportation (+2.1%)
  4. Wholesale (+2.1%)

Figure 6. Monthly Net Changes in Headcount: August-October

fig6

Geographic Trends

Similar to August, nearly all U.S. states with at least 1,000 employees on the Gusto platform showed net increases in headcount for the month of October. There were a handful of exceptions, but the only state with more than -1% decline was Maine (-1.4%). Figure 7 maps the month-over-month growth rates for October across the country, binned by growth rate into five roughly equal groups. New England and the Mid-Atlantic states experienced particularly slow growth this month, while the South-Central U.S. (Texas, Oklahoma, and Arkansas) has experienced some of the relatively fastest headcount growth. Indeed, the Southern US—a region not particularly exposed to the looming threat of colder weather—has experienced some of the fastest growth across the country. 12 of the 15 fastest-growing cities are located in the South (see Appendix Table A2).

To offer a longer-term view of the geographic trends, Figure 8 maps the cumulative change in headcount from March to October across the country. Although headcount in Maine, for instance, declined significantly in October, this state has seen one of the largest cumulative increases in employment since March (+13.3%).

Figure 7. Net percentage change in headcount from September-October

fig7

Figure 8. Cumulative Percentage Change in Headcount from March-October

fig8

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 by industry, for the month of October ‘20, ranked in decreasing order by net change in headcount.

IndustryHiresTerminationsLayoffs% Change in hiring vs. marchPercentage change in terminationsPercentage change in layoffsNet change in employees
Other Professional Services8.135.660.22-0.02-0.12-0.452.47
Retail7.305.110.270.00-0.140.012.19
Transportation9.367.230.670.07-0.020.782.13
Wholesale5.543.480.330.100.060.352.06
Insurance5.323.460.09-0.12-0.27-0.401.87
Healthcare & Social Assistance6.674.900.15-0.09-0.10-0.011.77
Manufacturing6.484.750.310.000.000.001.72
Communications4.602.970.380.08-0.010.091.63
Finance4.492.880.20-0.10-0.020.041.61
Consulting4.753.180.330.010.090.771.57
Technology4.112.550.22-0.02-0.100.131.56
Accounting4.012.500.170.130.140.781.51
Salon & Spa6.355.210.37-0.18-0.200.591.15
Construction6.195.060.33-0.04-0.10-0.221.13
Other Personal Services5.764.660.290.07-0.100.461.10
Facilities9.948.910.15-0.03-0.13-0.491.03
Non-Profits & Associations3.532.570.09-0.38-0.44-0.670.97
Legal3.762.840.12-0.06-0.09-0.120.92
Automotive7.857.100.10-0.030.05-0.270.75
Real Estate4.053.330.17-0.05-0.07-0.080.72
Sports & Recreation6.826.120.23-0.07-0.30-0.660.71
Arts & Entertainment5.164.520.270.170.11-0.610.63
Education5.595.010.24-0.18-0.280.280.58
Food & Beverage9.929.440.51-0.07-0.060.000.48

Table A2: Hires, terminations, and layoffs per 100 employees across the most populous 50 Metropolitan Statistical Areas for the month of October ‘20, ranked in decreasing order by net change in headcount.


MSA

Hires

Terminations

Layoffs
Percentage change in hiresPercentage change in terminationsPercentage change in layoffsNet change in employees
Memphis, TN-MS-AR10.836.300.240.150.052.754.53
St. Louis, MO-IL8.224.780.040.06-0.23-0.683.44
Orlando-Kissimmee-Sanford, FL8.275.000.340.07-0.170.383.27
Raleigh, NC6.793.720.09–-0.02-0.41-0.703.07
Tampa-St. Petersburg-Clearwater, FL7.835.020.230.20-0.031.462.82
Nashville-Davidson–Murfreesboro–Franklin, TN7.574.790.17-0.04-0.24-0.322.78
Phoenix-Mesa-Scottsdale, AZ8.215.550.100.24-0.05-0.332.67
Detroit-Warren-Dearborn, MI6.854.240.06-0.12-0.27-0.752.61
Indianapolis-Carmel-Anderson, IN6.493.900.070.02-0.25-0.642.59
New Orleans-Metairie, LA6.674.130.11-0.20-0.27-0.052.54
San Antonio-New Braunfels, TX7.965.500.16-0.02-0.03-0.042.46
Birmingham-Hoover, AL4.982.680.040.01-0.48-0.812.30
Riverside-San Bernardino-Ontario, CA6.974.720.520.10-0.120.102.25
Houston-The Woodlands-Sugar Land, TX7.044.890.160.03-0.23-0.622.15
Sacramento–Roseville–Arden-Arcade, CA6.764.730.32-0.16-0.05-0.112.04
Charlotte-Concord-Gastonia, NC-SC6.644.680.09-0.02-0.300.141.96
Miami-Fort Lauderdale-West Palm Beach, FL5.994.090.24-0.01-0.13-0.261.90
Cleveland-Elyria, OH6.684.850.060.04-0.19-0.811.84
Portland-Vancouver-Hillsboro, OR-WA6.424.600.430.01-0.160.751.83
Dallas-Fort Worth-Arlington, TX6.804.980.120.02-0.10-0.251.82
Salt Lake City, UT5.363.670.25-0.06-0.422.411.68
Los Angeles-Long Beach-Anaheim, CA5.533.900.46-0.04-0.030.151.63
Providence-Warwick, RI-MA6.054.470.12-0.13-0.270.011.57
Columbus, OH5.834.350.24-0.15-0.100.501.49
Baltimore-Columbia-Towson, MD6.184.700.20-0.01-0.09-0.231.48
Chicago-Naperville-Elgin, IL-IN-WI5.183.710.240.09-0.13-0.101.47
Denver-Aurora-Lakewood, CO6.204.810.180.03-0.010.051.40
Hartford-West Hartford-East Hartford, CT4.943.550.20-0.37-0.43-0.291.38
Minneapolis-St. Paul-Bloomington, MN-WI5.273.960.20-0.08-0.170.271.31
Boston-Cambridge-Newton, MA-NH4.873.680.18-0.19-0.29-0.291.20
Pittsburgh, PA6.415.220.08-0.080.19-0.231.19
Washington-Arlington-Alexandria, DC-VA-MD-WV4.903.720.28-0.16-0.160.331.18
Austin-Round Rock, TX6.245.110.15-0.04-0.02-0.201.12
San Francisco-Oakland-Hayward, CA4.753.720.350.02-0.07-0.221.03
New York-Newark-Jersey City, NY-NJ-PA6.045.040.52-0.04-0.160.251.00
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD5.564.640.10-0.01-0.020.470.92
Kansas City, MO-KS5.834.910.21-0.05-0.061.900.92
Buffalo-Cheektowaga-Niagara Falls, NY4.023.130.00-0.43-0.45-1.000.89
San Jose-Sunnyvale-Santa Clara, CA4.093.210.22-0.15-0.10-0.200.89
Atlanta-Sandy Springs-Roswell, GA5.965.220.090.00-0.09-0.830.74
Louisville/Jefferson County, KY-IN4.483.780.20-0.21-0.242.890.70
Seattle-Tacoma-Bellevue, WA5.855.180.48-0.09-0.070.240.66
Cincinnati, OH-KY-IN6.035.360.26-0.030.151.640.66
San Diego-Carlsbad, CA5.214.700.36-0.090.03-0.130.51
Las Vegas-Henderson-Paradise, NV6.286.000.26-0.050.08-0.470.28
Richmond, VA5.084.800.14-0.18-0.140.420.27
Milwaukee-Waukesha-West Allis, WI5.485.370.21-0.03-0.214.830.10
Virginia Beach-Norfolk-Newport News, VA-NC6.406.340.17-0.18-0.440.650.07
Oklahoma City, OK6.716.710.13-0.26-0.04-0.590.00
Jacksonville, FL6.226.270.25-0.15-0.064.34-0.04

Table A3: Monthly Net % Change in Headcount since March ‘20, Broken Down by Industry

Sector2020-03-012020-04-012020-05-012020-06-012020-07-012020-08-012020-09-012020-10-01
Sports & Recreation-9.16-5.392.114.89-1.20-1.31-1.370.71
Accommodations-15.51-4.579.308.921.89-0.37-6.83-1.98
Arts & Entertainment-5.79-5.070.850.740.70-1.450.340.63
Food & Beverage-12.89-3.864.553.991.240.370.650.48
Education-4.17-1.952.841.390.45-0.89-0.160.57
Salon & Spa-8.21-2.333.082.620.260.311.231.15
Other Personal Services-5.92-3.203.051.601.58-0.020.171.10
Accounting-1.76-2.591.620.80-0.270.601.361.51
Unknown-2.19-1.291.681.460.700.370.150.74
Non-Profits & Associations-0.89-1.681.640.500.430.751.100.97
Real Estate-2.22-1.092.651.340.450.600.670.72
Communications-3.33-2.142.601.021.281.331.261.63
Legal-0.87-0.452.401.640.781.200.860.92
Other Professional Services-2.81-1.262.711.521.341.611.812.49
Retail-4.980.063.942.611.770.781.392.19
Consulting-1.980.322.981.310.871.401.791.57
Wholesale-3.190.193.331.481.661.401.772.06
GovernmentNANA2.412.613.710.95-0.36-0.05
Technology-0.160.082.471.541.221.221.391.56
Manufacturing-3.540.043.733.231.361.401.731.72
Construction-1.740.444.263.001.141.120.821.12
Finance-0.890.232.452.451.311.572.041.61
Healthcare & Social Assistance-2.58-0.753.422.582.322.291.921.78
Transportation-3.21-0.503.823.283.221.751.372.13
Insurance-0.660.183.452.471.471.911.311.87
Facilities-0.291.936.603.761.300.45-0.031.03

Table A4: Monthly Net % Change in Headcount since March ‘20, Broken Down by State

State2020-03-012020-04-012020-05-012020-06-012020-07-012020-08-012020-09-012020-10-01
NY-7.47-3.183.191.771.070.880.190.77
NM-6.42-0.983.403.320.340.65-0.690.37
WY-3.73-2.292.703.21-0.17-0.160.96-0.30
ND-4.46-0.393.280.43-0.702.54-0.27-0.07
WA-3.96-2.701.942.380.900.690.850.62
DC-4.97-1.071.881.231.651.160.700.52
HI-5.470.003.05-0.050.090.750.932.14
VT-3.26-1.843.280.812.46-2.862.700.40
MS0.20-0.062.00-1.431.74-1.161.230.17
CA-3.36-1.232.171.180.710.821.311.31
OR-5.23-1.183.602.161.090.571.111.70
IA-0.750.171.860.36-1.880.062.012.27
IL-3.15-0.902.142.791.451.110.501.14
MA-3.780.672.102.231.760.390.891.01
CT-2.78-0.552.611.752.100.191.020.94
LA-4.84-1.243.282.401.64-0.482.282.32
CO-4.35-1.023.592.561.631.180.691.13
NJ-5.33-0.942.994.002.151.340.990.98
MN-3.28-2.083.393.511.750.960.861.26
GA-2.71-0.473.641.751.461.630.320.90
NV-4.00-1.633.382.742.052.920.550.58
MD-1.88-0.612.901.342.100.051.561.51
AL-1.61-0.342.403.180.151.051.031.29
FL-3.00-1.003.812.041.350.711.172.08
WI-4.090.373.725.042.07-0.450.130.46
PA-5.55-1.153.453.611.401.402.321.81
TX-2.96-0.934.252.820.960.601.081.63
SC-2.39-1.793.643.720.840.910.342.25
TN-3.570.053.731.540.081.042.462.56
OH-2.720.964.192.471.300.380.790.68
NE-7.011.803.740.353.242.571.042.48
VA-3.16-0.273.393.652.041.270.410.90
IN-3.25-1.753.933.051.471.220.942.85
DE-3.76-4.224.0713.800.550.49-1.75-0.52
AR-1.56-0.373.671.970.691.121.581.57
NC-2.76-0.923.852.352.021.311.021.90
AZ-2.96-0.323.442.021.481.821.202.51
MT-2.99-1.918.384.571.11-0.411.160.66
KS-3.962.085.543.990.200.551.471.37
KY-3.921.874.143.612.150.702.140.66
MO-0.67-0.233.172.751.291.981.871.36
OK-0.550.021.333.302.512.461.381.24
RI-2.88-1.294.365.243.191.510.411.26
ME-4.430.476.267.442.83-0.201.37-1.40
NH-3.980.995.704.573.29-0.031.590.64
UT-3.130.985.133.190.922.470.812.56
MI-2.06-0.384.614.251.872.370.971.50
ID-2.19-0.703.784.570.811.035.171.22

Figure A1: Cumulative % change in headcount of Accommodations workers between the beginning of March and end of October from 2019-2020. 

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). When we define outcomes, we’re assigning one outcome per employee per month, which can block certain outcomes (Outcome Rank Ordering).

Work Reduction & Furlough

Employees in our dataset were labeled as furloughed if they were employed for the entirety of February, March, April and May (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 hours reduced for the June report if the total hours of their June 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.  

Monthly reporting of termination data may differ slightly from prior reporting, as employers often log a termination several days or weeks after the employee was actually released. For example, more than a third of terminations that were created (logged in the system) in May were actually effective before May. Data in this report may also differ slightly from prior reports due to methodology improvements. Further employment changes are incorporated into this month’s analysis, such as reduction to hourly pay rate. We also separately categorized employees that worked for companies who “paused” their payroll service with Gusto. Employees that fall into this new bucket may have previously not been labeled as impacted, or may have been attributed as “hours reduced” for a given month.

When we assign an outcome to an employee for a given month, we follow this rank ordering:

  1. Employee Terminated
  2. Company Suspended/Paused
  3. Employee Furloughed
  4. Hours Reduced
  5. Hourly Pay Rate Reduced

What this means, in practice, is that if an employee’s hourly pay rate was reduced early in the month and then they were furloughed, we’ll count them toward the “Furloughed” outcome but not the “Hourly Pay Rate Reduced” outcome. The further down the rank order the outcome is, the more likely we are to undercount it in favor of something else.

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.

Sarah Gustafson
Sarah Gustafson Sarah Gustafson is a member of the Data Science team at Gusto. Sarah works with Gusto's platform data to help solve problems facing small businesses and help them survive and thrive, especially in this unprecedented economic landscape. Prior to Gusto, Sarah worked in risk management and statistical modeling for several large financial institutions. She studied math and statistics at Duke University and University of California Davis.

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