
2024’s Economy Lays the Groundwork for a Steady 2025
By Nich Tremper
Daniel SternbergHead of Data Science, Gusto October 14, 2020
This post was co-authored by Sarah Gustafson and Luke Pardue.
With ongoing gridlock over extended relief creating new waves of economic uncertainty, concerns for a potential COVID surge during fall flu season, and cold weather looming on the horizon with the potential to limit outdoor operations, small businesses are being forced to make a new round of urgent, and oftentimes difficult decisions to stay afloat.
New platform 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 September ‘20 shows that small business headcount growth remains low with just a 1.1% increase from August ‘20. Overall, current headcount growth at small businesses is 66% lower than what would be expected based on the average growth rate for the past 3 years. Additionally, an unusually high number of employees remain furloughed.
This report analyzes leading indicators and changes to employment at small businesses for the full month of September 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.
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 September ‘20. While this furlough rate has continued to come down from the peak in April ‘20 (9.5%), it still remains remarkably elevated compared to a typical year. The furlough rate observed in September ‘20 is 31% higher than the furlough rate in September of last year.
March ‘19 | April ‘19 | May ‘19 | June‘19 | July‘19 | Aug ’19 | Sept ’19 | March ‘20 | April ’20 | May ‘20 | June‘20 | July‘20 | Aug ’20 | Sept ’20 | |
Furlough rate | 3.4% | 3.0% | 3.4% | 4.3% | 4.2% | 3.8% | 3.9% | 4.1% | 9.5% | 6.8% | 6.1% | 5.6% | 5.2% | 5.0% |
Termination rate | 4.1% | 7.6% | 11.1% | 14.3% | 17.0% | 19.8% | 22.0% | 8.6% | 11.7% | 14.2% | 16.9% | 19.4% | 21.7% | 23.0% |
Reduction in hourly pay rate of at least 10% | 2.4% | 2.3% | 2.5% | 2.3% | 2.4% | 2.5% | 2.2% | 2.2% | 3.1% | 3.5% | 3.3% | 3.2% | 2.7% | 2.8% |
Reductions in hours of at least 10% | 9.7% | 9.6% | 6.9% | 10.1% | 8.6% | 6.0% | 8.8% | 13.5% | 11.5% | 9.5% | 9.1% | 6.4% | 8.6% | 7.5% |
YoY March | YoY April | YoY May | YoYJune | YoYJuly | YoYAug | YoYSept | |
Furlough rate | 20.6% | 214.6% | 97.6% | 40.9% | 33.6% | 35.2% | 30.8% |
Termination rate | 109.8% | 54.5% | 27.2% | 17.7% | 14.2% | 9.6% | 4.7% |
Reduction in hourly pay rate of at least 10% | -7.3% | 31.4% | 37.8% | 42.8% | 29.7% | 11.8% | 27.1% |
Reductions in hours of at least 10% | 38.4% | 19.3% | 38.9% | -10.2% | -24.9% | 44.3% | -14.5% |
For workers who have been furloughed since March ‘20, only 38% have returned to work by September ‘20. A startling number of workers furloughed this year remain in limbo as of September; 22% 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 September 2019 was only 18%, indicating that the rate of furloughed workers remaining in furlough is 23% 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.
Impact | 2020 | 2019 | YoY |
Terminated | 32% | 41% | -23% |
Still furloughed | 22% | 18% | 23% |
Returned to work | 38% | 33% | 14% |
Other | 9% | 8% | 10% |
As shown by the top black line in Figure 1 below, overall small business headcount is stagnating with growth creeping to a crawl at +1.1% in September (up very slightly from +1.0% overall headcount growth in August).
The top line of Figure 1 below shows the month-over-month percent change in overall headcount across small businesses—September grew by 1.1% (August was +1.0%, July was +1.2%)
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.
The year 2020, however, is clearly not adhering to prior year norms. As negotiations for further government funding falter and temperatures across the country dive, employers may be less able than ever to be able to maintain their workforce going into Q4.
Both hiring and termination rates (6.4% and 5.3%, respectively) are down in September ‘20 compared to the same month last year. Hiring is down -4% relative to September ‘19, and terminations are much lower than the same month last year (-15% lower than Sept ‘19).
Between March and September, headcount overcame a deep deficit to surpass its pre-COVID levels by 4% (as shown in the 2020 line in black in Figure 3). Unfortunately, 4% is still far below the growth we would expect in a typical year. In fact, it’s 66% lower than the prior 3-year average headcount growth between March and September.
Headcount growth in those industries hit hardest by the pandemic remains slow. Employment in Arts & Entertainment, Food & Beverage, Salon & Spa, Sports & Recreation, and Tourism have all maintained relatively flat growth since July and are still operating with fewer employees than they were at the beginning of March.
Accommodations headcount lost ground following Labor Day, the official end of summer. 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 +6.1% overall growth in headcount compared to early March, has fared better than many other non-desk-based industries. Its growth, however, is still slightly lower than 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 +6.7% growth on average since March.
The uneven recovery that different sectors of the economy have experienced is clear when looking at 2020 headcount growth versus the same period last year. 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 potential growth.
Food & Beverage (left panel) is an industry that was hit quite hard in April, seeing a drop in headcount of nearly 20% in one month. Despite gains over the summer, headcount is still 152% below the growth rate seen in 2019.
On the other hand, Healthcare & Social Assistance (including daycares, dentist and doctor offices, therapists and counselors, etc.) was also hit relatively hard during the initial phases of this pandemic as dentist offices were forced to close and patients delayed elective procedures. Within the first month of the pandemic, this industry experienced nearly a 10% drop in headcount. However, as offices were able to open and patients returned, the medical industry recovered quickly and has been able to rebound significantly, almost completely catching up to the growth rate seen in 2019.
Cumulative changes in headcount for 2019 and 2020 across additional industries are provided in Appendix Table A4.
Small business headcount grew again across nearly all industries in September, at a pace largely similar to those seen in August and July. A few industries saw a reduction in headcount in September compared to August (Education, Sports & Recreation, and Accommodations), and Arts & Entertainment returned to small headcount growth after contracting in August. On the whole, companies across industries are growing. Some of the largest gains were made in the following industries:
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 September ‘20. There were a handful of exceptions, but the only state with more than 1% decline was Delaware (-1.6%). Figure 7 maps the monthly growth rates for September across the country, binned by growth rate into five roughly equal groups. The Midwest has been the slowest to recover, while the West, initially hit hard, has experienced some of the relatively fastest headcount growth. New York, on the other hand, was also hit quite early by the pandemic, but has seen slower growth.
To offer a longer-term view of the geographic trends, Figure 8 maps the cumulative change in headcount from March to September across the country. While the Mid-Atlantic and West Coast have been recovering quickly this past month, Figure 8 shows that they still have relatively more ground to make up than other regions.
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.
Industry | Hires | Terminations | Layoffs | % Change in hiring vs. march | Percentage change in terminations | Percentage change in layoffs | Net change in employees |
Healthcare & Social Assistance | 7.41 | 5.38 | 0.15 | -0.04 | -0.02 | -0.06 | 2.02 |
Other Professional Services | 8.32 | 6.36 | 0.39 | 0.12 | 0.05 | 0.23 | 1.96 |
Finance | 4.87 | 2.93 | 0.19 | 0.06 | -0.02 | 0 | 1.94 |
Wholesale | 5.34 | 3.45 | 0.26 | -0.05 | -0.15 | -0.4 | 1.89 |
Consulting | 4.69 | 2.91 | 0.18 | -0.03 | -0.17 | -0.37 | 1.78 |
Manufacturing | 6.48 | 4.75 | 0.3 | -0.05 | -0.12 | -0.42 | 1.73 |
Transportation | 8.93 | 7.41 | 0.39 | 0.01 | 0.05 | -0.13 | 1.52 |
Automotive | 8.2 | 6.72 | 0.1 | 0.04 | -0.14 | -0.52 | 1.48 |
Retail | 7.37 | 5.92 | 0.27 | 0.02 | -0.08 | -0.47 | 1.44 |
Insurance | 6.18 | 4.79 | 0.16 | 0.01 | 0.15 | 1.22 | 1.39 |
Technology | 4.2 | 2.82 | 0.2 | -0.04 | -0.1 | -0.35 | 1.38 |
Accounting | 3.57 | 2.22 | 0.09 | -0.07 | -0.31 | -0.68 | 1.36 |
Communications | 4.31 | 3.02 | 0.35 | 0 | 0.03 | -0.05 | 1.29 |
Salon & Spa | 7.85 | 6.57 | 0.24 | 0.18 | 0.04 | -0.5 | 1.28 |
Non-Profits & Associations | 5.62 | 4.64 | 0.27 | 0.25 | 0.19 | 0.23 | 0.98 |
Construction | 6.5 | 5.59 | 0.45 | -0.01 | 0.02 | -0.06 | 0.91 |
Food & Beverage | 10.79 | 9.89 | 0.51 | -0.07 | -0.11 | -0.39 | 0.91 |
Legal | 3.97 | 3.11 | 0.14 | -0.09 | -0.01 | -0.26 | 0.86 |
Real Estate | 4.3 | 3.66 | 0.19 | -0.01 | -0.03 | -0.28 | 0.64 |
Other Personal Services | 5.54 | 5.22 | 0.19 | -0.04 | -0.09 | -0.45 | 0.32 |
Arts & Entertainment | 4.44 | 4.17 | 0.71 | -0.24 | -0.28 | 0.12 | 0.27 |
Facilities | 10.27 | 10.21 | 0.23 | -0.07 | -0.04 | -0.23 | 0.06 |
Education | 6.64 | 6.75 | 0.18 | -0.05 | -0.14 | -0.62 | -0.1 |
Sports & Recreation | 7.4 | 8.48 | 0.67 | 0.2 | 0.12 | -0.17 | -1.08 |
MSA | Hires | Terminations | Layoffs | Percentage change in hires | Percentage change in terminations | Percentage change in layoffs | Net change in employees |
Memphis, TN-MS-AR | 9.56 | 6.02 | 0.07 | 0.05 | -0.25 | -0.84 | 3.54 |
Sacramento–Roseville–Arden-Arcade, CA | 8.03 | 4.95 | 0.36 | 0.01 | -0.1 | 0.23 | 3.08 |
New Orleans-Metairie, LA | 8.34 | 5.63 | 0.12 | 0 | -0.05 | 1.88 | 2.71 |
Pittsburgh, PA | 6.92 | 4.37 | 0.11 | 0.17 | -0.3 | -0.5 | 2.55 |
San Antonio-New Braunfels, TX | 8.15 | 5.67 | 0.17 | 0.3 | -0.2 | -0.41 | 2.48 |
Columbus, OH | 6.98 | 4.82 | 0.12 | 0.1 | -0.24 | -0.69 | 2.16 |
Oklahoma City, OK | 9.32 | 7.25 | 0.32 | 0.05 | 0.08 | 0.73 | 2.08 |
Detroit-Warren-Dearborn, MI | 7.84 | 5.8 | 0.25 | 0.01 | 0.03 | -0.03 | 2.04 |
Austin-Round Rock, TX | 6.62 | 4.73 | 0.18 | 0.09 | -0.14 | -0.72 | 1.89 |
Los Angeles-Long Beach-Anaheim, CA | 5.78 | 3.95 | 0.39 | -0.01 | -0.13 | -0.36 | 1.82 |
Orlando-Kissimmee-Sanford, FL | 7.73 | 6.01 | 0.25 | -0.04 | 0.07 | 0.02 | 1.72 |
Tampa-St. Petersburg-Clearwater, FL | 6.71 | 5.04 | 0.09 | -0.01 | -0.08 | 0.37 | 1.67 |
Nashville-Davidson–Murfreesboro–Franklin, TN | 7.85 | 6.28 | 0.25 | 0.03 | -0.2 | -0.5 | 1.57 |
Hartford-West Hartford-East Hartford, CT | 7.88 | 6.33 | 0.21 | 0.2 | 0.17 | -0.26 | 1.55 |
Cincinnati, OH-KY-IN | 6.17 | 4.63 | 0.1 | 0.03 | -0.02 | -0.05 | 1.54 |
St. Louis, MO-IL | 7.7 | 6.22 | 0.13 | -0.03 | 0.2 | -0.02 | 1.48 |
Washington-Arlington-Alexandria, DC-VA-MD-WV | 5.89 | 4.44 | 0.21 | -0.02 | -0.12 | -0.54 | 1.45 |
San Jose-Sunnyvale-Santa Clara, CA | 4.9 | 3.53 | 0.28 | 0.03 | -0.21 | -0.44 | 1.37 |
San Diego-Carlsbad, CA | 5.93 | 4.56 | 0.42 | -0.02 | -0.06 | 0.01 | 1.36 |
Buffalo-Cheektowaga-Niagara Falls, NY | 6.98 | 5.68 | 0.12 | -0.22 | 0.79 | -0.76 | 1.3 |
Miami-Fort Lauderdale-West Palm Beach, FL | 5.97 | 4.7 | 0.31 | -0.06 | -0.09 | -0.46 | 1.28 |
Dallas-Fort Worth-Arlington, TX | 6.8 | 5.53 | 0.15 | -0.05 | -0.14 | -0.24 | 1.26 |
Indianapolis-Carmel-Anderson, IN | 6.3 | 5.04 | 0.18 | -0.19 | -0.09 | -0.3 | 1.26 |
Baltimore-Columbia-Towson, MD | 6.31 | 5.16 | 0.26 | 0.06 | -0.19 | -0.59 | 1.15 |
Denver-Aurora-Lakewood, CO | 6.06 | 4.91 | 0.17 | -0.06 | -0.06 | -0.64 | 1.14 |
Minneapolis-St. Paul-Bloomington, MN-WI | 5.83 | 4.69 | 0.16 | -0.1 | -0.1 | -0.46 | 1.14 |
Las Vegas-Henderson-Paradise, NV | 6.66 | 5.56 | 0.49 | -0.3 | -0.06 | -0.13 | 1.1 |
Riverside-San Bernardino-Ontario, CA | 6.38 | 5.39 | 0.46 | -0.11 | -0.07 | -0.06 | 1 |
Seattle-Tacoma-Bellevue, WA | 6.52 | 5.56 | 0.38 | 0.06 | 0 | -0.22 | 0.96 |
Boston-Cambridge-Newton, MA-NH | 6.11 | 5.16 | 0.25 | 0.1 | -0.03 | -0.26 | 0.95 |
Providence-Warwick, RI-MA | 7.01 | 6.1 | 0.12 | 0.02 | 0.16 | -0.51 | 0.91 |
Kansas City, MO-KS | 6.11 | 5.21 | 0.07 | 0 | -0.11 | -0.76 | 0.9 |
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 5.64 | 4.74 | 0.06 | 0.02 | 0.1 | -0.74 | 0.9 |
Portland-Vancouver-Hillsboro, OR-WA | 6.28 | 5.48 | 0.25 | -0.04 | -0.07 | -0.64 | 0.8 |
Phoenix-Mesa-Scottsdale, AZ | 6.64 | 5.86 | 0.15 | -0.1 | 0.11 | -0.55 | 0.78 |
Louisville/Jefferson County, KY-IN | 5.82 | 5.04 | 0.05 | 0.03 | -0.2 | -0.51 | 0.78 |
San Francisco-Oakland-Hayward, CA | 4.71 | 3.98 | 0.45 | 0.02 | -0.12 | 0.04 | 0.73 |
Cleveland-Elyria, OH | 6.72 | 6.01 | 0.3 | 0.03 | -0.23 | 2.31 | 0.71 |
Raleigh, NC | 7.13 | 6.45 | 0.29 | 0.05 | 0.08 | -0.18 | 0.68 |
Houston-The Woodlands-Sugar Land, TX | 6.81 | 6.27 | 0.36 | 0.04 | 0.05 | -0.36 | 0.55 |
Chicago-Naperville-Elgin, IL-IN-WI | 4.81 | 4.28 | 0.26 | -0.19 | -0.14 | -0.36 | 0.53 |
New York-Newark-Jersey City, NY-NJ-PA | 6.34 | 5.95 | 0.42 | 0.05 | 0.13 | -0.27 | 0.39 |
Richmond, VA | 6.03 | 5.64 | 0.1 | -0.04 | 0.12 | Inf | 0.39 |
Atlanta-Sandy Springs-Roswell, GA | 6.02 | 5.72 | 0.54 | -0.15 | 0.06 | 1.05 | 0.3 |
Jacksonville, FL | 7.01 | 6.75 | 0.05 | 0.06 | 0.08 | -0.78 | 0.26 |
Charlotte-Concord-Gastonia, NC-SC | 6.91 | 6.7 | 0.08 | -0.09 | 0.4 | -0.52 | 0.21 |
Birmingham-Hoover, AL | 4.96 | 5.2 | 0.2 | -0.23 | -0.15 | 0.65 | -0.25 |
Salt Lake City, UT | 5.68 | 6.18 | 0.02 | -0.09 | 0.39 | -0.84 | -0.5 |
Milwaukee-Waukesha-West Allis, WI | 5.7 | 6.76 | 0.04 | -0.03 | 0.15 | -0.8 | -1.07 |
Virginia Beach-Norfolk-Newport News, VA-NC | 7.79 | 11.44 | 0.1 | -0.03 | 0.76 | 0 | -3.65 |
Sector | 2020-03-01 | 2020-04-01 | 2020-05-01 | 2020-06-01 | 2020-07-01 | 2020-08-01 | 2020-09-01 |
Accounting | -1.79% | -2.62% | 1.65% | 0.77% | -0.28% | 0.63% | 1.36% |
Arts & Entertainment | -6.14% | -5.13% | 0.99% | 0.91% | 0.66% | 0.01% | 0.27% |
Communications | -3.26% | -2.27% | 2.59% | 1.06% | 1.30% | 1.36% | 1.29% |
Construction | -1.69% | 0.29% | 4.30% | 3.05% | 1.09% | 1.13% | 0.91% |
Consulting | -1.80% | 0.31% | 3.01% | 1.27% | 0.86% | 1.34% | 1.78% |
Education | -4.28% | -1.96% | 2.85% | 1.23% | 0.54% | -0.88% | -0.10% |
Facilities | -0.11% | 1.88% | 6.38% | 3.80% | 1.30% | 0.43% | 0.06% |
Finance | -0.87% | 0.29% | 2.45% | 2.44% | 1.31% | 1.60% | 1.94% |
Food & Beverage | -13.04% | -3.95% | 4.58% | 3.91% | 1.17% | 0.51% | 0.91% |
Healthcare & Social Assistance | -2.60% | -0.74% | 3.47% | 2.61% | 2.36% | 2.29% | 2.02% |
Insurance | -0.69% | 0.17% | 3.39% | 2.56% | 1.52% | 1.95% | 1.39% |
Legal | -0.88% | -0.50% | 2.38% | 1.62% | 0.81% | 1.21% | 0.86% |
Manufacturing | -3.63% | 0.01% | 3.77% | 3.24% | 1.51% | 1.38% | 1.73% |
Non-Profits & Associations | -0.94% | -1.74% | 1.73% | 0.48% | 0.36% | 0.61% | 0.98% |
Other Personal Services | -5.98% | -3.19% | 3.08% | 1.61% | 1.52% | 0.01% | 0.32% |
Other Professional Services | -2.90% | -1.30% | 2.78% | 1.46% | 1.27% | 1.37% | 1.96% |
Real Estate | -2.28% | -1.16% | 2.60% | 1.27% | 0.41% | 0.57% | 0.64% |
Retail | -4.91% | 0.06% | 3.94% | 2.48% | 1.73% | 0.78% | 1.44% |
Salon & Spa | -8.14% | -2.31% | 3.17% | 2.67% | 0.24% | 0.33% | 1.28% |
Sports & Recreation | -8.97% | -4.94% | 2.28% | 4.93% | -1.48% | -1.41% | -1.08% |
Technology | -0.18% | 0.05% | 2.49% | 1.53% | 1.20% | 1.23% | 1.38% |
Transportation | -3.26% | -0.53% | 3.67% | 3.42% | 3.34% | 1.76% | 1.52% |
Unknown | -2.30% | -1.32% | 1.50% | 1.34% | 0.60% | 0.47% | 0.37% |
Wholesale | -3.37% | 0.19% | 3.53% | 1.62% | 1.67% | 1.53% | 1.89% |
State | 2020-03-01 | 2020-04-01 | 2020-05-01 | 2020-06-01 | 2020-07-01 | 2020-08-01 | 2020-09-01 |
AL | -1.46% | -0.52% | 2.16% | 3.42% | 0.31% | 0.81% | 0.87% |
AR | -1.22% | -0.63% | 3.32% | 1.70% | 0.35% | 1.37% | 1.50% |
AZ | -3.01% | -0.38% | 3.47% | 2.05% | 1.49% | 1.87% | 1.23% |
CA | -3.34% | -1.20% | 2.19% | 1.17% | 0.69% | 0.82% | 1.38% |
CO | -4.39% | -1.05% | 3.57% | 2.37% | 1.60% | 1.16% | 0.92% |
CT | -2.94% | -0.54% | 2.67% | 1.80% | 1.94% | 0.19% | 1.10% |
DC | -5.12% | -1.06% | 1.97% | 1.17% | 1.63% | 1.19% | 0.79% |
DE | -3.46% | -4.26% | 4.11% | 13.87% | 0.83% | 0.54% | -1.49% |
FL | -3.06% | -0.98% | 3.83% | 2.22% | 1.35% | 1.07% | 1.17% |
GA | -2.66% | -0.57% | 3.71% | 1.80% | 1.52% | 1.67% | 0.40% |
HI | -5.32% | -0.26% | 2.77% | -0.10% | 0.05% | 0.78% | 0.88% |
IA | -0.80% | 0.04% | 1.84% | 0.80% | -2.21% | -0.17% | 2.09% |
ID | -2.29% | -0.93% | 3.65% | 4.74% | 0.67% | 1.03% | 5.49% |
IL | -3.16% | -0.88% | 2.13% | 2.77% | 1.49% | 1.19% | 0.58% |
IN | -3.40% | -1.70% | 3.81% | 3.02% | 1.90% | 1.43% | 0.76% |
KS | -4.08% | 2.21% | 5.70% | 4.16% | 0.31% | 0.16% | 1.36% |
KY | -4.12% | 1.80% | 4.61% | 3.59% | 2.29% | 0.73% | 2.42% |
LA | -4.73% | -1.27% | 3.20% | 2.48% | 1.68% | -0.49% | 2.30% |
MA | -3.81% | 0.64% | 2.16% | 2.07% | 1.57% | 0.35% | 1.10% |
MD | -1.93% | -0.63% | 2.87% | 1.39% | 2.12% | 0.08% | 1.61% |
ME | -4.16% | 0.20% | 8.10% | 7.21% | 2.36% | 0.30% | 0.81% |
MI | -2.19% | -0.38% | 4.68% | 4.21% | 1.75% | 2.36% | 0.79% |
MN | -3.28% | -2.19% | 3.29% | 3.46% | 1.78% | 0.90% | 1.09% |
MO | -0.71% | -0.24% | 3.09% | 2.74% | 1.33% | 1.94% | 2.01% |
MS | 0.22% | -0.41% | 1.98% | -1.70% | 1.96% | -0.79% | 1.70% |
MT | -2.50% | -2.29% | 8.10% | 4.79% | 1.13% | -0.43% | 1.68% |
NC | -2.90% | -1.08% | 3.77% | 2.48% | 2.15% | 1.31% | 1.12% |
ND | -5.86% | -1.05% | 3.92% | 0.89% | -0.26% | 3.50% | 0.57% |
NE | -7.49% | 1.66% | 3.86% | 0.31% | 3.32% | 2.40% | 0.88% |
NH | -3.77% | 0.74% | 5.74% | 4.24% | 3.35% | 0.11% | 1.67% |
NJ | -5.31% | -0.95% | 3.05% | 4.01% | 2.18% | 1.34% | 1.05% |
NM | -6.72% | -1.02% | 3.31% | 3.41% | 0.55% | 1.13% | -0.90% |
NV | -4.07% | -1.72% | 3.45% | 2.81% | 1.98% | 2.93% | 0.60% |
NY | -7.40% | -3.27% | 3.19% | 1.69% | 1.02% | 0.93% | 0.27% |
OH | -2.80% | 0.98% | 4.21% | 2.46% | 1.32% | 0.41% | 0.93% |
OK | -0.79% | -0.22% | 1.29% | 3.33% | 2.39% | 1.97% | 1.29% |
OR | -5.42% | -1.17% | 3.62% | 2.06% | 1.07% | 0.66% | 1.14% |
PA | -5.64% | -1.09% | 3.43% | 3.60% | 1.43% | 1.42% | 2.34% |
RI | -2.90% | -1.30% | 4.38% | 5.26% | 3.20% | 1.47% | 0.57% |
SC | -2.34% | -1.76% | 3.77% | 3.83% | 0.84% | 0.86% | 0.50% |
TN | -3.74% | -0.10% | 3.79% | 1.44% | -0.03% | 1.15% | 2.57% |
TX | -3.00% | -0.98% | 4.26% | 2.76% | 0.92% | 0.62% | 1.30% |
UT | -2.94% | 0.88% | 5.09% | 2.94% | 0.74% | 2.54% | 1.01% |
VA | -3.15% | -0.32% | 3.39% | 3.70% | 2.09% | 1.20% | 0.38% |
VT | -2.42% | -2.69% | 3.22% | 0.39% | 2.19% | -3.57% | 2.80% |
WA | -3.95% | -2.38% | 1.99% | 2.33% | 0.81% | 0.64% | 0.94% |
WI | -4.34% | 0.25% | 3.92% | 5.09% | 1.88% | -0.48% | 0.01% |
WY | -3.78% | -2.83% | 3.42% | 2.36% | -0.53% | -0.71% | 0.79% |
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:
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:
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.
[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] Historical data may differ from earlier Gusto reporting as employers may log employee terminations after the actual termination date (e.g. more than a third of terminations that were logged in April by employers actually occurred in a prior month).
[3] Employees in the Other bucket could have worked for companies that went out of business, left Gusto’s platform, etc.
[4] The seasonal trend of Accommodations headcount growth is shown in Figure A1 in the appendix.
[5] The full history of monthly Net % Change in Headcount by Industry since March ‘20 is provided in table A4 in the appendix.
[6] The full history of monthly Net % Change in Headcount by State since March ‘20 is provided in table A3 in the appendix.
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.Read More
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