Pandemic-era small business loans boosted payrolls by 5% a year later

Key Findings

• Economic Injury Disaster Loans (EIDL loans) boosted small business payrolls by 5% one year later, but the effect faded over time to about 2% one year later.

• In total, that translates into nearly 1 million jobs created or or preserved by the EIDL program.

• This effect is similar in size to most estimates of the effect of Paycheck Protection Program (PPP) loans. 

• Many businesses received both EIDL and PPP loans, and the payroll effect disappears when analyzing businesses that received only EIDL loans.

Introduction

During the early days of the Covid-19 pandemic in 2020, Congress enacted several emergency loan programs to help companies survive the immediate economic disruption. The impacts of the largest program, the Paycheck Protection Program (PPP), have been widely evaluated but there has been less research on the smaller Covid-19 Economic Injury Disaster Loan (EIDL) program. 

Most research on the effects of the PPP loan program put estimates of the effect of the loans on payrolls at the end of 2020 typically in the range of 0% to +6% (+2% to +10% at peak within the first year). To our knowledge, this is the first published analysis looking specifically at the effects of the EIDL program on small business outcomes.

Comparison of the PPP and EIDL Small Business Loan Programs   

The EIDL program was available to small businesses to use for working capital and operating expenses. However, its terms were generally more restrictive, lacking a mechanism for loan forgiveness. The average loan amount between April and November 2020 was $56,172.

By contrast, PPP loans were designed to be used to maintain payrolls and prevent layoffs, and included loan forgiveness provisions. The average loan amount between April 2020 and July 2021 was $69,113.

Businesses were eligible to receive both PPP and EIDL loans, and we estimate that 52% of EIDL recipients also received a PPP loan.

EIDL recipient payrolls were 5% higher a year after the loan compared to similar small businesses that did not receive a loan

Combining EIDL recipient data published by the Small Business Administration (SBA) with Gusto payroll records finds that EIDL loans granted between April and November 2020 boosted small business payrolls by about +5.2% 12 months later, with the effect fading to +2.2% 24 months later. Both results are statistically significant.

At the time of the loan award, the average recipient had 4.79 employees. That means that after 12 months, the EIDL program created about 0.25 full time employees at recipient companies – working out to 971,412 jobs in total. 

These results suggest that EIDL loans had a strong initial effect on small business payrolls, but that the effect tapered over time. Previous Gusto research shows that pandemic-era new businesses grew rapidly during their first two years. 

However, when we test the model excluding companies that received both EIDL and PPP loans, the effect disappears entirely – suggesting that the two pandemic-era small business programs worked in tandem to help business stay afloat and grow. 

Conclusion

This analysis provides the first published estimates to our knowledge of the effects of pandemic-era EIDL loans on small business payrolls. The evidence suggests that the emergency loans boosted small business payrolls during the first year of the pandemic, but the effects quickly faded. 

Methodology

We merged publicly available EIDL loan origination data from April to November 2020 published by the Small Business Administration with monthly Gusto payroll records on normalized company names and the month of the loan. Company name normalization included removing all punctuation, capitalization and spacing.

This fairly conservative match produced 3,181 businesses who were Gusto customers at the time of the EIDL loan approval in 2020 and who continued to be Gusto customers for at least 24 months after the loan approval.

Using the full set of Gusto customers, we computed propensity scores for a matched counterfactual sample of businesses to the EIDL recipients via Inverse Probability of Treatment Weighting on industry, the number of full-time employees, and the number of part-time employees. We then merged a 3,181 sample of non-recipient businesses that most closely matched the EIDL recipient data. 

Finally, we regressed total payrolls (full- and part-time employees) 12- and 24-months after the EIDL award on the test and control business samples.