• ITVI.USA
    14,088.240
    34.090
    0.2%
  • OTRI.USA
    21.610
    -0.070
    -0.3%
  • OTVI.USA
    14,061.290
    31.460
    0.2%
  • TLT.USA
    2.660
    0.020
    0.8%
  • TSTOPVRPM.ATLPHL
    2.540
    0.060
    2.4%
  • TSTOPVRPM.CHIATL
    2.460
    0.270
    12.3%
  • TSTOPVRPM.DALLAX
    1.360
    -0.040
    -2.9%
  • TSTOPVRPM.LAXDAL
    2.910
    0.180
    6.6%
  • TSTOPVRPM.PHLCHI
    1.490
    0.050
    3.5%
  • TSTOPVRPM.LAXSEA
    3.130
    0.260
    9.1%
  • WAIT.USA
    108.000
    5.000
    4.9%
  • ITVI.USA
    14,088.240
    34.090
    0.2%
  • OTRI.USA
    21.610
    -0.070
    -0.3%
  • OTVI.USA
    14,061.290
    31.460
    0.2%
  • TLT.USA
    2.660
    0.020
    0.8%
  • TSTOPVRPM.ATLPHL
    2.540
    0.060
    2.4%
  • TSTOPVRPM.CHIATL
    2.460
    0.270
    12.3%
  • TSTOPVRPM.DALLAX
    1.360
    -0.040
    -2.9%
  • TSTOPVRPM.LAXDAL
    2.910
    0.180
    6.6%
  • TSTOPVRPM.PHLCHI
    1.490
    0.050
    3.5%
  • TSTOPVRPM.LAXSEA
    3.130
    0.260
    9.1%
  • WAIT.USA
    108.000
    5.000
    4.9%
American ShipperNews

Paycheck Protection Program loans in manufacturing

The public release of data for Paycheck Protection Program (PPP) loans exceeding $150,000 on Monday by the Small Business Administration has provided visibility into the far-reaching impact of this program. Much has already been written about the impact of PPP on the motor carrier and 3PL sectors, but the PPP’s effect on manufacturing has been less explored. As substantial freight volume comes from manufacturing activity, especially for LTL carriers, examining how PPP loans have affected the manufacturing sector can better inform the freight market outlook. It should be noted that some errors have come to light in the released PPP data, so all figures should be interpreted as approximations.

Effect by sector

Across manufacturing NAICS codes (which start with two-digit codes of 31, 32 or 33), 68,642 PPP loans of at least $150,000 were provided. These loans are reported to have retained about 3.444 million jobs. As seasonally adjusted manufacturing employment was reported to be approximately 12.85 million individuals as of February, this suggests PPP has affected roughly 26.8% of manufacturing jobs. This figure is comparable to those reported in the trucking industry. Using the Q4 2019 figures reported for the Quarterly Census of Employment and Wages, this suggests at least 19% of manufacturers received PPP loans. The caveat is that many smaller manufacturers could have received loans under the $150,000 cutoff, which would explain why the number of jobs affected by PPP loans (26.8%) exceeds the number of establishments receiving the loans (19%). As such, the figures provided in the table below may be understated.

Splitting the data by durable versus nondurable goods, 21.4% of durable goods manufacturers received PPP loans compared with 15.4% of nondurable goods manufacturers. Consistent with this, a greater percentage of manufacturing jobs in the durable goods sector (28.2%) are affected by PPP than those in the nondurable goods sector (24.5%). It does not appear this difference stems from durable goods establishments being larger, as dividing nondurable goods employment and durable goods employment by the respective number of establishments indicates no substantial difference in number of jobs per establishment. Rather, this aligns with prior reporting that the durable goods sector has been harder-hit by COVID-19. Consistent with this, the two three-digit sectors reporting the highest percent of establishments with PPP loans are primary metals (32%) and machinery (29%).

Effect by state

Examining the data by state indicates the geographic dispersion of manufacturing PPP loans is consistent with well-recognized patterns of U.S. manufacturing activity. California and Texas received the most loans and accounted for the largest percentage of total manufacturing jobs. This was followed by manufacturing-heavy Midwestern states including Ohio, Illinois and Michigan. New York, Pennsylvania, Wisconsin, Florida and Indiana round out the top 10 states by number of jobs retained. 

Date of loans

As shown below, PPP loans were primarily taken out in April and the first week of May. With the signing of H.R.7010 — Paycheck Protection Program Flexibility Act of 2020, firms have 24 weeks to dispense 60% or more of their loans for payroll to ensure loan forgiveness. Consequently, the loans originated during the week starting April 5, 2020, must meet this criterion for the week starting Sept. 20, 2020. With the resurgence of COVID-19 cases, it is difficult to foresee how the extent of manufacturing activity will have returned to pre-COVID levels by this date. 

Conclusion

PPP loans have played a major role in retaining manufacturing employment levels during the COVID-19 pandemic. Consistent with reported employment declines, PPP loans have been more prevalent for durable goods manufacturers relative to makers of nondurable goods. Establishments in California, Texas and the industrial Midwestern states have received the largest number of PPP loans; consequently, these states have seen a larger number of manufacturing jobs retained due to the program. Continued resurgence of COVID-19 cases makes it difficult to predict the extent to which manufacturing activity will have returned to pre-COVID levels by the time PPP loans must be distributed to cover payrolls to ensure these loans are forgiven.

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Jason Miller

Jason Miller is an associate professor of logistics (with tenure) in the Department of Supply Chain Management at Michigan State University's Eli Broad College of Business. His research predominantly focuses on issues pertaining to the motor carrier industry. These topics include motor carriers' safety performance, compliance with and consequences of the electronic logging device (ELD) mandate, productivity, driver turnover, and market dynamics (e.g., how spot market rates influence contract rates). His research has appeared in Academy of Management Journal, Journal of Business Logistics, Journal of Management, Journal of Operations Management, Journal of Supply Chain Management, Multivariate Behavioral Research, Transportation Journal and Transportation Research: Part E, among others. He completed his Ph.D. in business administration with a concentration in logistics and a minor in quantitative psychology from The Ohio State University in 2014.
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