Smbliq C 053 Springer Small Business Economics Early Impacts Covid Business Sales 2021
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A peer-reviewed journal article, The early impacts of the COVID-19 pandemic on business sales, by Robert Fairlie and Frank M. Fossen, published in Small Business Economics (Small Bus Econ (2022) 58:1853–1864) and published online 31 March 2021. The article analyzes taxable sales for businesses in California using administrative data from the California Department of Tax and Fee Administration. It reports that taxable sales fell 17% in the second quarter of 2020 relative to the second quarter of 2019, although year-over-year sales typically grow by 3-4%. It finds the largest losses in businesses affected by mandatory lockdowns, with accommodations losing 91%, while online sales grew by 180%. The authors also report that counties with more COVID-19 cases per capita saw steeper declines in sales, and the article closes with a reference list.
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Small Bus Econ (2022) 58:1853–1864
https://doi.org/10.1007/s11187-021-00479-4
The early impacts of the COVID-19 pandemic on business
sales
Robert Fairlie & Frank M. Fossen
Accepted: 9 March 2021 / Published online: 31 March 2021
# The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
Abstract COVID-19 led to a massive shutdown of busi- different categories based on whether they were considered
nesses in the second quarter of 2020. Estimates from the essential or nonessential (and thus subject to early lock-
Current Population Survey, for example, indicate that the downs) and whether they have a moderate or high level of
number of active business owners dropped by 22% from person-to-person contact, we find interesting correlations
February to April 2020. We provide the first analysis of between sales losses and COVID-19 cases per capita
losses in sales among the universe of businesses in Cali- across counties in California. The results suggest that local
fornia using administrative data from the California De- implementation and enforcement of lockdown restrictions
partment of Tax and Fee Administration. Losses in taxable as safety measures for public health and voluntary behav-
sales average 17% in the second quarter of 2020 relative to ioral responses as reactions to the perceived local COVID-
the second quarter of 2019 even though year-over-year 19 spread both played a role.
sales typically grow by 3-4%. We find that sales losses Plain English Summary Business sales dropped by 17%
were largest in businesses affected by mandatory lock- on average due to the pandemic during the second quarter of
downs such as accommodations, which lost 91%, whereas 2020 in California. Accommodations lost 91% of sales,
online sales grew by 180%. Placing business types into whereas online sales grew by 180%. Sales fell more steeply
in counties with more COVID-19 cases. We examine how
much businesses lost in sales using administrative sales tax
R. Fairlie (*) data. The average losses of 17% in the second quarter of
Department of Economics, University of California Santa Cruz, 2020 relative to the second quarter of 2019 occurred even
Santa Cruz, CA, USA
e-mail: rfairlie@ucsc.edu
though year-over-year sales typically grow by 3-4%. We
find that sales losses were largest in businesses affected by
R. Fairlie mandatory lockdowns such as accommodations, drinking
Stanford University (Visiting Scholar), Stanford, CA, USA places, and arts, entertainment, and recreation.
Distinguishing between essential and nonessential busi-
R. Fairlie nesses, which were subject to early lockdowns, and by the
National Bureau of Economic Research, Cambridge, MA, USA level of person-to-person contact, we find that local imple-
mentation and enforcement of lockdown restrictions for
F. M. Fossen public health safety and voluntary responses to the perceived
Department of Economics, University of Nevada, Reno, Reno, local COVID-19 spread both played a role. The results
NV, USA suggest that small businesses may need more support from
governments and consumers to mitigate the strong shift to
F. M. Fossen online vendors, and that the pandemic must be brought
IZA, Bonn, Germany under control as a prerequisite to a full recovery.
1854 R. Fairlie, F. M. Fossen
Keywords business . entrepreneurship . self- California, we find that counties that experienced more
employment . COVID-19 . coronavirus . pandemic . COVID-19 cases per capita suffered a greater % decline
shelter-in-place restrictions . social distancing in sales. This relationship was most pronounced not
restrictions . revenues . taxable sales only for businesses affected by mandatory lockdowns
but also for businesses with high levels of person-to-
JEL Classifications L26 . H25 . I18 person contact.
The data do not allow us to distinguish between the
sales losses of small and large businesses; however,
1 Introduction 98% of business establishments with employees have
less than 100 employees in California (U.S. Census
The widespread closing of stores and businesses in the Bureau, 2018). Similarly, across OECD countries (in-
United States and around the world due to the corona- cluding the United States), small- and medium-sized
virus is unprecedented. Stores, factories, and many other businesses with less than 250 employees account for
businesses have closed by policy mandate, downward 99% of all businesses (OECD, 2019).
demand shifts, health concerns, or other factors. Esti- The relative revenue losses among small businesses
mates from the CPS, for example, indicate that the during the onset of the COVID-19 crisis might be larger
number of active business owners in the United States than among big businesses. Small businesses likely had
plummeted from 15.0 million in February 2020 to 11.7 a lower ability to quickly adjust to changes in regula-
million in April 2020 and only partially rebounded by tions and demand when the pandemic hit. Due to high
June (Fairlie, 2020).1 By June, losses were at 1.2 mil- fixed costs and required knowledge, small businesses
lion. The shutdowns and reductions in work activity are may face larger barriers to increasing their web pres-
likely to have resulted in substantial lost income for ence, expanding takeout services or adding delivery
business owners and may result in permanent closures.2 services, and coping with uncertainty regarding liability
In this paper, we provide the first analysis of sales during the health crisis. In particular, small businesses
losses among businesses using administrative data from may have had less ability to obtain financing needed for
the California Department of Tax and Fee Administra- adjustments, for example, for investing in online
tion. We examine taxable sales by type of business and ordering and inventory management, due to lower
across counties within California. We find substantial liquidity reserves, less collateral, and higher uncer-
losses in 2020 Q2 in total taxable sales in California. tainty from the perspective of lenders and inves-
Although average year over year growth by quarter is tors during the emerging economic crisis.3
normally roughly 3-4%, sales dropped by 17% from Our findings contribute to the scant evidence on the
2019 Q2 to 2020 Q2. Across industries, the losses were effects of COVID-19 on the sales and revenues of small
much more severe for those deemed “nonessential” or businesses. Data from the transactions of financial ac-
ones with substantial person-to-person contact. For ex- counts at JP Morgan Chase (JPMC) indicate that small
ample, accommodations sales dropped by 92%, bars by business revenues dropped 30-50% at the end of March
86%, and clothing stores by 52%. In contrast, however, and early April and 40% into May (Farrell et al., 2020;
online sales grew by 180%. Across counties in Kim et al., 2020). In surveys conducted by the
Kauffman Foundation, Desai and Looze (2020) find that
1
Additional evidence of business shutdowns early in the pandemic is 60% of business owners reported lower sales in April
provided, for example, from the weekly U.S. Census Small Business and 50% of owners reported lower sales in May. The
Pulse Survey which indicates that roughly 50 percent of businesses
report having a large negative effect from the COVID-19 pandemic
Opportunity Insights Economic Tracker reports small
(U.S. Census Bureau, 2020; Bohn et al., 2020). Bartik et al. (2020)
3
conducted a survey in late March of nearly 6000 small businesses that In line with this, based on an online survey conducted in April and
were members of the Alignable Business Network. They find that 43% May 2020, Block et al. (2021) report that the more severe the COVID-
of businesses are temporarily closed, large reductions in employees, 19 crisis was for entrepreneurial ventures in Germany, the more they
and that the majority of businesses have less than one month of cash on resorted to bootstrap financing. Small entrepreneurial businesses may
hand. also depend more than larger firms on relational finance with face-to-
2
Just prior to the pandemic when small business owners were asked face interaction, further impeding their access to financing during the
what actions they would take if faced with a two-month revenue loss pandemic. Brown and Rocha (2020) and Brown et al. (2020) provide
roughly half said they would use their own funds and 17% said they evidence in this direction using real-time data on funding transactions
would close or sell the business (Mills et al., 2020). from Crunchbase for China and the United Kingdom, respectively.
The early impacts of the COVID-19 pandemic on business sales 1855
business revenue data from Womply and finds a drop of due to a loss in the number of sales permits which
50% in April from January and losses of roughly 20% at experienced growth of 1% from 2019 Q2 to 2020 Q2.
the end of May from January levels.4 Bloom et al. Average sales per business permit dropped by 18.3% to
(2021) partnered with a large payments technology $123,237 in 2020 Q2.
company to collect survey data from 2500 small busi-
nesses and find an average loss of 29% in sales in 2020 2.1 Event study results
Q2. We build on these findings by analyzing data from
the State of California that covers all sectors reporting We estimate a simple event-study regression in which
taxable sales across the 58 counties in the state.5 By we adjust for a time trend and allow for seasonal
using administrative data on the universe of firms in (quarter) fixed effects. The results do not change from
California, our paper complements studies on the impact the comparison of 2019 Q2 to 2020 Q2 and adding an
of the COVID-19 pandemic on small businesses and on average growth rate over the time period. We find that
their responses using surveys6 or qualitative research total taxable sales losses are predicted to be $37.9 billion
designs (e.g., Kuckertz et al., 2020). or a 20.5% drop from 2019 Q2 levels. Using a quadratic
The findings are potentially important for future time trend instead of a linear time trend results in a
targeting and oversight of government aid to preserve slightly larger loss in total sales from COVID-19. We
small businesses and the jobs they create. The results focus the remaining analysis on 2019 Q2 to 2020 Q2
also have implications for discussions around what the comparisons for simplicity and clarity.
federal government will do next (e.g., President Biden's
proposed $1.9 trillion coronavirus stimulus package). 2.2 Losses across business types (categories, types,
and subtypes)
2 Results To slow the spread of COVID-19 governments enforced
social distancing restrictions that shut down businesses
The data used here are from the California Department in jobs and industries deemed “nonessential.” Less dras-
of Tax and Fee Administration. We focus on taxable tic restrictions were also imposed on “essential” busi-
sales for all businesses in the state. In California, taxable nesses, such as capacity limitations for grocery stores.
sales decreased substantially in the second quarter of Health concerns also dissuaded customers from visiting
2020, which directly followed the social distancing re- stores that had person-to-person contact. Finally, the
strictions imposed by the state.7 Total taxable sales in ability to telecommute in jobs allowed certain busi-
California were $152 billion in 2020 Q2 which repre- nesses or at least certain jobs in those businesses to
sents a drop of 17.5% from 2019 Q2. Typically year continue to operate.
over year growth for the same quarter is between 3% We investigate losses across business types used by
and 4% (see Fig. 1). The sharp decline in sales was not the Department of Tax and Fee Administration. Table 1
reports the percent change in sales from 2019Q2 to
4
See https://tracktherecovery.org/. Womply aggregates data from 2020Q2 and sales levels in 2020Q2 for aggregated
several credit card processors to analyze for small businesses. The business types. Starting with stores that were mostly
data are distributed across sectors for which credit card use is
common and focus on small businesses, thus comprising a larger considered “nonessential” and have person-to-person
share of food services, professional services, and other services. contact we find major losses. Clothing and Clothing
5
The findings also contribute to the broader literature on the general Accessories Stores lost 54.5% from the second quarter
relationship between recessions and entrepreneurship. The evidence is
surprisingly mixed with many previous studies showing positive rela- of 2019 to the second quarter of 2020.
tionships, negative relationships, and zero relationships (Parker, 2018). Food services and drinking places were not shut
6
For example, Graeber et al. (2021) analyze a survey of 339 self- down but faced restrictions in terms of switching to
employed persons and 3583 employees between April and July 2020 in
takeout and delivery service only and then later
Germany, and Thorgren and Williams (2020) use a sample of 456
SMEs from March 2020 in the Swedish region of Norrbotten. adding outside dining service. These restrictions
7
On March 11, 2020, the World Health Organization (WHO) declared and concerns over health led to a major drop in
COVID-19 a pandemic. On March 16, the San Francisco Bay Area demand. Sales at restaurants, bars, and other eating
imposed the first shelter-in-place restrictions in the country followed by
the State of California on March 19. New York State followed the next establishments dropped 47.4% from 2019 Q2 to
day. By early April most states imposed social distancing restrictions. 2020 Q2. In contrast, this business type category
1856 R. Fairlie, F. M. Fossen
Fig. 1 Total all outlets: Year-
over-year growth
Percent Change in Sales
was experiencing year over year growth of 3-6% In Fig. 2, we report losses for selected disaggregated
prior to the pandemic. Gasoline was deemed essen- business types for large losses and large gains in 2020 Q2
tial but as workers stayed at home and business (see Appendix Table 1 for all business types). Drilling down
travel was mostly shut down gasoline stations lost by detailed business type reveals some extremely large
substantial revenue. From the second quarter 2019 losses for specific sectors. The accommodation subsector
to the second quarter 2020, sales dropped by 47.0%. had the largest loss at 91%, followed by the 86% drop in
Larger purchases and ones with more flexibility in taxable sales at drinking places-alcohol, and the 83% drop at
timing of purchases experienced large but smaller arts, entertainment and recreation places. Full-service restau-
drops in taxable sales. Home furnishings and appli- rants, which were often shut down or switched to take out,
ance stores dropped 18% over the year. Similarly, also did not fare well with sales losses of 61%. Small shops
motor vehicle and parts dealers dropped by 14.8%. selling gifts and souvenirs, clothing, or books also experi-
Not all businesses experienced large losses. enced large losses in the second quarter of 2020. All of these
Businesses that were deemed “essential” were not businesses are characterized as by being “nonessential” and/
forced to close and remained open during the first or suffered from reduced demand because of high levels of
three months of the pandemic (i.e., second quarter person-to-person contact.
2020). Food and beverage stores experienced an On the other end of the spectrum, some business
increase of 1.7%, but the growth rate was lower types did extremely well. The shift by consumers to
than average year over year growth in sales. online purchases bolstered the sector “Nonstore Sales”
Building material and garden equipment grew by into astonishing positive growth of 181%. The sectors of
12.1% which likely reflects the many home and agriculture, building materials, pharmacies, garden cen-
garden repair and improvement projects started by ters, supermarkets, and even liquor stores were deemed
home owners with more time on their hands dur- “essential” and experienced positive sales growth from
ing the pandemic. 2019 Q2 to 2020 Q2. Although supermarkets experi-
“General merchandise stores” capture both es- enced growth of 5% in 2020 Q2 the shutdown and
sential and nonessential goods so were often open avoidance of many restaurants and previous annual
during the pandemic. They experienced a drop of growth of roughly 2% suggested perhaps larger poten-
9.8% from 2019 Q2 to 2020 Q2. All other outlets tial growth.8 Interestingly, 2020 Q1 experienced growth
experienced a drop of 19.4%.
Combing all business types, all outlets experienced a 8
drop of 17.5%. Total retail and food services dropped by Note that most grocery items are exempt from sales tax in California.
Taxable items include hot prepared food products, carbonated bever-
a similar amount, 16.6%. ages, effervescent bottled water, wine, and spirits, for example.
The early impacts of the COVID-19 pandemic on business sales 1857
Table 1 California Taxable Sales Losses by Business Types
Business Type Percent Change Taxable Transactions Amount Percent of Total Tax
2019Q2 to 2020Q2
Total All Outlets -17 152,362,296,481 100.0
Total Retail and Food Services -17 105,528,311,167 69.3
Motor Vehicle and Parts Dealers -15 19,294,245,937 12.7
Furniture and Home Furnishings Stores -18 2,625,229,637 1.7
Electronics and Appliance Stores -14 3,663,719,124 2.4
Building Material and Garden Equipment and Supplies Dealers 12 12,248,068,380 8.0
Food and Beverage Stores 2 7,584,295,812 5.0
Health and Personal Care Stores -11 3,414,123,225 2.2
Gasoline Stations -47 7,737,896,946 5.1
Clothing and Clothing Accessories Stores -54 4,744,372,982 3.1
Sporting Goods, Hobby, Musical Instrument Stores -20 2,010,965,666 1.3
General Merchandise Stores -10 12,522,013,242 8.2
Miscellaneous Store Retailers -17 4,418,659,674 2.9
Food Services and Drinking Places -47 11,991,170,465 7.9
Total All Other Outlets -19 46,833,985,314 30.7
Source: Administrative data from the California Department of Tax and Fee Administration.
of over 10% over 2019 Q1 which might reflect some one of the largest sales losses across all counties,
panic buying of food and supplies when concerns over dropping by 50% from 2019 Q2 to 2020 Q2. Los
the pandemic first hit. Concerns over health and chang- Angeles County experienced a drop in taxable sales of
ing restrictions on the shopping experience then might 24%, and San Diego County experienced a drop in
have tempered demand somewhat for visiting supermar- taxable sales of 19%. In contrast, several small counties
kets in 2020 Q2. actually experienced positive growth in taxable sales
Overall, the patterns of sales losses and growth indi- from 2019 Q2 to 2020 Q2.
cate a shift from in-store purchases to online purchases,
and from restaurants to grocery stores. Whether an 2.4 COVID-19 cases and sales losses by county
industry was deemed essential versus nonessential had
a major impact on whether sales growth was negative or In this section, we analyze how the changes in taxable
positive in the second quarter of 2020. Finally, con- sales were correlated with coronavirus cases at the
sumers avoided business subsectors in which there county level. We obtain confirmed COVID-19 cases
was a lot of person-to-person contact because of health by county and day from USAFacts (2020) and use
concerns over the coronavirus. cumulative cases by May 15, 2020 (the midpoint in
the second quarter) per capita.9 Testing for COVID-19
2.3 Losses across counties was often not readily available in the second quarter of
2020, and availability and uptake of testing may have
California has a diverse set of counties ranging from varied across counties. However, decisions of con-
large, densely populated counties such as Los Angeles sumers and producers as well as decisions of
and San Francisco to very small rural counties in the policymakers about the implementation and enforce-
mountains such as Alpine and Shasta counties. Related ment of lockdowns were based on the same testing data,
to population density COVID-19 cases per capita dif- which were widely reported in the media, including the
fered substantially across counties. Table 2 reports tax- local media. Therefore, our analysis is informative about
able sales losses by county for all outlets and cumulative the effects of the perceived local spread of COVID-19.
confirmed COVID-19 cases per capita by May 15, 9
2020. Businesses in San Francisco County experienced County population numbers are from the U.S. Census Bureau.
1858 R. Fairlie, F. M. Fossen
Fig. 2 Sales growth percent (2019Q2 to 2020Q2) - selected business types with large losses and gains
Fig. 3 provides a scatter plot relating the growth rate contagion even without government regulation? A
in taxable sales across all business types between the comparison across different business types sheds
second quarter in 2019 and the second quarter in 2020 to some light on these questions. Table 3 classifies
the cumulative number of COVID-19 cases per capita exemplary business types by whether they were
by May 15, 2020, in each of the 58 counties in Califor- deemed nonessential and therefore subject to
nia. The data indicate a clear negative relationship. A strong lockdown restrictions and by the possibility
bivariate regression line is also shown; the slope coeffi- to maintain social distance from other people
cient is −40.06 with a standard error of 22.48, indicating (workers or customers). For example, garden
that an additional known COVID-19 case per 1000 equipment and clothing shops may have compara-
inhabitants in a county was associated with an additional ble opportunities for maintaining social distance,
decline in taxable sales by 4 percentage points.10 but the former business type was exempt from
From a policy perspective, it is important to stricter lockdown restrictions because it was con-
understand how much mandatory lockdown restric- sidered essential. Therefore, if we find a stronger
tions implemented for public health safety were correlation between known COVID-19 cases and
binding. Would consumers have avoided spending sales losses for clothing than gardening shops at
or producers shut their businesses due to fear of the county level, this may be attributable to the
imposition and enforcement of lockdown restric-
tions, which can be expected to be stricter in
10
Weighting the regression by the population size of the counties does counties with more COVID-19 cases per capita.
not change the picture (see Figure B1 in Appendix B), the slope
In contrast, both clothing shops and restaurants
coefficient (std. err.) becomes −36.77 (0.0148).
Table 2 California taxable sales losses by county
County Change 2019Q2 Taxable transactions Cum. COVID-19 County Change Taxable Cum. COVID-19
to 2020Q2 amt. M$ cases per 1000 inh. 2019Q2 to 2020Q2 transactions amt. M$ cases per 1000 inh.
Los Angeles −24% 32,702.3 3.59 Imperial −9% 614.9 4.36
Orange −25% 13,242.8 1.30 El Dorado −6% 591.6 0.34
San Diego −19% 12,388.5 1.67 Kings 15% 535.3 2.48
Santa Clara −13% 10,061.4 1.25 Humboldt −2% 513.4 0.53
San Bernardino −8% 9,633.8 1.55 Sutter 0% 489.2 0.39
Riverside −7% 9,554.2 2.36 Madera 2% 475.3 0.45
Alameda −26% 6,601.6 1.40 Mendocino −6% 391.8 0.15
Sacramento −7% 6,339.9 0.80 Nevada 2% 377.4 0.41
Fresno −3% 4,011.2 1.18 Tehama −11% 234.6 0.03
Contra Costa −16% 3,836.7 0.97 Tuolumne 3% 204.0 0.04
San Joaquin −1% 3,646.0 0.90 San Benito −1% 187.6 1.01
Kern 3,642.2 1.62 Lake 8% 183.5 0.12
The early impacts of the COVID-19 pandemic on business sales
−9%
San Mateo −31% 3,147.7 2.06 Yuba 5% 177.9 0.33
Ventura −16% 3,123.6 0.90 Siskiyou 10% 162.5 0.11
San Francisco −50% 2,648.4 2.33 Colusa 6% 141.6 0.14
Tulare 28% 2,541.1 2.91 Glenn −2% 136.3 0.32
Stanislaus −6% 2,324.6 1.01 Amador −4% 122.6 0.24
Placer −17% 2,229.3 0.46 Calaveras 7% 118.8 0.29
Sonoma −16% 2,144.6 0.73 Lassen 14% 81.1 0.00
Solano −13% 1,859.8 0.93 Inyo −24% 72.7 1.05
Santa Barbara −18% 1,593.2 3.16 Del Norte 7% 67.1 0.15
Monterey −22% 1,524.2 0.88 Plumas 12% 65.6 0.21
San Luis Obispo −15% 1,229.1 0.85 Mono −31% 48.1 2.33
Marin −25% 1,059.4 1.10 Trinity 27% 37.1 0.08
Yolo −12% 1,047.1 0.85 Mariposa −41% 36.1 0.86
Butte −6% 927.0 0.10 Modoc 5% 25.0 0.00
Santa Cruz −17% 857.1 0.54 Sierra −63% 4.6 0.00
Shasta −5% 848.3 0.18 Alpine −14% 3.8 1.75
Merced −8% 819.3 0.74 CA Total −17% 152,351.1 1.97
Napa −31% 667.2 0.59
Note: Cumulative COVID-19 cases are confirmed cases per 1000 inhabitants by May 15, 2020. Source: Administrative data from the California Department of Tax and Fee Administration 1859
and USAFacts.
1860 R. Fairlie, F. M. Fossen
Fig. 3 Taxable sales losses by
county for all outlets. Each dot in
the scatter plot represents one
county in California. The taxable
sales growth rate is the relative
change between 2019 Q2 and
2020 Q2 for all outlets. COVID-
19 cases are the cumulative con-
firmed cases per capita in the
county by May 15, 2020. A linear
bivariate regression line is also
shown
Table 3 Potential exposure of business types to the pandemic
“Essential” (no lockdown) “Nonessential” (subject to lockdown)
Moderate person-to-person contact Building material and garden equipment; Clothing and clothing accessories stores
Gasoline stations
High person-to-person contact Food and beverage stores Food services and drinking places
(food services and drinking places) were classified quarter of 2020, but social distancing may be
as nonessential and therefore subject to similar easier in clothing shops; therefore, if we find dif-
lockdown restrictions in California in the second ferent strengths of correlation between COVID-19
Fig. 4 Taxable sales losses by
county for building materials and
garden equipment. Each dot in the
scatter plot represents one county
in California. The taxable sales
growth rate is the relative change
between 2019 Q2 and 2020 Q2
for building material and garden
equipment stores. COVID-19
cases are the cumulative con-
firmed cases per capita in the
county by May 15, 2020. A linear
bivariate regression line is also
shown
The early impacts of the COVID-19 pandemic on business sales 1861
Fig. 5 Taxable sales losses by
county for clothing and clothing
accessories stores. Each dot in the
scatter plot represents one county
in California. The taxable sales
growth rate is the relative change
between 2019 Q2 and 2020 Q2
for clothing and clothing
accessories stores. COVID-19
cases are the cumulative con-
firmed cases per capita in the
county by May 15, 2020. A linear
bivariate regression line is also
shown
cases and sales losses in these types of businesses, We begin by contrasting two business types which
this may be attributable to voluntary behavior of seem comparable in terms of social distancing possibil-
customers or sellers due to caution and fear of ities: building material and garden equipment stores,
contagion.11 which were considered essential businesses, in Fig. 4,
Motivated by these considerations, we compare scat- and clothing stores, which were nonessential, in Fig. 5.
ter plots with unweighted regression lines for the busi- The impact of local known COVID-19 cases on sales
ness types mentioned in Table 3. They appear in Figs. 4, was larger for clothing stores. While sales grew on
5, 6, 7.12 All of these plots reveal negative relationships average for building materials and gardening stores,
between local known COVID-19 cases and sales they shrank on average for clothing stores, presumably
growth. The finding that this negative relationship is due to the stricter lockdown restrictions for the latter
not only observed for business types that are subject to business type. In addition to the level difference, the
strict lockdown restrictions, but also for so-called essen- negative correlation of sales growth with local known
tial business types such as garden equipment stores and COVID-19 cases is much stronger for clothing stores,
grocery stores, indicates that at least some of the drop in with a regression slope coefficient (std. err.) of −169.9
sales is driven by a voluntary change of behavior by (38.57), in comparison to building material and garden-
consumers and producers out of caution when the local ing stores with a slope (std. err.) of −40.72 (19.63).13
spread of COVID-19 seemed high, and potentially also This suggests that stronger local enforcement of lock-
by larger drops in income in these regions. However, the down restrictions in the case of clothing stores when
negative slopes of the relationships are steeper for non- local COVID-19 spread was high had a larger effect
essential businesses that were subject to strict lockdown than voluntary reactions of customers and sellers in the
restrictions, indicating that the imposition and enforce- case of building materials and gardening stores.
ment of lockdown restrictions as safety measures also When comparing two business types that were both
played an important role. considered nonessential, clothing stores on the one hand
and food services and drinking places (in Fig. 6) on the
other, one might have expected a larger impact of
11
COVID-19 on restaurants and bars, because social dis-
We classify food and beverage stores into the high person-to-person
contact category due to the often comparably high density of customers
tancing in these businesses seems harder than in cloth-
and employees in and around these stores. Keep in mind that most ing stores; both business types were generally allowed
grocery items are exempt from sales tax in California, see footnote 8. to offer at least (curbside) pickup and delivery. Howev-
12
Appendix Figure B2 additionally contains a plot for gasoline sta- er, the negative correlation between sales growth and
tions, a second business type in the group of essential businesses with
moderate person-to-person interaction. known COVID-19 cases is actually weaker for
1862 R. Fairlie, F. M. Fossen
Fig. 6 Taxable sales losses by
county for food services and
drinking places. Each dot in the
scatter plot represents one county
in California. The taxable sales
growth rate is the relative change
between 2019 Q2 and 2020 Q2
for food services and drinking
places. COVID-19 cases are the
cumulative confirmed cases per
capita in the county by May 15,
2020. A linear bivariate regres-
sion line is also shown
restaurants and bars, with a slope (std. err.) of −45.21 beverage stores is −58.27 (16.70). When weighting
(21.17). This is another indication suggesting that vol- the regressions by county population, the correlation
untary behavior change as a reaction to local COVID-19 is more negative for restaurants and bars with a
cases was not the main driver of industry and county slope (std. err.) of −41.08 (0.0168) than for food
differences in sales declines. and beverage stores with −16.98 (0.00883), suggest-
Finally, food and beverage stores (Fig. 7) experi- ing that the local enforcement of lockdown restric-
enced an increase in sales on average, in contrast to tions was important again. The unweighted point
food services and drinking places, which is likely estimate of the slope is steeper for grocery stores
due to the fact that grocery stores were deemed than for building material and gardening stores,
essential and subject to fewer lockdown restrictions. which were also considered essential. This suggests
The negative association between sales growth and that voluntary reactions to the number of known
COVID-19 cases is similar in both cases; however, local COVID-19 infections in case of the often more
the regression coefficient (std. err.) for food and crowded grocery stores played a role.
Fig. 7 Taxable sales losses by
county for food and beverage
stores. Each dot in the scatter plot
represents one county in
California. The taxable sales
growth rate is the relative change
between 2019 Q2 and 2020 Q2
for food and beverage stores.
COVID-19 cases are the cumula-
tive confirmed cases per capita in
the county by May 15, 2020. A
linear bivariate regression line is
also shown
The early impacts of the COVID-19 pandemic on business sales 1863
3 CONCLUSIONS foundations and companies have promised to help.
Can these programs help small businesses survive the
Although it is well known that COVID-19 led to a shutdowns and other setbacks through the pandemic, or
massive shutdown of businesses in the second quarter will more assistance be needed in the recovery? Further-
of 2020, surprisingly little is known about actual sales more, will an added shift in consumer behavior away
and revenues losses in the early stages of the pandemic. from large online retailers towards small businesses to
Using administrative data from the California Depart- fight longer-term trends be needed? States have promot-
ment of Tax and Fee Administration, we provide new ed shopping local (e.g., California's
evidence on sales losses among the universe of busi- #ShopSafeShopLocal) but can this counteract these
nesses by detailed business types and locations. Normal trends? In the end, getting the virus in check and the
year-over-year growth in taxable sales is 3-4%, but roll out of vaccines to lift restrictions and restore cus-
losses in sales were 17% in the second quarter of 2020 tomer, owner and employee confidence in health safety
relative to the second quarter of 2019. Sales losses were is likely the first real step to a full recovery for small
largest in businesses affected by mandatory lockdowns businesses.
such as accommodations at 91%. But other types of
businesses experienced large gains, such as online sales,
which grew by 180% as consumers substituted away
from in-store purchases. The pandemic-induced reces- Supplementary Information The online version contains sup-
plementary material available at https://doi.org/10.1007/s11187-
sion created large losses for many types of businesses.
021-00479-4.
Placing business types into different categories based
on whether they are “essential” or “nonessential” (and
thus subject to early lockdowns) and whether they have Acknowledgements We would like to thank Isabel Guzman at
a moderate or high-level of person-to-person contact, the California Governor's Office of Business and Development
we find interesting correlations between sales losses and and Irena Asmundson at the California Department of Finance, for
help with the data. The study also benefited from preparing for and
COVID-19 cases per capita across counties in Califor- discussions in recent testimonies to the U.S. House of Represen-
nia. The findings across these different classifications tatives and California State Assembly (Fairlie, 2021a, b).
reveals that local implementation and enforcement of
lockdown restrictions for public health safety and vol-
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