Consumer spending makes up around 68 percent of the nation’s
gross domestic product. Consumer spending is individuals and families
purchasing groceries, clothing, recreation, stocks, insurance, education and much
more. The transactions cover a broad swath of economic activity.
Much of the nation’s consumer spending is captured via
retail trade. A useful retail trade definition
is “the re-sale (sale without
transformation) of new and used goods to the general public, for personal or
household consumption or utilization.” Not all consumer spending is captured through
retail trade transactions, but majority large share is.
Whereas in the past nearly all retail transactions were done
through traditional brick-and-mortar stores, now a significant and growing
segment is diverted to internet sales. The consumer shops online and FedEx (or
like) delivers the product. One can see that the number of brick-and-mortar
stores and the level of local sales across the country are being endangered by this
economic evolution.
The brick-and-mortar reduction is beginning to show its economic
presence in the United States employment numbers. While the U.S. economy is
finally expanding at a healthy pace this side of the Great Recession, one of
the few industries not rising with this tide is retail trade. While overall
retail sales are increasing, employment is not.
Traditionally, as a population increases, retail trade
employment grows simultaneously, since population growth and consumer spending volume
is an integrated dynamic. If studied deeply, a certain ratio of retail trade employment
growth spawned from population growth would emerge.
Before the internet, the
vast majority of all consumer sales occurred in the immediate community or
region. But now, the internet is diverting these sales away from the local
community — and with internet sales growing, its market share will increase.
We do not yet know how much brick-and-mortar erosion will eventually
occur. And will such a phenomenon hit some areas more than others (e.g., urban
vs. rural, or local vs. tourist spending)? These are touch points that
economists will be watching as this internet sales phenomenon continues to grow
within the national and Utah economies.
In light of this change, in this quarter’s Local Insights we
are profiling retail trade employment throughout Utah’s local regions. This can
offer a profile of where retail trade is now in a local economy, and possibly
how much of the sector could become vulnerable to the internet-sales
phenomenon.
All regions can be viewed through the Local Insights web
portal. The following is a retail trade profile for the Mountainland region:
Measuring
Retail – NAICS Codes
In order to explore
the relationship between internet and brick-and-mortar retail we need to look
at data grouped through the North
American Industry Classification System (NAICS), which “is the standard
used by Federal statistical agencies in classifying business establishments.” Stated
simply, the NAICS groups businesses together based upon what they do.
Hierarchical in
nature, the NAICS begins with a broad categorization and narrows its focus at
subsector levels. As an example, the educational services sector includes all
institutions focused on providing instruction and training. At the subsector
levels, that focus is narrowed so that data from elementary schools, colleges
and trade institutions are separated.
In the case of
retail, a broad sector known as retail trade includes several underlying categories
such as: motor vehicle sales, furniture stores, electronics stores, building
material stores, grocery stores, pharmacies, gas stations, clothing stores and
department stores, among others.
Then there is the
relatively new and emerging part of the retail trade sphere — non-store
retailers. These are establishments that sell products primarily on the internet
or through direct selling. Examples include Amazon, Overstock.com, Young Living
and dōTERRA. These types of retailers have grown rapidly in the past 15 years
and their presence is reshaping the retail trade landscape. We will look at
this subsector in a later section.
Retail in
the Mountainland Region
In 2016, retail trade accounted for 12.8 percent of
employment in the four Mountainland counties making it one of the largest
industries with nearly 35,000 jobs. The three largest retail subsectors in the area
are general merchandise stores, food and beverage stores, and motor vehicle and
part dealers. These three account for 41 percent of retail employment in the
area are responsible for nearly a third of all taxable sales in the four
counties.
This and other data are represented in the visual below, which
illustrates trends in retail employment and taxable sales between 2000 and
2016. From this visual we see that retails’ share of employment has declined in
recent years. On the surface, this may indicate that the internet is replacing
“vulnerable” brick-and-mortar jobs with employment in electronic shopping
related industries.
While many of these online retail jobs are counted in
non-store retailers, some worksites may be placed in other industries like
transportation and warehousing. As an example, despite their online storefront,
the distribution center for Backcountry.com in West Valley City is classified
as a warehousing establishment. This structural difference between online and
traditional retail may account for some of the employment share reduction, but
to what extent is it driven by the internet supplanting vulnerable retail
locations?
Infrastructure,
Perishability and Behavior – Identifying Vulnerable Retail Sectors
One way to identify potential vulnerabilities in
brick-and-mortar retail employment is to explore trends in e-commerce sales
relative to total retail sales. While this data is unavailable at the region
and state level it is provided for the U.S. Despite the lack of geographical
specificity in the data, it captures trends and relationships in an industry
where borders are disappearing due to the growing accessibility of the
internet.
In order to identify vulnerable employment, we will identify
subsectors which have been impacted most by online shopping. We can do this by
looking at internet sales penetration within retail, which is the share of
online sales for a particular subsector, and comparing it to employment in
Utah, Summit, Juab and Wasatch counties. For this portion of the analysis, we
will exclude non-store retailers and look at “traditional” brick-and-mortar
retail groupings and their online sales.
Mountainland Employment
vs. Internet Sales Penetration
Source: Census Bureau E-Stats
This graph illustrates four main points about the
connection/competition between brick-and-mortar and online stores.
First, not all industries are currently well-suited for
internet sales and may lack the infrastructure required. This is seen primarily
in the low online sales levels in general merchandise (one-stop shopping) and
food/beverage (grocery) stores. While the idea of having all your groceries and
toiletries shipped is appealing, the infrastructure to transfer these
perishable goods to a large amount of households in a timely manner does not
yet exist. Conversely, the electronics subsector appears to be much better
suited for online sales. Perhaps it is because individuals purchasing
technology are comfortable with using technology to purchase it.
The second insight we can glean from the graph is the impact
of product on labor needs. A food and beverage store will require more
employees to care for perishable goods relative to a furniture store where
products rotate only a few times annually. Books, clothing and electronics are
also examples of products requiring less labor to maintain. Therefore, the less
maintenance an inventory requires, the higher the likelihood that it will
transition to online sales.
Third, the motor vehicle and part dealer subsector is
unique. While perishability of goods can explain the need for higher employment
levels in the grocery groupings, a car doesn’t expire the way a gallon of milk
does. While some of the higher employment in motor vehicles may be explained by
a lack of infrastructure in shipping cars purchased online, it may be more of a
behavioral driver. According to a 2015 Autotrader
survey, 88 percent of consumers said they wouldn’t buy a car before a test
drive.
These first three points illustrate that infrastructure,
perishability and behavior all influence the degree to which certain retail
groups sell online.
The final point is the negative relationship between
internet sales penetration and employment. In general, higher levels of internet
sales penetration are correlated to low regional employment in that industry.
This confirms visually that jobs gained with online retailers reduce employment
among traditional retail.
What About
Non-Store Retailers?
As mentioned previously, the graph above excluded non-store
retailers. In the Mountainland area, this subsector employs more than 6,200
individuals, making it the largest retail category. Of these jobs, over 4,000
are found in the direct selling category which encompasses in-house sales,
truck or wagon sales and portable stalls. With the rise of essential oil
companies like Young Living and dōTERRA,
among other multi-leveling marking (MLM) companies, Utah County has become a
bastion of this type of retail activity. Since 2000, employment in this subsector
has grown by 595 percent (mostly since 2007) and taxable sales have grown by 63
percent. So why are non-store taxable sales gaining at a slower pace than
employment?
In the case of direct selling, many MLM workers are
contracted labor, in other words they operate as self-employed workers. This
means their taxable sales will not be captured in a retail NAICS code, and
cannot be tracked. In online sales, taxes are collected by the state of the
purchaser, and then, only if the seller has a physical presence in that state. This
means that when Overstock.com sells a rug to someone outside of Utah, there is
money coming into Utah (in terms of the jobs that the sale supports), but there
is no sales tax coming in to Utah. The only non-store sales taxes captured in
Utah are Utah consumers purchasing goods from retailers with a presence in
Utah. Since a large share of sales by local online retailers are to customers
in other states, it means that sales tax revenue lags compared to employment
growth in the industry.
Direct sales (MLM) and companies like Overstock.com
illustrate the difficulties in quantifying the impact of non-store retailers on
brick-and-mortar locations. When Utah residents purchase tax-free goods from a
non-store retailer like Amazon or from a direct sales company, establishing a
relationship between non-store and traditional retail is challenging.
Perhaps the state’s recent agreement with Amazon will be
helpful in unraveling part of this puzzle. Amazon recently established a nexus
with the state of Utah and therefore became obligated to collect sales taxes. Amazon
reportedly captured 33 percent of all US online purchases in 2015, according to
the magazine Internet Retailer, up from 25 percent in 2012. Conversely, direct
selling firms will continue to create challenges as long as the current data
methodology and MLM business model is preserved.
