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.”[1] Not all consumer
spending is captured through retail trade transactions, but a large share is.
Broad-category
examples of retail trade sectors are motor vehicle sales, furniture stores,
electronic 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 on the internet. Examples
include Amazon, Zappos, Overstock.com, or eBay. These types of retailers have
grown rapidly in the past 15 years and their presence is reshaping the retail
trade landscape.
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 Eastern Region:
Non-store Taxable Sales Are Gaining,
But Not as Fast as Employment. Why?
Taxable sales in non-store retail have not gained as a share
of total taxable sales as quickly at the employment share has increased. This
is primarily due to the fact that 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 BackCountry.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 large shares 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.
About NAICS
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.”[2] Stated
simply, NAICS groups businesses together based upon what they do.
Hierarchical in
nature, NAICS begins with a broad categorization and narrows its focus through
subsector levels. As an example, the educational services sector includes all
institutions focused on providing instruction and training. At the subsector
level, the focus narrows to elementary schools, colleges and trade institutions,
etc.
The broad sector
known as retail trade includes several underlying categories, such as motor
vehicle sales, furniture stores, electronic 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 dÅTERRA. 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 an
illustration of this in a later section.
Internet sales have increased dramatically. Data from the
Federal Reserve shows that internet sales are 8.5 percent of total retail sales
as of January 2017. Nationally, retail’s 2016 share of employment is 11.2
percent. It is important to note that NAICS classifies businesses by what they
do at a location, rather than by their business model. For example, the
BackCountry.com location in West Valley City is classified under warehousing
since that location is a warehouse.
Back to the East
In the Eastern Region (Carbon, Duchesne, Daggett, Emery,
Grand, San Juan, and Uintah counties) retail trade is correlated with commodity
prices because of the areas reliance on mining. When prices are high there is
more discretionary income in the community, therefore more retail sales; and, correspondingly,
retail establishments expand to meet demand. The reverse happens when commodity
prices decline, slowing the economy and reducing discretionary income,
therefore lowering retail sales and potentially retail employment.
The commodity-dependent industries can expand and shrink
their employment in large quantities. When these industries’ employment
increases, so then does retail trade employment. But commodity-dependent
industries can grow so rapidly that their share of total employment also grows
rapidly. Even though retail trade employment goes up, it does not grow as
rapidly; and, therefore, retail’s share of total employment actually declines.
Retail sales in the Eastern Region also differ from the
national archetype because of broadband internet usage. The Pew Research center
estimates that there is a 10 percent “gap” in broadband access between urban
and rural internet users. This impacts the ability of Eastern Region residents to
purchase goods on-line and forces them to rely on “brick and mortar” stores.
The composition of the retail trade labor force in the Eastern
Region is now different than for the state as a whole. Utah’s retail trade
labor force has greyed significantly over the past 15 years. In 2001, 11
percent of the labor force was under 18 while 8 percent was older than 55. As
of 2016, only 3 percent of the sector’s labor force was under 18 while 16
percent was over 55. Unlike the state as a whole, the age composition of the
Eastern Region has remained unchanged from 2001; the share for workers under 18
was, and still is, 13 percent. The analogous figure for workers older than 55
is 26 percent.
Conclusions
Traditionally, “retail follows roof tops.” Retailers try
hard not to oversaturate given an area’s population. It follows that the ratio
of retail-employment-to-population should fall over time. Given internet
competition, it takes more people to generate the same amount of retail sales.
The state data seems to weakly support this hypothesis. The statewide share has
fallen by 0.4 percentage points since 2001, hardly an indication of a “retail
apocalypse.” Surprisingly, the share in the Eastern Region has fallen by 0.6
percentage points. Analysts speculate that the larger decline is influenced by
incomes in the Eastern Region’s energy-based economy. Internet purchases are
positively related to income, and energy economies have greater income than
agricultural-based economies. Further, because of the internet, consumers in
Vernal or Roosevelt has infinitely more choices than they did a decade ago.
Perhaps the state’s recent agreement with Amazon will be
helpful in unraveling this puzzle. Amazon recently established a nexus with the
state of Utah and therefore became obligated to collect Utah sales taxes. Amazon
reportedly captured 33 percent of all U.S. online purchases in 2015, according
to the magazine Internet Retailer, up from 25 percent in 2012. In response to
this development, revenue estimators for Salt Lake County have added a half
percentage point to their estimate for 2017 sales tax collections. It will be
interesting to see how Amazon’s actions will impact the
Eastern Region.