Unemployment Insurance Claims Data Shed Light on the Local Economic Impacts of COVID-19 Public Health Directives

By Lyndsey Stram, Regional Economist; Lecia Parks Langston, Senior Economist

“You have power over your mind — not outside events. Realize this, and you will find strength.” Marcus Aurelius

In the wake of the COVID-19 pandemic, businesses lost revenues and workers lost jobs. But because of the time it takes to collect and collate data, economists have been left without much information to quantify the economic impacts at the local level.

But there is one ray of data illumination. Claims for unemployment benefits are promptly available and provide information about a large cross section of the economy. This post will outline what light unemployment claims data sheds on the state of the Uintah Basin’s economy.

While not all workers are protected by unemployment insurance laws, roughly 95% of jobs are covered. This makes claims data an exceptional source of information about the economy. Not included under unemployment insurance laws are most self-employed workers, about half of agricultural employment, unpaid family workers, railroad personnel (covered separately) and many nonprofit organizations (such as churches). Also, some out-of-work employees may not have worked a sufficient work history to qualify for unemployment insurance benefits, but may file anyway.

Fortunately, in this time of economic distress, the social safety nets of the unemployment insurance program, special national COVID-19 funding and social programs are working together to keep workers’ income and well-being stable.

Unemployment claimants and the unemployed; they aren’t the same

Also, keep in mind that, in addition to individuals drawing unemployment benefits, the unemployment rate includes those entering and re-entering the workforce and non-covered groups without current employment. This means the number of “unemployed” will be greater than the number of claimants. In “normal” times, only about 40% of the “unemployed” are claiming benefits.

The generally reported unemployment rate also has a work-search requirement. If you haven’t made any minimal attempts to find work, you aren’t counted as “unemployed.”

Watch this Space

While this analysis won’t be updated on a regular basis, new data will be added to the data visualization on a weekly basis allowing readers to check back for the latest information.

An Unprecedented Event

Not surprisingly, first-time claims for unemployment benefits soared in Utah and across the nation as the pandemic swept across the country. This increase is unprecedented since the creation of unemployment insurance coverage during the Great Depression. Week 12 (beginning March 16) marks the start of this unparalleled surge in claims. On a positive note, while new claims for unemployment benefits have skyrocketed in Utah, the state currently shows one of the lowest claims rates in the nation.

For the Uintah Basin counties, initial claims peaked in week 14. At the peak, initial claims totaled 500 between the three counties. By week 19, claims have decreased considerably. The levels are now comparable to levels seen during the Great Recession in the Uintah Basin.

Prior to the COVID-19 pandemic, counties in the Uintah Basin averaged 36 first-time claims per week. Afterwards, an average of 317 first-time claims were filed per week.

Who took the hardest hit?

Counties with large shares of accommodations/food service employment have been taking the hardest hit in the wake of the COVID-19 pandemic. This is true in the Uintah Basin as well, where 22% of the accommodations/food services workers in the area have filed claims for unemployment in the recent weeks.

Across all industries on a statewide level, 10% of the covered workforce have filled claims for unemployment benefits. Daggett County has been able to hold onto more of its workforce, with only 5% filing claims. Duchesne and Uintah Counties saw 11% and 13% of the workers file, respectively.

Tourism and COVID-19

Especially in the early stages of the restrictions, this is a story of tourism-dependent industries. Even with a relatively small portion of the Uintah Basin’s employment belonging to accommodations/food services, this industry made up for more than 14% of claims filed since the pandemic started. In addition, the true effect of the pandemic on this industry is masked by a large number of claims classified as industry “unknown” in the early days of the claims flood. Undoubtedly, many of these claims would rightfully be classified in accommodations/food services if the appropriate information were available.

Mining is a large share of the employment in the Uintah Basin and has also been responsible for a large amount of the claims filed — 21% of the regional claims. Retail trade, transportation/warehousing and healthcare/social assistance have also been high claims sectors.

The High and the Low

Although mining and accommodations/food services has generated the largest number of Uintah Basin initial claims in the COVID-19 time period, in percentage terms, other industries have actually suffered more. For example, the administrative support/waste management/remediation (which includes temporary employment services) sector has seen 45% of its workforce file for claims in recent weeks.

Although retail trade has seen a large number of claims, the percentage of its covered employment that has filed claims is relatively low at 7%. In other regions, retail trade saw a large share of the workforce file; but, in rural areas, a larger share of the retail establishments are likely deemed “essential,” meaning more of the workforce remained employed.

Public administration accounts for much of the Uintah Basin employment, and this is a sector that has kept a large share of its workforce employed, buoying the economy of the area.

County by County
Daggett County
• Prior to COVID-19, Daggett County had an average of one first-time unemployment claim per week. This has since increased to three claims.
• Public administration is an industry that has kept much of its workforce employed in the wake of COVID-19. With 49% of Daggett County’s workforce employed in the public administration sector, a relatively small percentage of the county’s covered workforce have filed claims for unemployment — only 5%.
• Like many other areas, the sector that suffered most from the restrictions was accommodations/food services. A significant 45% of this sector’s workforce filed claims for unemployment benefits.
• Prior to COVID-19, Daggett County accounted for 2% of the region’s unemployment claims, which has since decreased to 1%.

Duchesne County
• Prior to COVID-19, Duchesne County had an average of 11 first-time unemployment claims per week. This has since increased to 105 weekly claims.
• Mining and transportation/warehousing accounted for the largest numbers of claims in Duchesne County. Because these are such large industries in the area, the claims as a percentage of the workforce are relatively low — at 12% and 16% respectively.
• Public administration is also an important sector in Duchesne County and only 6% of that workforce has filed claims in recent weeks.
• Prior to COVID-19, Duchesne County accounted for 31% of the area’s unemployment claims. This has increased to 33% of the claims.

Uintah County
• Prior to COVID-19, Uintah County had an average of 24 first-time unemployment claims per week. This has since increased to 209 weekly claims — an increase of 774%.
• Mining and accommodations/food services have been the hardest hit sectors in Uintah County. Nearly 20% of the mining workforce in Uintah County has filed first-time claims for benefits in the wake of COVID-19. For accommodations/food services, more than 24% of the workforce has filed.
• Similar to the other counties in the region, public administration is an important sector in Uintah County. Only 1% of the workforce in that sector have filed claims, which helps offset some of the economic impact of some of the harder hit industrial sectors.
• Prior to COVID-19, Uintah County accounted for 67% of the area’s unemployment claims. This has decreased to 66% of the claims.

Utah's Seasonally Adjusted Unemployment Rates

Seasonally adjusted unemployment rates for all Utah counties have been posted online here.

Each month, these rates are posted the Monday following the Unemployment Rate Update for Utah.

For more information about seasonally adjusted rates, read a DWS analysis here.

Next update scheduled for March 26th.

Utah's Employment Situation for January 2018

Utah's Employment Situation for January 2018 has been released on the web.

Find the Current Economic Situation in its entirety here.

For charts and tables, including County Employment, go to the Employment and Unemployment page.

Next update scheduled for March 23rd, 2018.

Ten Years After ...

December 2017 marked 10 years since the Great Recession first cast its long shadow across the American economy. The recession officially lasted 18 months, but its consequences can still be seen across the country without having to look very hard. We have not had another recession since.

Utah was hit hard at the time, losing a larger share of jobs than the national average; but, we were fortunate to be one of the most resilient states in terms of economic rebound. There are plenty of states where the Great Recession continues to weigh upon them. Employment levels in 14 states are still not back to their pre-recession peak, and another 29 states have only grown 5.0 percent or less. As the working-age population has grown by more than 5.0 percent, the job gains nationally have not been enough to fully employ working-age labor.

Utah lost 7.0 percent employment during the recession. Since that low, employment has recovered by 18 percent. That is the second-best rebound in the nation. From Utah’s pre-recession employment peak to now, Utah’s employment has increased by 9.5 percent, third best in the nation. Yet, Utah’s job growth has not been enough to absorb all of the labor force growth during that time. Utah’s unemployment rate is low, but the percent of the working-age population in the labor force is several percentage points below the pre-recession norm — telling us that potential labor is still not as fully engaged with the job market as before the recession.

As a whole, Utah has had a notable recession rebound, but those gains have not been shared equally across all regions. Just like the national profile, some areas have bounced back strong while others are still lagging behind. The state’s metropolitan areas have grown well, but many of Utah’s rural areas cannot say the same. Nine counties have employment levels below their pre-recession peaks.

In this issue of Local Insights, we profile Utah’s regional and county economies in light of the 10-year span since the Great Recession.

Eastern Utah Overview

This post relies on analysis of employment shares and growth by industrial sector. Sectors are defined using the North American Industrial Classification System (NAICS).

The general theme in Eastern Utah (with certain prominent exceptions) is that the Great Recession initiated a trend that shrunk the share of private-sector revenues driving the local economies and increased the share of the public sector
.

All industries receive their funding from either the private or public sectors. Receiving funding from the public sector means that some level of government is paying for that industry’s services, even if the services themselves are provided by non-government businesses. For example, hospitals are generally private-sector ownership (non-government), yet through Medicaid and Medicare receive much government funding.

This post will highlight three industries due to their significant level of government funding: 1) public administration, which is exclusively government-owned services; 2) educational services, which in Utah is also predominantly government-owned; and 3) health care and social assistance. These will be identified as “public sector.” All other industries will be the “private sector.”

In the tourism-dependent counties, the above definition of public sector itself may not fully capture the government-funded importance. Throughout parts of eastern Utah, tourism is due to scenic beauty and national parks, with government ownership and funding the economic underpinning. Hotels, restaurants and gas stations may not get their revenues from the government, but they do from the tourists who come to see and pay for the government-provided access. All one has to do is observe a government budget shutdown to see the permeating effect the government-funded foundation has even on the private sector.

This analysis will evaluate the share of the three, above-cited industries that receive much government funding, how that funding may have changed between the Great Recession and now, and discuss, as needed, where tourism is also prominent.

Southeastern Utah

Employment growth in Southeastern Utah (Grand and San Juan counties) has lagged the statewide average since the Great Recession. Growth since the third quarter of 2008 has registered at 10 percent compared with the 17 percent rate for Utah. However, these two counties do not behave as a single economic unit, so their stories differ.

Grand County

Grand County pulled out of the recession and has experienced strong employment growth. Its 19 percent rate slightly exceeds the state’s growth of 17 percent. These gains have been fueled by tourism. The history of other sectors is mixed.

Table 1 shows the employment shares by sector for the third quarter of 2017 and the corresponding quarter in 2008, which corresponds to the depth of the recession. For ease of reference, NAICS codes are included.

Table 1

Grand County Employment Share by NAICS Sector

In 2008, 81 percent of Grand County’s employment share was in the private sector. In contrast to the general Eastern Utah trend, this private-sector share had increased to 82 percent by 2017. Tourism (defined as NAICS sectors 71 and 72) dominated the labor market with 40 percent of the total in 2008, and increased its share to 44 percent by 2017. However, if tourism is excluded from the calculation, the remaining private sector share actually decreased from 41 percent to 37 percent.

Table 2 shows total employment change by sector from the third quarter of 2008 to the third quarter of 2017.

Table 2

Grand County Employment Change by NAICS Sector

Private sector employment has grown by 20 percent across the 2008-2017 period. Moab’s national prominence as a recreation center has fueled explosive growth in the leisure and hospitality sectors (sectors 71 and 72). This has swamped the modest growth experienced in large sectors, such as retail trade and public administration. In fact, private sector growth was only 8.0 percent when excluding the tourism sectors. Employment losses associated with the Moab Uranium Mill Tailings Remedial Action Project was a small but still significant drag on private sector employment. Since this is a clean-up project, employment is by nature of limited duration and should approach zero in the immediate future.

Of interest is the growth in manufacturing. This is driven by the local brewery. Regional beer distribution has also had a complementary effect on the relatively small warehousing and transportation sector.

San Juan County

In contrast to its northern neighbor, San Juan County’s employment growth has been stagnant and increasingly dependent on public funding. Table 3 shows 2008 and 2017 industry shares by their associated NAICS codes.

Table 3

San Juan County Employment Share by NAICS Sector

In 2008, more than 57 percent of total employment was concentrated in sectors independent of government funding. This share had shrunk almost 8.0 percentage points to a little less than 50 percent by 2017.

Table 4 evaluates current–quarter employment against 2008. The cumulative employment in sectors not dependent on government funding decreased by more than 14 percent.

Table 4

San Juan County Employment Change by NAICS Sector

Even the leisure and hospitality industry (sectors 71 and 72) saw a decline of almost 5.0 percent. This is surprising given the area’s natural beauty and the tourism boom in neighboring Grand County.

The only significant growth in spending came from the public sectors. At 47 percent, the healthcare sector was by far the greatest contributor of jobs since the Great Recession, followed by education at 10 percent. The comparable growth rate for the nation is only 20 percent.

Castle Country

The story of Emery and Carbon counties since the Great Recession mimics the coal industry story across the United States. The value of coal production has fallen 34 percent since the third quarter of 2008. During the same period, regional employment has fallen by 15 percent. The correlation between these two numbers is overwhelming. Statistically, the correlation coefficient value is 0.9 where a value of 1.0 is perfect correlation.

Table 5 shows shares by NAICs sectors between 2008 and now. What is obvious is the striking decline in the mining sector’s employment share. Less obvious is the associated fallout to the rest of Castle Country’s private sector. The share of jobs not dependent on government funding shrunk almost 5.0 percent from 71 percent to 66 percent.

Table 5

Castle Country Employment Share by NAICS Sector

Even the leisure and hospitality industry (sectors 71 and 72) saw a decline of almost 5.0 percent. This is surprising given the area’s natural beauty and the tourism boom in neighboring Grand County.

The only significant growth in spending came from the public sectors. At 47 percent, the healthcare sector was by far the greatest contributor of jobs since the Great Recession, followed by education at 10 percent. The comparable growth rate for the nation is only 20 percent.

As Table 6 shows, with the economy shrinking, most of the increase in the public share is due to a smaller rate of decline rather than growth.

Table 6

Castle Country Employment Change by NAICS Sector

For example, the education sectors’ employment share increased from 10 percent to 11.5 because employment only shrunk by a “moderate” 2.0 percent from 2008 to the present.

In sympathy with the coal industry’s decline, the Castle Country’s private sector has shrunk by 20 percent. There really has been no substitute for the high paying mining jobs that formerly powered Castle Country’s economy. In keeping with the national trend, health care has been a net creator of jobs but the 8.0 percent growth in the area badly lags the national statistic of 20 percent.

Uintah Basin

As of late, the changes to the Daggett, Duchesne, and Uintah County economies have been dominated by the oil and gas industry. However, since the Great Recession, changes in oil prices do not completely explain the region’s economic history. In fact, the correlation between the price of oil and employment is only moderate/strong at 0.59. This is due to public sector growth in the Uintah Basin.

Table 7 shows Uintah Basin employment shares from 2008 and 2017.

Table 7

Uintah Basin Employment Share by NAICS Sector

In 2008, the mining sector was more than 23 percent of the employment base. The price of a barrel of West Texas Intermediate crude oil (the U.S. benchmark) averaged $118/barrel. In 2017, the mining sector had shrunk to almost 16 percent of the base. The average price of West Texas Intermediate averaged $48/barrel.

Private sector employment, defined as those sectors not directly dependent of government spending, declined from almost 80 percent of the total to 71 percent. Other sectors reacted similarly. Construction declined by almost 3.0 percent. This loss is not just due to fewer homes built; the oil and gas industry requires substantial amounts of construction services.

As shown in Table 8, total employment has declined by 16 percent and the majority is attributable to the 43 percent employment decline in the mining sector. Associated industries like transportation and warehousing, and wholesale trade declined in sympathy.

Table 8

Uintah Basin Employment Change by NAICS Sector

The biggest increase in public sector employment was the 34 percent gain in the education sector. This principally an expansion in higher education. In 2010, Utah State University opened the Bingham Entrepreneurship and Energy Research Center in Vernal, a 70,000 square-foot research hub with an entrepreneurship center, classrooms, teaching labs and student services. In addition, the Uintah Basin Applied Technology College opened an 83,475 square-foot industrial technology facility and classrooms.

As with other Eastern Utah regions, the healthcare sector was a strong net job contributor, but less than the comparable national statistic.

Of note is the 18 percent increase in the public administration sector. Since public administration is typically funded by local taxes, this kind of growth is unusual in the face of declining total employment.

Economic Hurdles in Rural Utah

by Mark Knold

Utah is a geographically large state. Based on total area, it is the 13^th largest state, implying there is room to spread out. Despite all this space, Utah’s population distribution is quite concentrated. According to the U.S. Census Bureau, Utah is the nation’s 9^th most urbanized state. This dichotomy has shaped a state with two economic profiles — one urban, one rural. It can be challenging for a state dominated and prospering within the urban to extend its economic bounty to the betterment of the rural.

What is rural? It depends upon one’s objective behind the question. Most define rural by a visual scan of the landscape. A lot of open land and not many people — rural. Yet economically, the view can be different. An area may look rural, but if the economic vitality of its populace is strongly integrated with a nearby urban area, then this creates a different perspective. The latter is a preference of the federal government — an entity that often makes allocation or distribution decisions based upon economic factors.

No matter how one technically defines rural, the Governor’s Office recognizes a recent dichotomy in Utah’s economic prosperity. Since the Great Recession, Utah has had compelling economic success. Yet, most of this is concentrated in Utah’s urban centers. Portions of Utah’s rural communities are not seeing matching levels of success. Utah’s Lt. Governor recently observed, “Not all of Utah’s communities are full participants in this economic success. Many counties off the Wasatch Front are experiencing challenges.”

In response to this economic disparity, the Governor’s Office has launched the 25k Jobs initiative — an effort for businesses to create 25,000 new jobs in 25 Utah counties by 2020. With this spotlight on rural Utah’s economics, let’s take a look at some of these rural challenges.

To most, jobs deliver their income and means for living sustenance. Therefore, employment, and peripheral variables associated with employment, becomes the strongest proxy for measuring the Utah economy’s health. We will look at Utah’s counties through the lens of employment, unemployment, the labor force and how the industry structure speaks to the underlying performance of these variables.

A profile of job growth becomes a starting point. Economic performance needs to be viewed with a somewhat long lens. The Governor’s 25k Jobs initiative was not born from a short-term disorder, but instead is recognition of weak longer-term fundamentals. To illustrate this perspective, one needs to backdrop the short-term mechanics against the longer-term dynamics.

The County Job Profile chart is an intersection of the short-term trend with the moderate-term. Each county is a bubble, and the bubble size reflects job counts. The chart is divided into four quadrants. The quadrants tell the story of the intersection of the short and moderate-term trends (growth or contraction) and the general health of the county’s economy.

There are two axes of measure. First, the vertical axis represents the short-term. It is the percentage of county job change between 2015 and 2016. Above the horizontal axis is growth — below is contraction.

Second, the horizontal axis measures the moderate-term. It is the percentage of job change over the past five years (2011-2016). To the right of the vertical axis is growth — to the left is contraction. Where a bubble lies is the intersection of the short and the moderate term.

To illustrate, find Beaver County on the chart. Beaver aligns with around -4.0 percent on the vertical axis, and 8.0 percent on the horizontal axis. This says that over the past five years, Beaver County’s job count has grown by 8.0 percent, but over the past year it has contracted by around 4.0 percent. This implies that Beaver County’s economy may be slipping a bit. A one-year view would imply a problem. A longer-term view places this short-term setback against a broader perspective of overall prosperity.

The quadrant of concern is the Contracting quadrant. These economies have contracted over both the most recent year and the past five years. No matter how one wants to define rural as outlined above, all of these contracting counties identify as rural.

In-county jobs alone are not the complete picture. For example, a large percentage of Morgan County’s residents commute to Weber or Davis counties for work. If jobs are not being germinated in Morgan County, the county and its population can still prosper from its ties with the urban area.

An additional way to look at the economy is through the lens of the labor force. The labor force consists of those 16-years and older who are either working or looking for work. It is based upon where people live, not where they work. A worker living in Morgan County will be represented in Morgan County on the following chart (County Labor Force Change); yet, if they work in Weber County, their job is represented in Weber County on the prior chart. Adding this perspective helps to round out a county’s profile.

The structure of the County Labor Force Change graphic is the same as the prior chart. The area of vibrancy is the upper-right quadrant where the labor force is increasing. The quadrant of labor force contraction is the lower left. A decline in the labor force occurs when people become discouraged and leave the labor force — yet stay in the county, or when people leave the county altogether. Either way, a decline in the labor force signals a fundamental negative in the economic trend.

Depending upon the variables measured, a gain in one and a decline in another can both be positive. Job growth and an unemployment decline are both positive. To associate the positive with low unemployment, the quadrant message on the Unemployment Rate chart has been transposed.

Every month an unemployment rate is calculated for Utah and each of its counties. A county’s unemployment rate can be measured against the Utah statewide average unemployment rate. In the following graphic, county rates are mathematically compared against the statewide rate (seasonally adjusted), recorded and then summed across time.

For example, if a county’s unemployment rate is 5.5 percent and the statewide rate is 4.0 percent, then that county’s difference for that month is 1.5. If a county’s rate were to be 3.5 percent against the statewide rate of 4.0 percent, then the difference is -0.5. These monthly differences are tallied and summed. A high score speaks to a consistent and persistent unemployment rate above the statewide average. In other words, these are counties with a continuous environment of high unemployment.

The horizontal axis is a measure since 2000 and the vertical axis a measure since the beginning of the Great Recession (2008). The axis intersection is not at zero to isolate the “concern area” within the upper right quadrant. The statewide average is consistently close to the Salt Lake County average, so a sizeable number of counties will have sums slightly above the statewide average; yet, this doesn’t imply an unemployment problem. But the non-zero intersection is utilized to emphasize the counties that do have an outstanding unemployment disparity.

Across these various charts, a common group of rural counties emerge in the weak quadrant. These include Carbon, Emery, Garfield, Piute and San Juan counties; with Duchesne and Uintah hanging on the edge. There is a common theme that surrounds this grouping and it centers upon low economic diversity.

An economy’s ability to be consistently positive has a strong foundation in a diverse mix of industrial employment. Think of it in terms of “not putting all your eggs in one basket.” Economic diversity is spreading jobs across many baskets. Diversity is desirable because the overall economy is not dominantly influenced by one or a handful of industries whose poor performance weighs upon the whole.

A Hachman Index is an evaluation tool measuring to what degree an economy may or may not have all its eggs in one basket. In the Hachman Index, a measure of 1.0 means your eggs are well distributed across many industries. Conversely, numbers approaching zero point to a high concentration in one or a handful of industries.

Many of the counties that score low on the previous charts are the same ones on the lowest tier of the following Hachman Index chart. This chart represents the placement of economic diversity upon employment change of the past five years. A county will be placed high or low (vertical axis) on the chart depending upon its Hachman Index score. It will align right or left (horizontal axis) depending upon its five-year employment change. Metropolitan counties have higher economic diversity than rural counties — placing them higher on the chart. They are also further to the right on the chart, showing stronger employment growth. There can be individual exceptions, but the general theme is that lack of economic diversity is a foundational impediment to economic viability. Industrial diversity, though difficult to artificially induce, is a desired remedy to counter sluggish economic performance.

Lack of diversity does not mandate a poor economy. A reproduction of this chart five years ago would have placed Uintah and Duchesne counties still low on the chart, but their five-year growth rates would have been off the chart, needing arrows to point out beyond the chosen 40 percent horizontal axis limit.

Those economies are dominated by energy production. When energy prices are high, their economies can soar. When energy falters, they often do likewise. They are striking examples of economic outcome being determined by a dominant industry.

In summary, there is a dichotomy within the Utah economy between urban and rural. The urban economies are diverse and, therefore, more economically balanced; while many rural economies are not. With some rural counties the economic distinction is not a wide divide; but in the rural counties where the divide is pronounced, the underlying theme is often a low level of economic performance.

A Look at the Retail Trade Industry in Eastern Region

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 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 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.

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[1] OECD Glossary of Statistical Terms.

[2] U.S. Census Bureau

Census Bureau Tool Provides Labor-Force Insight for Utah

Across the United States, jobs are quantified through each state’s unemployment insurance program. Those programs provide the potential for laid-off workers to receive unemployment benefits — the goal being to bridge the gap between workers’ lost jobs and their next jobs. An eligible recipient’s weekly benefit amount is based upon their earnings from recent work. This begs the question, how does Utah’s unemployment insurance program know how much an individual recently earned while working?

That answer is supplied by all businesses that hire workers, as they must report their employees and pay as mandated by the unemployment insurance laws. Companies identify their individual workers and those workers’ monetary earnings for a calendar quarter. As businesses are identified by their industrial activity and geographic location, it is through the unemployment insurance program that aggregate employment counts by industry and location are calculated.

Yet each state’s profiling of individuals is quite minimal in the unemployment insurance program. The U.S. Census Bureau can bring more light to the overall labor force by supplementing said information with gender, age, race/ethnicity and educational attainment (imputted from American Community Survey responses) for Utah’s labor force.

The Census Bureau packages this information through their Local Employment Dynamics program and makes available said data on its website. Here at the Department of Workforce Services, we recently downloaded and packaged Utah-specific data from said website and summarized it in the attached visualization.

Various data “tabs” are available, presenting Utah’s economy from different angles, ranging from industry shares within the economy to the age-group distributions of the labor force, to gender and race distributions. These labor variables can be viewed for the state as a whole, or by each individual county.

Some statewide highlights:

Industry — industrial distribution is quite diverse, which provides strength within the economy. Distributions do fluctuate with time, with manufacturing seeing its share lessen while health care and professional and business services shares have increased.

Age — the bulk of Utah’s labor force is composed of 25- to 44-year-olds. Older worker shares have increased over the past 15 years, yet still remain a non-dominant portion of Utah’s labor force. The youngest segments of the labor force declined noticeably during the Great Recession due to less participation, and that trend remains.

Educational Attainment — turnover rates are understandably highest with workers under the age of 25 as they strive to build their educational foundation and also find their niche in the labor market. A trend does stand out where the more education that a worker attains, the lower the turnover rate businesses experience from said educational classes.

Race/Ethnicity — Whites account for around 80 percent of Utah’s labor force. The Asian community is small but slowly increasing in share, and is also characterized with the lowest turnover rate and the highest new-hire wages.

Gender — males comprise about 55 percent of Utah’s labor force. The female share of 45 percent is higher than the national average. Roughly 35 percent of working females work part-time compared to 15 percent for males. Therefore, female new-hire wages are considerably lower than male new-hire wages. (Note: employer reporting into the unemployment insurance system is not hourly wage rate reporting but instead total calendar quarter wages paid. Therefore, calculations can only be made upon total quarterly wages, and part-time employment weakens this measure).

As for the various counties in the region, here are some labor highlights:

Uintah Mining employs about the same share that it did in 2000. In 2000 and 2016, the mining sector accounted for 16 percent of all jobs. The age of the workforce has increased markedly. In 2000, 32 percent of the workforce was 25 or younger. The current share is 19 percent. Paradoxically, the share of workers with a high school diploma or less has actually increased. In 2000, this group comprised 33 percent of employment. The 2016 number is 39 percent.

Duchesne The mining sector has become the dominant force in the economy. Its share increased from 9 percent in 2000 to 21 percent in 2015. Trade and Education have shrunk as a share of total jobs. Their combined share decreased from 37 percent in 2000 to 25 percent in 2015. Like Uintah County, the age of the workforce has increased markedly. In 2000, 31 percent of the workforce was 25 or younger. The current share is 16 percent. The share of workers with a high school diploma or less has also increased. In 2000, this group comprised 34 percent of employment. The 2016 number is 41 percent.

Daggett The Daggett County economy has become more diverse. In 2000, Public Administration and Leisure and Hospitality, and Education made up 79 percent of all jobs. In 2015, this number had decreased to 70 percent. Daggett County has also seen the age of the workforce has increased. In 2000, 45 percent of the workforce was 25 or younger. The current share is 15 percent. Workers 65 years and older increased their share from 4 percent in 2000 to 10 percent in 2015. Consistent with the trend, the share of workers with a high school diploma or less has actually increased. In 2000, this group comprised 45 percent of employment. The 2016 number is 21 percent. The workforce, while still overwhelmingly white, has become more diverse. The minority share of jobs grew from 6 percent in 2000 to 11 percent by 2015.

Native Americans in Utah and Uintah County

 

The word 'Utah' means 'top of the mountains' and is derived from the Ute Indian language." --From a Utah tourist brochure dated June 1955.

"The word 'Utah originated with the people inhabiting that region..of the Utah nation, which belongs to the Shoshone family. There were many tribes...There were the Pah Utes...and many others. Pah signifies water. ...Pah Utes, Indians that live about the water." --from Hubert H. Bancroft's "History of Utah." published in 1964.

"Utah comes from the Ute tribe and means 'people of the mountains." --From the Information Please 1994 almanac.

"Utah -- from a Navajo word meaning upper, or higher up, as applied to a Shoshone tribe called Ute. Spanish form is Yutta. English is Uta or Utah." --From The 1979 World Almanac and Book of Facts.

These quotes compiled by the Utah Education Network website show that we are still not sure where the  state’s name came from but fairly certain that it originated with the state’s indigenous peoples. There are roughly 32 thousand Native Americans in Utah, or a little over 1 percent of the population.

There are eight federally recognized Indian tribes in the state:

·         Confederated Tribes of the Goshute Reservation (Nevada and Utah)

·         Navajo Nation (Arizona, New Mexico and Utah)

·         Northwestern Band of Shoshoni Nation 

·         Paiute Indian Tribe of Utah  (Cedar Band of Paiutes, Kanosh Band of Paiutes, Koosharem Band of Paiutes, Indian Peaks Band of Paiutes, and Shivwits Band of Paiutes)

·         Skull Valley Band of Goshute Indians of Utah

·         Ute Indian Tribe of the Uintah and Ouray Reservation

·         Ute Mountain Ute Tribe (Colorado, New Mexico and Utah)

These tribes are distributed across the breadth of Utah with concentrations in the eastern and southwestern parts of the state. There is also is significant Native American presence along the Wasatch front population centers.

The Department of Workforce Services has just published an interactive graphic detailing demographic information about Utah’s Native American population. The visualization has six tabs.  Unlike other department graphic tools, it has a principal focus on raw numbers rather than proportions because of the huge disparity in populations at the county level. For example there are thousands of Native Americans in San Juan County but only one person in Rich County.

The first tab presents median earnings defined as compensation from all employment plus other sources of income. This is a useful measure when comparing the income of workers who may receive non-wage income from the sales of agricultural products or bonus income from the sale of tribal natural resources. The number of counties is limited because of the paucity of reliable data in counties with small Native American populations.  Statewide, full time males earn slightly less than their national counterparts. The same is true for female Native American Utahns. It must be noted that Utah tribes are geographically disadvantaged when compared to their Pacific and eastern peers; tribal seats are far from the major population areas and therefore unable to market their legal and cultural advantages as effectively.

The second tab shows veterans status by age. Native American Utahns are less likely to be former members of the armed forces.  For Utahns and the nation as a whole, younger people are much less likely to be veterans than their elders.

The third tab shows educational attainment, Here, the results are mixed. The distribution for male Utahns is about the same as for male Native Americans nationally; around 13 percent of males have college degrees and roughly 23 percent have not finished high schools. However only 11 percent of Utah females have college while the comparable national statistic is close to 13 percent  Further, Utah lags the national statistics with respect to the native American females without a high school; diploma by roughly two percentage points. 

The fourth tab shows Native American home ownership. Here the Utah statistics are very similar to the nations; the majority of the population owns their home either outright are with a mortgage. Around 45 percent rent.

The fifth and final tab details poverty rates. Roughly 32 percent of Utah Native Americans are in poverty. In contrast, 28 percent of their national counterparts are in poverty. Roughly 55 percent of the population in poverty is female; the national analogue is only slightly less. 6 percent of the Utah’s senor Native American population exists below the poverty level. The national number is markedly higher at 11 percent.

Uintah County

The Uintah and Ouray reservation is located in Northeastern Utah. The tribal seat is Fort Duchesne, approximately 150 miles east of Salt Lake City. It is the second largest Indian Reservation in the United States and covers over 4.5 million acres. It lies in parts of seven counties: Uintah, Duchesne, Wasatch, Grand, Carbon, Utah, and Emery. The reservation (in some form) has been in existence since 1864.

The vast majority of the tribe’s population resides in Duchesne and Uintah counties. The latest Census Bureau estimates for population are 800 Native Americans Duchesne County and 2,631 Native Americans in Uintah County. This represents 4 and 7 percent of the two county’s total population, respectively. This blog posts will concentrate on Uintah county residents; this constitutes the vast majority Uintah Basin residents. Furthermore, like their nonnative counterparts, the statistics for Duchesne and Uintah Counties are quite similar. This underlying reason for this is that, like the rest of the Uintah basin, economic activity is dominated by natural gas and oil extraction.

Uintah County Native American earnings are roughly equivalent to the national average; this is no doubt due to natural resource distributions. The earnings of the Uintah County’s Native Americans working full time are relatively unaffected by sex; median earnings are roughly the same for both men and women  This is in contrast to the state and national average; women tend to earn much less than men. However, the male/female part time work differential is much larger than the one reported both statewide and nationally.

The proportion of Native American veterans in Uintah County is around 11 percent. This lies between the state and national rate of 9 percent and 14 percent, respectively.  Veteran’s status for those over 65 years old is very similar to the national archetype. However, county Native Americans ages 18-65 are much less likely to be veterans than Native Americans nationally; only 5 percent of county residents are veterans as opposed to 11 percent across the country.    

Only 6 percent of Uintah County Native Americans hold bachelor’s degrees. Again, the statewide number is close to 12 percent. In contrast, the proportion of the population without a high school diploma or equivalent is 33 percent; the statewide number is 21 percent.

Roughly one-half of the population owns their homes free and clear. This statistics overstates the areas’ wealth. Federal law prohibits the alienation of tribal lands. Since nonnative lenders cannot foreclose, there is virtually no mortgage market on the reservation.

Poverty is much less prevalent for Native Americans in Uintah County than statewide; 27 percent of the population is in poverty. Again, the statewide number is around 32 percent. Also, this rate is roughly the same as national poverty rates. In addition, the poverty rate for both males and females is roughly the same in Uintah County. The lower rates are probably caused by the tribe’s ability to distribute royalty income from natural resource extraction. However the proportion of tribal member over 65 in poverty is lower than the statewide rate but above the national rate; 37 percent of elderly tribal members are in poverty.

 

 

Better, Faster, Smarter... Check out our new website design!

Go to: JOBS.UTAH.GOV/WI to check it out

Information is the treasure of the current age. The instant access to information since the advent of the Internet has transformed societies in ways that thousands of years prior had not. Information can lead to knowledge, and — with increased knowledge — better efficiencies and way of life. If information is vital, then the presentation of information has also risen to a prominent level. With this, the Utah Department of Workforce Services has made some organizational improvements to its economic webpages. Various economic data categories are not mutually exclusive, but we made an effort to compartmentalize economic data for a better organizational display and navigation. We also added a new feature area that taps into various national data elements and measurements from the Federal Reserve Economic Data (FRED), the database of the Federal Reserve Bank of St. Louis. FRED’s added value is national — and Utah — economic indicators. More on FRED’s contribution below.

Depending on the subject, economic data can be categorized as either broad or specific. For example, the demographic makeup of an area and how that impacts an economic structure is a broad-subject approach. Conversely, a current monthly snapshot of the Utah economy, its job growth and unemployment rate is a more specific observation. Our economic webpage has four “portals” through which to “categorize” and search for information. One portal is broad, while the other three are more specific in nature.

Topic Portals

The monthly employment profile just mentioned is a specific topic and gets its own “portal,” entitled Employment Update. Here, the most current Utah economic performance can be explored and summarized. The information found here is what often gets cited in the local news media in reference to the current Utah job performance and unemployment rate.

The second specific “portal” is labeled Local Insights. This is a quarterly profile of the Utah economy down to a county level. Each county is summarized with its own economic performance, including job growth, unemployment rate, housing starts, taxable sales and other profile variables. The common theme here is a county-specific approach.

The third specific “portal” is Reports and Analysis. Workforce Services’ economic forte is the labor market. Things over and above the everyday reporting on the labor market are presented here. Sometimes we do special economic studies, other times we will report on specific economic groups within the labor force, like women or veterans. Anything we do that is not an often repeated or ongoing report are grouped here.

The final “portal,” and possibly the one that will be most used, is labeled Economic Data. The core of our data collection and analysis is concentrated here. Employment data, occupational data, wage information and demographic profiles are just some of the major economic themes found in this area.

FRED's on site

As mentioned earlier, we have added an economic indicator area tapping into FRED, which is a massive compilation of economic data from various sources — primarily government statistical agencies, but also some nongovernmental organizations. Workforce Services economists have gone through the list and selected a handful of the most useful data series for gauging the performance of Utah’s macro economy and gaining insights into expected trends. Utah functions within the national economy, so the national economic indicators profiled here are intended to also be guiding influences on the Utah economy. These indicators include composite indexes; a recession probability indicator; leading indicators, such as construction permits and the yield curve; coincident indicators, such as real GDP and employment; and price indicators, such as the consumer price index, regional housing prices, and oil and gas prices. Each chart has a detailed description of what the data represent and how they may be useful.

Keeping relevant with the fast-changing pace of the Internet and data presentation is our goal at Workforce Services. We hope these changes help to better present our broad package of economic data offerings.