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

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 YearsAfter...

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.

---

[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:

Carbon The share of workers employed in the mining sector slightly increased. In 2000, 9 percent of all Carbon County jobs were in mining. The analogous number for 2015 was 10 percent. The age of the workforce has increased markedly. In 2000, 31 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 30 percent of employment. The 2016 number is 38 percent.

Emery In 2000, mining made up 19 percent of the job base. As of 2015, mining’s share has shrunk to 9 percent. In 2015, the three biggest sectors were construction (13 percent), Trade (15 percent), and Education (13 percent). As with Carbon County, the age of the Emery County workforce has increased. In 2000, 24 percent of the workforce was 25 or younger. The current share is 16 percent. The 55-64 year old cohort has increased its share from 9 percent in 2000 to 22 percent. The shares of jobs by educational attainment has remained fairly stable over time in the county.

Recent News for the Utah Coal Fired Electricity Market

PacifiCorp has just released its 2017 Integrated Resource Plan (IRP). The IRP “presents the company’s plans to provide reliable and reasonably priced service to its customers. The analysis supporting this plan helps PacifiCorp, its customers, and its regulators understand the effect of both near-term and long term resource decisions on customer bills, the reliability of electric service PacifiCorp customers receive, and changes to emissions from the generation sources used to serve customers.”

The IRP has a 20-year forecast horizon and encompasses their entire service area, including Utah.

From a Castle Country labor market perspective, the IRP is particularly useful for deriving the utilities’ outlook toward the local coal-fired power plants. Not only would closure of the generating stations result in a job loss at the plants, it would also cause losses in the mining sector. The vast majority of Utah coal is used for electricity generation.

Newspaper accounts have emphasized that the majority of power expansion is from renewable energy sources in Wyoming. However, the biggest news in the document is the downward revision in prior forecasts for demand. On average, forecasted system load is down 5.3 percent when compared to the last IRP. Utah demand is anticipated to increase at less than 1 percent annually due to decreased industrial demand and retail consumer efficiencies.

The plan does not anticipate the installation of catalytic reduction equipment in Utah. Avoiding installation of this equipment will save customers hundreds of millions of dollars. It also notes that the EPA requirement to have this equipment installed is currently under appeal in the U.S. Tenth Circuit Court of Appeals. The IRP presents the requirement being upheld as a downside risk to the forecast and economic viability of coal generated power in Utah.

Currently, coal accounts for around 50 percent of PacifiCorp’s generating capacity. While the plan does not contemplate the early retirement of Utah coal-fired capacity, it also does not envision an expansion. Coal is currently at a competitive disadvantage to natural gas. Further, there are renewable fuel mandates in the Pacific coast states. The end-of-life dates for Utah capacity are given in following table.

Plant	County	Assumed End-of-Life Year
Hunter 2	Emery	2042
Hunter 3	Emery	2042
Huntington 1	Emery	2036
Huntington 2	Emery	2036

 Note that PacifiCorp does not own the Intermountain Power Project (IPP) in Millard County. This plant is owned by the Intermountain Power Agency and exports roughly 75 percent of its electricity to Southern California, principally Los Angeles. That contract was set to expire in 2017. However, the Los Angeles Department of Water and Power (LADWP) modified this contract in 2013, to enable the city to stop relying on coal-fired power no later than 2025. The modifications to the contract require permitting and construction of a natural gas plant at the IPP site to begin no later than 2020. However, there has been no recent news on the permitting process. In a 2016 compliance filing with the California Energy Commission, the City of Los Angeles noted that “The ability to meet this date is contingent upon several factors, including permitting, material procurement and final concurrence of all participants. The commercial operation date may be delayed due to circumstances beyond LADWP’s control.”

 

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.