Friday, April 7, 2017

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. 

Monday, March 27, 2017

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 April 24th.

Friday, March 24, 2017

Utah's Employment Situation for February 2017

Utah's Employment Situation for February 2017 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 April 21st, 2017.

Tuesday, February 14, 2017

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.

Tuesday, December 13, 2016

How Business is Organized in Utah and in Southeastern Utah

Utah has a diversified economy meaning employment is spread out across many industries. Some industries, like banking, tend to have many employees spread among many locations. Others, like hospitals, tend to cluster around a single location. “Mom and Pop” restaurants and law offices usually have one location and a small number of employees.The Department of Workforce Services has constructed an interactive data tool to flesh out these relationships. It uses data collected through Utah’s Unemployment Insurance system. This system produces a comprehensive tabulation of employment and wage information for workers covered by Utah Unemployment Insurance laws and Federal workers covered by the Unemployment Compensation for Federal Employees program.

The program makes two key definitions important for this analysis:
  • A firm, or a company, is a business and may consist of one or more establishments, where each establishment may participate in different predominant economic activity. 
  • An establishment is an economic unit, such as a farm, mine, factory, or store that produces goods or provides services. It is typically at a single physical location address and engaged in one, or predominantly one type of economic activity for which a single industry classification may be applied. 
As an example, Wells Fargo is a firm. Its branch locations are establishments.

The visualization’s first tab makes an important generalization about where people work. A typical Utahn is employed at a large company and works at a location employing 20–250 people.

The second tab shows that larger locations generally pay more than smaller locations. The prominent exception, of course, is shown in the 1-4 employer category. Analyst speculate that the large average wage is due to tax reasons. Sometimes there is a financial advantage in a sole proprietor (which of course would report as one location only) claiming his/herself as an employee. Again, these sort of tax vehicles would benefit higher earning professionals.

Tab 3 shows the percentage of total wages and employment sorted by location size. As expected from the distribution of employment, the bulk of the state’s wages are paid by locations employing 20-250 people with a sizable contribution coming from locations employing more than 1000. However, locations employing more than 100 workers contribute five percent in wages more than their employment would suggest. Schools, universities, and hospitals would be included in this employment range and generally pay higher wages.

The fourth and last tab focuses on firms (companies) by time. Here the results are unambiguous; these firms employ the biggest share of workers. However, it is interesting to note that firms employing 10-49 employees rank third in terms of share. These firms are commonly thought of as small businesses.

Southeast Region 

 Because of confidentiality problems, it is problematic to separate firm data by county. Data is suppressed to protect the identity, or identifiable information, of cooperating employers. Most of the suppressed data are provided by or are substantially attributable to an individual employer. In many cases, suppressions may also be necessary for otherwise disclosable data that may be used to derive sensitive information from another industry or area. However it is widely understood that employment in the region is dominated by government and tourism.

An examination of the Average Monthly Wages by Establishment Size tab (Tab 2) for Grand County shows that larger establishments tend to pay more than smaller establishments. Analysts believe this is attributable to government and health care jobs. On average, establishments pay less than their statewide counterparts. This generalization is also true in San Juan County. It is worth emphasizing that that difference is most pronounced for establishments employing 1-4 persons. Analysts speculate that this is because of the relative lack of small professional businesses in rural areas such as accounting and law firms.

The Quarterly Employment and Wages by Establishment Size (Tab 3) shows employment and wage share by establishment size. As noted above, locations with employment greater than 100 make up 45 percent of total state employment but contribute 50 percent of all wages. In Grand County, locations employing more than 100 workers total 10 percent of employment and contribute 13 percent of county wages. The analogous numbers for San Juan County are 16 percent for employment and 17 percent of total wages. On the small side of the spectrum, locations with less than 10 employees make up 13 percent of statewide employment and contribute 12 percent of wages. In Grand County, these locations make up 24 percent of the employment base and contribute 26 percent of wages. Grand is the only county in eastern Utah where the smallest establishments contribute wages out of proportion to their employment share and it is puzzling considering the relatively low average wage for establishments in this range. In contrast, establishments in San Juan County employing less than 10 workers comprise 18 percent of total employment but only contribute 16 percent of total wages. This again is due to the relative scarcity of small professional firms such as accounting and law firms.

Tuesday, November 8, 2016

Older Utahns in Grand County

The Department of Workforce Services has just published an interactive graphic on older Utahns. Based on 2015 Census Bureau data, it allows researchers (and the simply curious) to “drill down” to the county level.

Roughly 15 percent of the state’s population is age 60 and older. Further, workers age 55 and older make up 17 percent of the labor force. As the population “greys”, the economic importance of older Utahns will naturally become of greater importance. The Deseret News recently reported that in 2015 there were 337 people in Utah over the age of 100. In 50 years, there will be nearly 7,000.
As an example of the information available and the potential for insights, this post will focus on Grand County.

The visualization has six profile segmentations, each represented by a “tab” above the graphs that one can click on. The first tab is a statewide overview of Utahns age 60 and older. From this the reader can generalize that about half of older Utahns still receive taxable income (either passive or active) and/or retirement income. Around 5 percent qualify for some form of public assistance. The typical older Utahn owns his or her home, is married, and speaks English.

The second tab shows unemployment rates by county and age. Older working age Grand County residents experience lower unemployment than the state as a whole, although the relationship reverses when for the post 65 year old cohort.

Tab three shows that this rate is real rather than ephemeral; the labor participation rates up to age 62 are significantly higher than statewide. After age 62, the comparison reverses; older Grand County males are then less likely to participate in the labor force. This pattern seems to be consistent throughout Eastern Utah. Analysts believe that that the higher participation for workers under age 62 are out of necessity; private sector jobs that provide retirement plans are not as common in rural areas. The lower participation rates after age 62 could be a function of the availability of social security and the more physical nature of occupations in rural areas.

The fourth tab shows the older population sorted by poverty level which is $11,670 for an individual. Poverty is much more common in the county than it is statewide. The proportion of residents at the highest end of the scale (more than 400 percent of poverty or $46,680) is less in the county than statewide for older Utahns in the age 55 to 64 cohort but almost exactly the same for the retirement age cohorts. This is most likely a function of migration; urban retirees are drawn to the area and skew the profile toward the statewide statistics.

The fifth tab displays insurance coverage differentiated by educational attainment for older Utahns. Note that there is no display for persons without coverage; due to Medicare, that number is statistically zero for both Grand County and the state as a whole for persons over age 65. Give the inferred prevalence of urban retirees, it is not surprising that so many Grand County residents over age 65 are covered by private insurance. Private insurance coverage also correlates with education. Better educated workers have better noncash benefits and would therefore prefer their private plan over the public options.

The sixth and final tab shows disability rates for older Utahns. Disability rates for Grand County resident are generally the same as for older Utahns statewide. It is somewhat puzzling to observe that the county rates for the age 75 and older cohorts are similar to the state’s. Given, the absence of substantial medical infrastructure, one who assume that disabled county residents would leave the area and therefore depress the disability rate.

Wednesday, October 19, 2016

Show Me the Economy

Mark Knold, Supervising Economist 

“The government knows everything about everyone.”

 Fortunately, that statement is not true. Yet society still looks to the government to provide answers to comprehensive and complex questions that have their foundation within individual decisions and activities. One subject frequently directed toward the government is individual-level information about the economy — particularly, what occupations are in demand, what occupations pay well and have lucrative outlooks, and ultimately, what occupation(s) should I build my career upon?

It takes the accumulation of a wide array of individual information to answer these questions. Employers provide the foundation information about the occupations they employ. Jobs are held by individuals, but employers provide the profile information about the job itself, not any particular individual.

Since society desires to profile such a broad spectrum of the economy — occupational profiles and the occupational distribution within the economy — only government is in the unique position to collect, analyze and provide answers for said desire. Yet, no government program or regulatory agency mandates any comprehensive occupational reporting from individuals or businesses. Therefore, government attempts to fill the void with an ongoing, robust and voluntary survey of employers — a survey where employers are asked to provide details about their various occupations; including descriptions, quantities, wages/salaries and location. Through this survey emerges an occupational portrait of an economy.

The U.S. Bureau of Labor Statistics (BLS) structures and funds the survey, yet the individual states conduct the survey. Under BLS administration, all states use the same methodology; therefore, occupational profiles are comparable across states.

Through this survey, analysts discover how industries are populated with various occupations. Accountant is an occupation, yet accountants can be found across many different industries. Other occupations may be more exclusive to certain industries; for example, doctors are largely found only in the healthcare industry. One of the survey’s products is that industries can be profiled with their general mix of occupations. This is called an industry’s occupational staffing pattern.

This brings us back to the original questions: what occupations are in demand, what occupations pay well and have lucrative outlooks, and ultimately, what occupation(s) should I build my career upon? The foundation is to make informed forecasts about how industries will expand/contract over the next 10 years. By applying existing occupational staffing patterns to each industry’s projected change, a trained economic analyst can then make an extrapolation about how occupations will correspondingly increase/decrease. Knowledgeable analyst judgment further refines the occupational expectations, such as knowing an occupation will grow faster than in the past, with the result being a set of occupational projections that accumulate to profile a state or regional economy.

A new set of occupational projections are done every two years to keep the information fresh even though economies do not change dramatically in short order. Because of slow change, updated occupational projects generally continue the overall message of preceding occupational projections. But economies do modify with time, and therefore, subtle changes will arise with each new set of occupational projections.

Utah’s most recent occupational projections are found here: These projections look forward to the year 2024.

The occupational profile is structured from the general to the detailed, mimicking the structure of a family tree. First, broad occupational categories are defined, such as management or healthcare occupations; then, subcategories are defined; and finally, individual occupations are defined. Individual occupations are the heart of the occupational projections. But overall patterns and characteristics do emerge when observing the broader categories.

While a Utah statewide profile leads the way, Utah’s local economies are not homogenous; therefore, nine Utah subregions are also profiled. Due to confidentiality restraints and statistical reliability, the amount of occupations available will diminish the smaller a subregion; but, occupations comprising the backbone of a regional economy will be available.

Eastern Region Highlights

Scott Smith, Regional Economist

The Eastern Region labor market is dominated by resource extraction industries. Roughly 15 percent of all 2014 jobs (the base year for the projections) are counted in the mining sector. A further 4 percent are involved in the short haul trucking industry — businesses that are almost exclusively hauling coal, oil and gas-related products. Alternately, a little more than half the jobs in the Eastern Region are located in the oil-rich Uintah Basin. Employment in Uintah and Duchesne counties is highly dependent on the price of oil and subject to the volatility of the commodity cycle. It is an understatement to note that the oil and gas industry is currently in a slump. In addition, Carbon and Emery counties both have a relatively large number of active coal mines, an industry facing its own challenges.

Given these headwinds, Eastern Region employment is projected to grow by only 0.8 percent annually through 2024. Total oil and gas employment is projected to grow at 0.1 percent annually. Coal mining employment is expected to decline by 1.3 percent annually. Construction, which is currently 6 percent of the total jobs, is naturally expected to follow this trend and is projected to increase by only 0.3 percent annually.

Table 1 shows the top six sectors in terms of new jobs. These 2,546 jobs comprise a little more than 60 percent of the projected Eastern Region total.

 With the exception of Junior Colleges and Restaurants and Eating Places, growth is expected to be sluggish.

Occupations related to the restaurant industry are expected to add the greatest number of net new jobs. Combined food preparation/serving workers and waiters/waitresses are expected to add more than 13 percent of net new jobs over the forecast horizon. The entry level salary for these jobs range from $16,888 to $17,010.
While cashiers are expected to add a substantial number of jobs annually, the total number of jobs is expected to shrink over the forecast horizon. The high number of annual openings is entirely a function of turnover. Entry level cashier jobs in the Eastern Region pay $17,220.

Heavy truck drivers are expected to add almost 5 percent of net new jobs. These jobs pay $39,400 to start and require some post-secondary education.

For occupations requiring at least a bachelor’s degree, the teaching occupations generate the largest number of net new positions. These jobs are projected to comprise 10 percent of all net new jobs. The vast number of these jobs are involved in primary or secondary education and start around the mid-$30,000.

Thursday, October 6, 2016

Veterans in San Juan County


The Department of Workforce Services has just published an interactive graphic on Utah veterans. Based on 2015 Census Bureau data, it allows researchers (and the simply curious) to “drill down” to veteran profiles at the county level. The department pays special attention to veterans for a number of reasons. Obviously, the nation is deeply obligated to veterans for their service. Veterans also make up almost 5 percent of Utah’s population and roughly half of veterans are of working age. Veterans have a higher disability proportion than the general public and sometimes have difficulty adapting their military skills to civilian uses. Given the potential for lost productivity, it also makes economic sense for society to concentrate on this population.

As an example of the information available and the potential for insights, this post will focus on San Juan County veterans. The veteran’s visualization profile has five profile segmentations, each represented by a “tab” above the graphs that one can click on.
The first tab is a broad overview of veterans statewide. The second tab details San Juan County veterans versus Utah veterans as a whole. San Juan County veterans in the 35-54 year-old age group (known as a cohort) are employed and participate in the labor force at a much lower rate than veterans in the state as a whole. While a larger part of this discrepancy can be explained by low participation rates in San Juan County as a whole, it is puzzling that County veterans participate less in the labor force than county nonveterans. This differs than the statewide profile; Utah veterans are more likely to be in the labor force than nonveterans.

The third tab shows median income for San Juan County by sex and veteran status. Two observations are especially noteworthy; the first is that the $101,390 estimate of female veteran strains credulity. Further examination of the data shows that the margin of era for the estimate is almost one third and the count of female veterans is very small. The data for male veterans is consistent (although at a lower income) with the experience of veterans statewide; veterans earn more their nonveteran counterparts.

The fourth tab shows veterans by era of service in detail.

Lastly, the fifth tab shows veterans by educational attainment and veteran’s status. The San Juan County profile shows that veterans have significantly more post-high school education than their nonveteran counterparts. However, San Juan County veterans have much less postsecondary educational attainment than Utah veterans statewide. This degree of the gap is somewhat surprising; usually an underrepresentation in the category holding bachelors degrees is (at least partially) compensated by an overrepresentation of the population holding associates degrees or advanced certificates. This is usually a result of the supply of jobs in a particular area. For example, Uintah count veterans have more associates degrees than veterans statewide because of the requirements of the oil and gas industry.

Tuesday, September 6, 2016

Age and Employment in Grand County

People work (and choose not to work) differently depending on where they live and how old they are. Obviously different people also prefer to live in different places. This can be because of employment opportunities, amenities, or even family ties. In like fashion, some industries attract a certain age demographic and are necessarily located in certain places.

The US Census Bureau tracks data like this and it allows economists to analyze the differences in age groups in different areas and industries.

The graph below shows employment by age in Utah and Grand County. The accommodation and food services sector was singled out due to Grand Country’s economic foundation; its economy is primarily tourist driven
It is obvious that the age make-up for the county and accommodation industry is different from Utah as a whole. The striking difference is in the 16-24 grouping (known as a cohort); the state has more workers in this cohort than the county but much less than the industry. It is likely that the difference between Utah and Grand County can be explained by the lack of four year universities in the area. In fact, it is quite typical for rural areas to be underrepresented in this cohort; young people tend to migrate to urban areas.

The 21 percent share for the accommodation sector in Grand County’s youngest age cohort is actually an under representation when compared to state-wide numbers; 37 percent of Utah’s accommodation sector workers are in the 16-24 years category. Other data from the U.S. Census Bureau’s American Community Survey suggests that the composition of this age group is markedly different from that of other rural counties. Roughly 7 percent of 18 through 24 year olds hold at least a bachelor’s degree. In contrast, the median level for the state (the measure that accounts for the rural nature of most counties) is only 3.6 percent. In fact, the level of educational attainment in this age group is on par with Utah’s “urban” counties that naturally attract educated young workers. A definitive explanation for this trend would require detailed survey work. However, the data suggests that Grand County benefits from the “river guide” effect. Young, educated workers come to the area for a post-bachelor degree association with mountain biking and white water rafting. Eventually, they migrate back to urban areas to start their professional lives.