County level labor force participation


By Marilyn Cannon, Regional Economist

The United States Bureau of Labor Statistics (BLS) provides unemployment statistics for the nation. BLS does the data capturing, calculations, and publication. It distributes both statewide and county-level labor force, employment, and unemployment statistics. One variable that BLS does not provide at the county level is the labor force participation rate (LFPR). This article addresses how county-level participation rates are calculated.

The LFPR measures the percentage of an area’s working age population that is active in the workforce. In order to determine the working age — 16 and older — population, BLS calculates the number of people in an area who make up the noninstitutional population, which excludes active military and people confined to institutions like prisons, mental facilities, and homes for the aged. Next, BLS obtains the area’s civilian labor force number, which is estimated by the U.S. Census Bureau. This metric includes all people age 16 and older who are either working or looking for work. Then, BLS calculates the LFPR for an area by dividing the civilian labor force by the total age 16-and-older-noninstitutional population.  Using this formula, LFPRs for the United States and Utah in June 2024 were 62.5% and 68.6%, respectively: 



United States


Utah


Civilian Labor Force


168,009,000

= 62.6%

1,799,224

= 68.6%

16+ Population

268,438,000

2,621,588




How are county LFPRs calculated?   
The U.S. Census Bureau measures county population through its American Community Survey (ACS). ACS data is available for larger counties as a one-year measurement, and it is available for all counties, regardless of population, as a five-year average measurement, with the most recent available data from 2018-2022. BLS provides 2022 civilian labor force counts for each county. Following the LFPR formula explained previously, calculation of county-level LFPRs can be obtained by dividing a county’s BLS 2022 civilian labor force by its ACS 16-and-older population estimate.

Although the ACS does publish county-level LFPRs, those are subject to historical economic impacts when the five-year average ACS data is used in their calculation. For instance, the ACS LFPRs might contain economic effects that do not impact current estimates. The ACS five-year average (2018-2022) includes data from the COVID-19 economic disruption. Since the current economic environment has moved past the distortions from the pandemic, the ACS LFPRs are disproportionately influenced by the effects of the pandemic. In order to overcome these distortions, the usage of ongoing county-level BLS labor force estimates and ACS county population estimates aid in lessening the past impact of the pandemic while focusing on current workforce trends. 

For the least populated counties in Utah, Daggett and Piute, LFPRs cannot be shared because of their small ACS sample size. BLS suppresses data in areas with small sample sizes to maintain confidentiality of employers, protect sensitive information from being identifiable, and to ensure that published data is accurate. For the remainder of Utah’s counties, LFPRs can be shared.



Overall, Utah has a high LFPR compared to other states, but that rate can vary by county as illustrated in the map below. Differing demographic and economic dynamics in each county impact how much of each county’s population participates in the labor force.



For example, Washington County has a lower percentage of people in the labor force (61%) than most counties. This is because the county is traditionally a popular location for retirees, who have removed themselves from the labor force. On the other end of the spectrum, Utah County has a relatively high LFPR of 72.7%. This is partly due to the county having the youngest average population in the state and younger age groups having a greater tendency toward working.



Urban counties tend toward higher LFPRs than rural counties. There are several forces at play that can explain this trend. One explanation is that Utah’s urban counties have the lowest percentage of 55-and-older persons in Utah. This factor is augmented by labor force active young people living in Utah’s rural counties who subsequently move to the urban areas. They come for employment opportunities, which are both more numerous and more diverse in urban areas than in rural counties. This results in feeding the urban county LFPRs.



Urban periphery counties feed off of their proximity to urban counties, which results in a tendency toward higher LFPRs. These counties, including Summit, Tooele, Wasatch, and Morgan counties, benefit from easier access to the number and diversity of jobs in urban areas. There also tends to be a wider variety of jobs available in the urban periphery counties than in more rural counties. In turn, employment growth and job opportunities spill over from urban counties into the neighboring counties.

Rural counties generally can’t overtake urban job opportunities due to limited size and diversity of industries. Rural county economies make their economies work around natural endowments. However, these endowments can be specific and limited in scope. A well-rounded industrial base is oftentimes absent from rural counties. This speaks to why some of the rural area’s young population migrates to Utah’s urban corridor for a broader employment picture, as the jobs they are interested in may not be readily available in a rural setting.

Summary
Labor force participation rates speak to the work engagement of a population. Different economies produce different LFPRs. Profiling LFPRs reveals demographic knowledge, which helps in understanding local economic trends. County-level LFPRs are not available by the U.S. Bureau of Labor Statistics in its ongoing economic evaluations. However, these rates can be produced with the use of current BLS civilian labor force county data and U.S. Census five-year 16-and-older population estimates. The strength of using this data is the ability to capture current conditions and account for ongoing changes.