Labor force participation rates varied substantially across Southern Arizona in 2019. Hereafter, when discussing multiple cities, towns, or census-designated places (CDP) the general term communities will be used. This article explores 41 of the largest communities within Cochise, Pima, Pinal, Greenlee, Graham, Santa Cruz, and Yuma counties. Due to the importance of mining in Greenlee County, we also include three nearby communities in New Mexico.
In 2019, the average labor force participation rate for those 16 years and older for the 41 communities tracked on the MAP was 52.5%. That was a decline from a twenty-year high of 54.7% in 2014.
The town of Florence posted the lowest labor force participation rate at 14.3% when compared to the other Southern Arizona communities. Of the 41 communities tracked on the MAP, only 10 followed an upward trend between 2000 and 2019. The Morenci CDP posted the largest increase in the labor force participation rate of 75.4%. The cities of Douglas, Eloy, and the Tanque Verde CDP exhibited a downward trend, with rate differentials of 23.6%, 16.9%, and 14.7%, respectively between 2000 and 2019 (Figure 1).
Figure 1: Labor Force Participation Rate for adults 16+ (2019)
The labor force participation rate, which includes both the employed and the unemployed who are actively seeking employment, is an important gauge of the health and potential output of the economy. As the economy expands, more individuals will be encouraged to enter the labor force. However, the demographics of a region can affect this measure significantly. For example, a population with a higher percentage of adults in their prime working years typically will have a higher labor force participation rate and the potential for higher economic growth. Holding these demographic factors constant, a higher labor force participation rate indicates that workers believe businesses are hiring for jobs that are worth their time and effort – valuable information in assessing the labor market in a region.
The labor force participation rates for those 16 years and older vary significantly by ethnicity across the Southern Arizona communities. The Morenci CDP had the highest labor force participation rates for both Hispanics and Whites, non-Hispanic, at 83.0% and 73.4%, respectively. Substantial variation exists for many of the Southern Arizona communities between Hispanics and Whites, non-Hispanic, including communities such as the town of Oro Valley and the city of Casa Grande, with a difference between both groups of 30.9 and 23.7 percentage points, respectively. The average difference between Hispanics and Whites, non-Hispanic for all of the Southern Arizona communities was 13.2 percentage points. This was greater than the U.S. difference of 5.3 percentage points. See Figure 2 for the labor force participation rate by race and ethnicity for the Southern Arizona communities.
Figure 2: Labor force Participation Rate by Race & Ethnicity (2019)
We will now explore the prime working age (25-54) for gender and the overall trend. The prime working-age makes up the majority of those in the labor force as many individuals under the age of 25 are still in school and those over 65+ may be retired.
The labor force participation rates exhibited significant variability by gender across the Southern Arizona communities as highlighted in Figure 3. For men ages 25-54, the city of Somerton had the highest labor force participation rate at 95.6%, outpacing both the state (at 84.9%) and the U.S. (87.4%). This trend holds for communities such as the town of Sahuarita (95.1%) and the Vail CDP (94.0%). For women ages, 25-54, the city of Safford, had the highest labor force participation rate at 82.2%, which outpaced the state (73.9%) and the U.S. (77.1%). The town of Clifton exhibited the highest male-female differential, with men surpassing women by 42.1 percentage points.
Figure 3: Labor force Participation Rate by Gender (25-54) (2019)
The U.S. economy experienced a long-term increase in the labor force participation rate, due largely to an increase in the percentage of women participating in the workforce during the second half of the 20th century. This trend continued from 2000 through 2019 as the national rate among prime working-age adults (25-54) rose from 79.6% to 82.2%. In 2019, the Corona de Tucson CDP posted the highest rate of labor force participation at 86.0% among adults in their prime working years (ages 25-54). That was 6.5 percentage points higher than the state’s rate of 79.5% and 3.8 percentage points higher than the U.S. rate of 82.2%.
The 2019 U.S. labor force participation rate for the prime working-age was outpaced by eight Southern Arizona communities (including the Corona de Tucson CDP): Casas Adobes (85.6%), Vail (84.0%), Catalina Foothills, and Drexel Heights CDP’S with a rate of 83.5%, Oro Valley (83.4%), and Sahuarita towns (82.7%) and the city of Casa Grande (82.4%). The city of San Luis posted the largest increase in the prime working-age labor force participation rate between 2000 and 2019 when compared to the 41 Southern Arizona communities, increasing from 47.0% in 2000 to 70.6% in 2019, a 23.6 percentage point rise. Communities with a high percentage of the population in the prime working-age (25-54) tend to have higher labor force participation rates. Figure 4 shows the labor force participation rate for the prime working-age for the Southern Arizona communities.
Figure 4: Labor Force Participation Rate for the Prime Working Age (25-54) (2019)
The labor force participation rate is calculated by dividing the total number of people in the labor force by the total population. The labor force includes both the employed and the unemployed who are actively seeking work. Data for 2009, 2014, and 2019 are from the American Community Survey (ACS) five-year estimates from the U.S. Census Bureau, while data for the year 2000 are from the U.S. Census 2000 SF3 sample. The ACS is a nationwide rolling sample survey that produces one-year and five-year estimates on demographic, social, housing, and economic measures. Note that the ACS five-year estimates are produced over a five-year time period and can only be compared to non-overlapping five-year estimates (for example 2005-2009 and 2010-2014).