Six southern US metro areas: part 4 – labor force status

Part four in the series looks at whether people are working, looking for working, or doing something else, in each of six mid-sized metro areas around the southern portion of the Appalachian mountains. Since economic cycles influence whether people want jobs and whether they can find them, this post also looks at how the labor force status has changed for men as the overall US economy improved from 2015 to 2018.

The six areas of interest are: the Chattanooga-Cleveland-Dalton, TN-GA combined statistical area, the Greenville-Anderson-Spartanburg, SC combined statistical area, the Asheville, NC center-based statistical area, the Johnson City-Kingsport-Bristol, TN-VA combined statistical area, the Huntsville, AL center-based statistical area, and the Knoxville, TN center-based statistical area. See the first post in the series for more background.

The source for these results is 12 months of aggregated CPS microdata, covering January to December 2018. The rate of change data compares the 2018 results with those from January to December 2015.

Employed, unemployed, or “not in the labor force”

This section compares the six areas in terms of whether men and women age 16 to 64 are employed, unemployed (meaning they don’t have a job and are actively trying to find one), or are “not in the labor force.” Not in the labor force, which I will generally refer to as “non-participation,” can be for any reason, such as discouragement (want a job but have given up hope of finding one), disability or illness, school, taking care of family, retirement, or for other, unspecified, reasons.

In 2018, the share of each area’s age 16-64 population that is employed, unemployed, and not in the labor force is similar to the US as a whole. Overall, in the US, 2.6% of women and 3.2% of men are unemployed (this is not the unemployment rate, but rather the unemployed share of the population). Among the six metro areas of interest, the unemployed share of women ranges from 0.8% in Knoxville to 4.3% in the Chattanooga area. The unemployed share of men ranges from 1.2% in the Johnson City-Kingsport-Bristol area to 3.3% in the Greenville area.

lfs

In the US as a whole, 76.1% of 16 to 64 year-old men are employed, compared to 65.5% of women. The main reason for the gap is that women are more likely to be doing unpaid work at home, like taking care of children or elderly relatives. The employed share of men in the six areas ranges from 73.8% in Asheville to 78.1% in the Greenville area and Huntsville. The employed share of women ranges from 59.8% in Huntsville to 68.1% in Knoxville. Huntsville has the largest gap between men’s and women’s employment.

Finally, for those age 16-64 in the US as a whole, 31.8% of women and 20.8% of men are not in the labor force. Again, the patterns are similar in all of the six areas. The non-participating share of women ranges from 29.9% in Asheville to 36.9% in Huntsville. Among men, the non-participating share ranges from 18.6% in the Greenville area to 23.8% in the Johnson City-Kingsport-Bristol area.

Change in labor force status

While the labor force status in each of the six areas of interest doesn’t differ too much in 2018 from the US as a whole, there have been some pretty big changes within some of the areas since 2015, which are discussed in this section.

From 2015 to 2018 there was general improvement in the overall US economy, but seemingly even more substantial improvement in the local economies of most the six areas. This is evidenced by the change in the share of the each area’s population that was employed in 2018 compared to 2015. For the US as a whole, the age 16-64 employment share increased by 2.1 percentage points for women and 1.9 percentage points for men. In contrast, only women in the Greenville area (0.5pp) and men in Asheville (1.6pp) had an employment share increase that was smaller than the US average.

lfs_change

 

Among the six areas of interest, the largest change in employment share was for women in Knoxville. The employed share of this group increased by 7.3 percentage points, to 68.1% in 2018 from 60.8% in 2015. This is a massive increase in a relatively short period of time. Among men, the largest increase was 6.1 percentage points in the Greenville area, where the employed share of 16-64 year olds increased to 78.1% in 2018 from 72% in 2015.

In addition to men in Greenville and women in Knoxville, other groups with at least a four percentage point increase in the employed share of the population include women in Huntsville (4.8pp), men (5.5pp) and women (4.1pp) in Johnson City-Kingsport-Bristol, and men in Knoxville (4.3pp).

Perhaps most interestingly, and as pointed out recently by economists Matthew Boesler and Elise Gould, much of the recent change in employment seems to be coming from people who were previously not looking for work. That is, while unemployment has clearly fallen, so has non-participation. This is a very important development because unemployment is already low by historical standards, but non-participation is still high by historical standards.

In the US as a whole, non-participation explains 0.8 percentage points of the 1.9 percentage point increase in employment among men, and 1.3 percentage points of the 2.1 percentage point increase in employment among women. In contrast, it over-explains employment growth among women in the Chattanooga-Cleveland-Dalton area, who have higher rates of unemployment in addition to higher rates of employment.

Notably, non-participation in Knoxville fell by 5 percentage points for women and by 3.7 percentage points for men, over the four year period. In the Greenville area, non-participation fell by 4.9 percentage points for men but actually increased by 1.1 percentage points for women. Non-participation also increased slightly among women in Asheville. Non-participation fell by 3.4 percentage points for women in Johnson City-Kingsport-Bristol.

The next post in the series will look specifically at reasons for non-participation. The jupyter notebook used in this analysis is here.

EDIT: The original version of this post used person weights, instead of the composite weights. The text and graphics above are updated to use composite weights.

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