Six southern US metro areas: part 6 – unemployment

My sixth blog post on mid-sized cities near the southern section of the Appalachian mountains looks at unemployment (people who do not have a job but are actively trying to find one).

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 36 months of aggregated Current Population Survey microdata, covering January 2016 to December 2018.

Unemployment rate

In a previous post, I calculated the unemployed share of the population. This post looks at the unemployment rate, which is the unemployed share of the labor force. Over the three-year period from 2016 to 2018, the US unemployment rate averaged 4.4%. The unemployment rate varied in the six areas of interest from 2.9% in Asheville to 5.1% in Huntsville. The unemployment rate in this three-year period averages 3.5% in Knoxville, 3.9% in the Greenville-Anderson-Spartanburg area, 4.0% in the Johnson City-Kingsport-Bristol area, and 4.6% in the Chattanooga-Cleveland-Dalton area.

BLS publishes high frequency estimates of unemployment in the Local Area Unemployment Statistics report. I’ve used the multi-year averages instead, to allow analysis of why people are unemployed and for how long they have been looking for a job.

Reason for unemployment

Unemployment can be grouped into four categories, based on what people were doing before they became unemployed: 1) people who quit a job and are looking for a new one (job leavers), 2) people who lost a job and are looking for a new one (job losers), 3) people who are looking for their first job (new entrants), and 4) people who were previously not in the labor force (for example: disabled or ill, taking care of family, retired, or had simply given up hope of finding work) and are now looking for work again.

From 2016-18, nearly half of US unemployment was because people had lost a job. This “job loser” category can be the most painful, as it is perhaps the least voluntary. The person had a job, and presumably wanted to keep it, but could not, and now they are trying to find a replacement job. In contrast, the re-entrant category, which makes up 1.3% of the US labor force, can be a positive indication. From 2001 to 2014, the US labor market was particularly poor for many people, and, as a result, many decided to stop looking for work. But over the past few years, the labor market has improved, and new jobs are pulling people off of the sidelines and encouraging them to look for work again. These people show up as “re-entrants”. Job leavers can also be an indication of a strong labor market. When people are confident that they can find a better job, they are more likely to leave their current job.

In four of the six areas of interest, the unemployment rate is below the US average for the “right” reasons. That is, people are less likely to be job losers or unemployed new entrants. In Knoxville and the Johnson City-Kingsport-Bristol area, more than half of the unemployed are job leavers and re-entrants. Re-entrants are also disproportionately common in the Greenville-Anderson-Spartanburg area.

The job loser share of the labor force is at or below the national average in all six areas, and particularly low in Knoxville and Asheville. The new entrant share of the labor force is above average in Huntsville and Chattanooga. Job leavers are more common in Chattanooga and Johnson City.

unempreason

Duration of Unemployment

Another important determinant of whether unemployment is particularly painful is the duration of unemployment. If people are unemployed for a short time, they may be able to rely on unemployment benefits and, in some cases, their personal savings, to survive. However, a long period of unemployment can devastate savings, exceed the period where unemployment benefits are allowed, affect mental health, and even create a situation where people begin to lose their skills.

Long-term unemployed, measured as those whose unemployment has lasted 27 weeks or more, makes up one percent of the US labor force. The long-term unemployment rate is the same in Johnson City-Kingsport-Bristol and Knoxville. In contrast, it is more common in Huntsville (1.8%) and less common in the Greenville area (0.7%), Chattanooga (0.5%), and Asheville (0.3%).

Short-term unemployment (lasting a month or less) makes up 1.4% of the US labor force, 1.5% in the Greenville area, 1.1% in Knoxville, and 1.3% in Huntsville. The unemployed populations in both Huntsville and Knoxville are more likely to be long-term unemployed than the US average.

unempduration

The next blog post in the series will look at which industries and occupations employ people in the six areas. The jupyter notebook used to create the analysis above is here.

Six southern US metro areas: part 3 – education and school enrollment

Part three in the series on mid-sized metro areas around the southern portion of the Appalachian mountains looks at education and school enrollment, for men and women, and how it compares to the US as a whole.

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 24 months of aggregated CPS microdata, covering January 2017 to December 2018.

Highest level of education attained

When defining education levels for adults, it customary to identify the highest level of education someone has attained based on five categories: 1) people without a high school degree, 2) those with a high school degree or GED but no college, 3) those with some college but no degree or a two-year degree, like an associate degree, 4) people with a bachelor’s degree, and 5) people with an advanced degree like a master’s degree, law or medical degree, or PhD.

I’ve used this grouping to calculate the educational distribution for men and women, age 25-54, in each area and in the US as a whole. Much like previous results in the series, there is an interesting divergence between areas. There is also an interesting divergence between men and women within areas.

education

Overall, people in the 25-54 age group in Huntsville are the most likely to have an advanced degree. However, the result is much stronger for men (20.3%) than for women (14.3%). Women in Huntsville are no more likely to have an advanced degree than women in the US as a whole. Other than Huntsville, none of the six areas has an above-US-average likelihood of having an advanced degree. It is also interesting to observe that Huntsville was the only area of the six where 25-54 year old women are less likely to have a high school degree than men. Huntsville’s share of age 25-54 men without a high school degree is nearly half the nationwide average.

The Asheville area has the largest gap between men and women in educational attainment. In Asheville, 42.1% of women age 25-54 have a bachelor’s degree or more, compared to only 26.7% of men. Men in Asheville, like those in Knoxville, Greenville, and especially Chattanooga, are less likely to have a high school degree than men in the US as a whole. However, in contrast to Asheville, in the Chattanooga-Cleveland-Dalton area, the share of men (28.8%) and women (28.5%) with a bachelor’s degree or more is almost identical.

The educational distribution for 25-54 year olds is fairly similar between the Johnson City-Kingsport-Bristol, Knoxville, and Greenville-Anderson-Spartanburg areas, with two exceptions. First, in the Johnson City-Kingsport-Bristol area, men are far more likely to have a high school degree compared to men in the other areas. Second, in Knoxville, like Huntsville, men are more likely than women to have an advanced degree.

School enrollment among young people

School enrollment among people age 18 to 24 in the six areas varies greatly between the six areas. In Huntsville, more than half (55.5%) of men in the age group are enrolled in school (college, university, or high school). Huntsville is the only one of the six areas where young men are more likely to be in school than young women, however, school enrollment is still higher for young women in the area than for young women nationwide.

School enrollment rates in the Chattanooga, Greenville, and Knoxville areas are similar to the US-wide average. Among 18-24 year olds in the Johnson City-Kingsport-Bristol area, both men (34.9%) and women (37.8%) are far less likely to be enrolled in school than those in the US as a whole. Among women age 18-24 in the six areas, those in Johnson City-Kingsport-Bristol were the least likely to be enrolled in school.

Men in Asheville stand out in the school enrollment data, with only 21.9% enrolled during ages 18-24, compared to 38.9% for women in the area.

school_enrollment

To look at school enrollment for a narrow age group (those 18-24), I used 4 years of aggregate CPS microdata (January 2015 to December 2018). However, there were only 138 valid observations for men age 18-24 in Asheville (by population the smallest area of the six). To check that the result from the four combined years of data is meaningful, I applied the same calculation to each of the four individual years of data. The results were pretty consistent in each year.

It’s worth noting that the school enrollment variable is derived from a household survey and asks whether anyone in the household was enrolled in school in the previous week. This is an important detail for several reasons. First, young people living in a dorm will only be included if their dorm room is part of the survey (not if their parent’s household is in the survey). Second, some of the areas in this survey have large colleges and universities where people from all over the world are locally enrolled in school and can therefore be part of the survey. Third, the data are from monthly files, so those who are in school for eight months of the year would answer “no” during any of the four months that they are not in school.

The jupyter notebook used in this analysis is here. The next blog post in the series will look at what share of people in each area are working, unemployed, or not in the labor force, compared to the nation as a whole.

Six southern US metro areas: part 2 – race, ethnicity, and country of origin

Today, I continue my look at six mid-sized cities around the southern portion of the Appalachian mountains. This post examines how the racial, ethnic, and national backgrounds of people in the area differ from the US as a whole. The results surprised me.

As a reminder (see yesterday’s post for more background), 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.

As in the previous post, the source for these results is 24 months of aggregated CPS microdata, covering January 2017 to December 2018.

Race and ethnicity

The first section compares the racial and ethnic makeup of each area to the national average. The racial and ethnic categories are defined in such as way as to not overlap and to cover the entire population: white only (non-Hispanic), black only (non-Hispanic), Asian only (non-Hispanic), Native American only (non-Hispanic), more than one race (non-Hispanic), and Hispanic (any race).

The black share of the population varies greatly by city, with Huntsville (19.7%) and Greenville (18.9%) well above the US average of 12.3%. The black share of the Chattanooga area is similar to that of the US as a whole. In contrast, the black share of the population in Asheville (9%), Knoxville (6%), and Johnson City-Kingsport-Bristol (2.5%) is far below the national average. People in these areas are much more likely to be white than in other parts of the US, and particularly, in other parts of the south.

black

The Hispanic share of the population is more consistent across the six areas but is far below the nationwide average. In the US as a whole, 18.3% of the population is of Hispanic origin. Only 5% of the population of the six areas is Hispanic, with the largest Hispanic share of the population in the Greenville area (6.5%). The Johnson City-Kingsport-Bristol area has the lowest Hispanic share of the population (3.1%).

Hispanic

The Asian share of the population in these six areas (2%) is also substantially below the nationwide average (6.1%), however, the Asian share of the population in the entire south region (3.9%), is also below the national average. The Asian share of the population in the Huntsville area (3.5%) is the highest among the six areas. Chattanooga (1.5%) and Asheville (1%) have the lowest Asian share of the population.

Asian

Changing concepts slightly, the share of children (under age 16) that are more than one race (and not of Hispanic origin) provides additional insight into each of these six areas. In this category the Greenville (5.9%) and Chattanooga (5.2%) areas are above the national average (4.2%). In contrast, the share of children with more than one race is particularly low in the Asheville area (0.8%).

More_than_one_race

Country of birth

Interestingly, the foreign born share of the population in these six areas (5.5%) is far below the national average (13.7%) and the average for the south region (12.7%). None of the six areas have even half the foreign born share of population in the US as a whole. Greenville has the largest share of its population born outside the US (6.5%), and Chattanooga (4%) has the lowest.

Foreign_born

Finally, I combined four years of microdata to get a sufficient sample for identifying individual countries of birth in each of the six areas. Even though people in the six areas are very likely to be born in the US, data suggests that there are significant communities of people born in certain countries in five of the six areas, relative to the overall US as a whole.

In Chattanooga, the Guatemalan born population is above the US-wide average. In Greenville, there is an above average Russian-born population. In Asheville, people are more likely to be born in Canada and the Philippines. Huntsville has a German- and Philippines-born population that exceeds the national average. Lastly, people in the Knoxville area are disproportionately likely to have be born in Sudan and Turkey.

The Jupyter notebook used for this analysis is here.

The next blog post will look at education levels and school enrollment.

Six southern US metro areas: part 1 – age and family structure

While it’s snowing here in DC, frigid in the northern US, and Florida is full of snowbirds,  there exists a theoretical climate happy medium in the southern Appalachian region of the US. This magical area gets four seasons, has mountains nearby for hiking and clearing out unproductive thought patterns, and yet doesn’t get super cold. But before I decide to move to this region, I should probably know more about it. Fortunately, the Current Population Survey (CPS) can help.

Background

What follows is the first in a series of blog posts about six mid-sized metro areas in the region that surrounds the southern portion of the Appalachian mountains. The six areas 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.

small_map

These mid-sized areas are likely influenced by three major cities nearby: Charlotte, Nashville, and Atlanta, however, I’m going to focus only on the mid-sized cities, which perhaps get less analytical attention.

The first post in the series will cover population, age composition, and family structure for people age 22 to 32. Specifically, I’ll look at whether people in the age 22-32 group are married and whether they have kids. Future blog posts will cover education, industry composition and occupation composition, labor market status (employed, unemployed, why not in the labor force), hours worked and wages, and finally, union membership and professional certification.

To get a sufficient sample size, data listed in the post today are drawn from 24 months of aggregated CPS microdata, covering 2017 and 2018. The wage discussion will likely use three or four years of data (since wage questions are asked to 1/4 of the CPS sample).

Population

CPS-based-estimates of population for the six areas are as follows:

  • Chattanooga-Cleveland-Dalton, TN-GA: 802,000
  • Greenville-Anderson-Spartanburg, SC: 1,270,000
  • Asheville, NC: 463,000
  • Johnson City-Kingsport-Bristol, TN-VA: 505,000
  • Huntsville, AL: 478,000
  • Knoxville, TN: 853,000

Age composition of population

My first question is what share of people living in these areas are children (under 16) and what share are retirement age (over 64).

The age 15 or less share of the population in the six areas is at or below the US average. The Greenville area has the highest share of children (20.7% of the population) and is the only area with an above-average share of children. The Asheville area has the lowest (15.1%).

under_16_share

The age 65 or older share of the population varies between the six areas, with four of the six areas having an above average retirement-age share. The highest age 65 or older share of the population is in Asheville (22.1%) and the lowest is in Huntsville (11.3%).

over_64_share

Marriage rates among those age 22-32

Next, I’m curious about family structure among those age 22-32. Student debt and expensive housing, among other things, have the result of reducing marriage rates for young people. I’m curious how young people’s marriage rates compare between these six areas and the nation as a whole.

Five of the six areas (Asheville is the exception again) have above national average rates of marriage for those age 22-32. The highest age 22-32 marriage rate is in the Johnson City-Kingsport-Bristol area, where 40.8% of the age group is married. In Asheville, 31% of the age group is married, just under the 32% nationwide rate. Marriage rates are also well-above average in Knoxville (39.7%) and in the Chattanooga area (39.4%).

My suspicion here is that student debt levels and housing prices are below national averages for much of this region, which makes starting a new household easier.

married_share

Share of 22-32 year olds with kids

Finally, I want to look at how many 22-32 year olds have kids in each of the areas, compared to the US as a whole.

The share of 22-32 year olds with kids varies among the six areas. Like marriage rates, the Johnson City-Kingsport-Bristol has the highest share of 22-32 year olds with at least one kid, at 41.9%, compared to 29.3% nationwide. Knoxville (34.7%) and the Chattanooga area (34.1%) also have above average parenthood rates. Huntsville (22.9%) and Asheville (24.7%) have a low rate of parenthood among 22-32 year olds.

one_or_more_kids

The share of 22-32 year olds with two or more kids is above the national average for five of the six areas. Chattanooga (20.1%), Johnson City-Kingsport-Bristol (20%) and the Greenville area (19.3%) are well above the national average of 16.2%. Interestingly, Huntsville is far below the national average, with 8.7% of the age group with two or more kids. The Huntsville area has a large military population, but, importantly, people in the Armed Forces are already excluded from this dataset, so that can’t be the explanation.

two_or_more_kids

The next blog post in the series will look at education and industries and occupations.

The jupyter notebook used in this analysis is available here.