Following on from Part II where I looked at the population of people who had left the labor force completely, this week I turn my attention to the unemployed. The unemployed are defined as those who are currently not employed but have made “specific efforts to find employment some time during the previous 4 week-period ending with the reference week”. Chart 1 maps the unemployment rate since 1948.
Cause of Unemployment
The first breakdown (shown in Chart 2) is the unemployed population (as a percentage of the total civilian labor force) broken down according to the cause of unemployment:
- Lost a job
- Left a job
- Rejoining the labor force after some hiatus
- Joining the labor force for the first time
Chart 2 – Unemployed Persons by Cause 1967 to 2015
From this breakdown, the first conclusion we can draw is that people losing their jobs drives almost all the variation in the total unemployment rate over time. This stands in stark contrast to the population of job leavers and new entrants to the labor force, both of which have remained remarkably consistent over a long period of time.
The second thing to note is that the changes for those reentering the labor force appear to track the changes for job losers, but with smaller peaks and troughs. This suggests that when there is a spike in people losing their jobs (due to a recession for example), a population of people who had left the labor force is returning to look for jobs. Although counterintuitive (why would you rejoin the labor force in the middle of a downturn?), this likely reflects cases such as a family where the primary breadwinner loses their job, and both parents begin the hunt for jobs to make ends meet.
This is interesting primarily because it shows a feedback loop that potentially increases the spike in unemployment in a downturn. That is, just as large numbers of people are getting laid off from their jobs, an additional population of people who weren’t in the labor force also begins looking for jobs, further boosting the population of unemployed. Conversely, this also means that unemployment can fall much quicker than anticipated (for example when one parent becomes employed and the other drops out of the labor force again).
Education Level of the Unemployed
Chart 3 shows the unemployed population broken down by education level and the obvious conclusion to draw is that your teachers were right; finishing school will help you get (and keep) a job. The rates of unemployment for those people that didn’t finish high school are significantly higher than for everyone else, keeping in mind this is for people actively looking for work (as opposed to cruising on their parents couch or living off a wealthy spouse). Conversely, the unemployment rate for those that completed a bachelor’s degree or higher is by far the lowest of the four groups.
Chart 3 – Unemployed Persons by Education Level 1992 to 2015
The other observation to be made is that there is not a huge difference in the unemployment rates for those that finished high school but didn’t go on to further studies, and those that went on to get an associates degree or attend, but not finish, college (university for those not in the US). Contrast this with the large gap between the ‘Some College/Associates Degree’ group and the ‘Bachelor’s or Higher’ group, and the advantage of graduating from college (at least in regards to getting employed) becomes plain to see.
Length of Unemployment
One of the more interesting and discussed breakdowns of the BLS unemployment data is the breakdown by length of time unemployed. Chart 3 shows how these percentages have changed over time for three groups:
Chart 4 – Unemployed Persons by Length of Unemployment 1948 to 2015
The main feature that immediately stands out on this chart is the huge spike in the percentage of people unemployed for more than 15 weeks in 2009. This peak is well well above anything since the end of World War II and remains high today. This indicates that in addition to unemployment spiking in the global financial crisis (as we saw in Chart 1), people tended to stay out of work for significantly longer than in any other downturn since the end of World War II.
What this chart also shows us is how far the US economy is from what would be considered ‘historically normal’. For most of the past 60 years, the majority of unemployed people were unemployed for less than 5 weeks, followed by those unemployed for 5-14 weeks, and then finally the smallest group was those unemployed for 15 weeks or more. However, with the financial crisis we saw this split reverse and, unlike previous downturns, over 6 years after the financial crisis the population of people unemployed for 15+ weeks is still significantly higher than the population of people unemployed for less than 5 weeks.
Further confirming this shift, an additional series that the BLS produces is the average weeks unemployed (see Chart 5). From this chart we see that the latest downturn caused a huge spike in the average weeks unemployed, but also that the average period of unemployment remains at a level higher than at any other point pre-crisis.
Chart 5 – Average Period of Unemployment 1948 to 2015
The other interesting point from Chart 5 is that even before the spike in 2009, if we look past the ups and downs of the recessions and recoveries, there appears to a trend of slowly increasing average time unemployed in the preceding 60 years. What would cause this average to creep up over time? It is likely to be a combination of a number of factors. Below are some factors that have occurred over time that could help explain this trend:
- Professionalization of recruiting – recruiting is increasingly a function that is handled by a professional team within an organization, or is outsourced to a professional firm, even for smaller companies. This practice generally ensures a certain minimum standard of hire, but also means it is increasingly rare that a firm will take a chance on someone with a long period of unemployment or a spotty employment history.
- Increasingly technical nature of jobs – with many professional jobs, even outside of the tech world, there is increasing pressure to continually develop new skills and adapt to new software and best practices just to keep up with the requirements of the job. As difficult as this can be for someone in the job, it is essentially impossible for someone who is unemployed leaving that person heavily disadvantaged in the job market.
- Improved ability to validate work history – previously, if a person had been unemployed for an extended period, they could fudge the dates (or flat out lie) with little chance of being found out. In 2015, with online networks such as LinkedIn and generally more thorough background check processes in place, it is much more difficult to get away with this type of deception (although it definitely ).
Many of these changes would appear to be positive changes, such as increasing professionalism in the recruitment process and less room to mislead potential employers, so surely we are just reducing the number of dishonest people and under qualified children of bosses/friends getting jobs? That is probably true to some extent. But what is also true is that those underdog stories that we love to hear about and watch, like becoming hugely successful after years of staying home to raise the kids, or scamming his way into a prestigious law firm, are becoming close to impossible in reality. For better or worse, the job market is becoming a place for the of the world, not the .
People in Part Time Work
Finally, although officially classified as employed, the BLS also tracks the number of people who want full time work but that are currently only working part time (also referred to as ‘under employed’). The change in this population is shown in Chart 6.
Chart 6 – Persons at Work Part Time for Economic Reasons 1956 to 2015
One of the criticisms of the recovery post-2009 has been that it is a “part-time recovery” (see and for example). In other words, the belief is that the jobs being created are mostly part-time jobs and so the unemployment rate is not accurately reflecting the poor state of the economy. However, we can see that although the peak in 2009 was high (but not the highest, the peak in this series was actually 6.2% in October 1982), it has since fallen back to around average for the period and continues to fall in both absolute and percentage terms.
Watch this space for the final part of this series, Part IV, where we will explore the employed population.