I started my first blog post by saying that this country is heading in the wrong direction in many ways. It is obvious that the trend in obesity is one of those problems that will have a major impact on this country for some time.
Rising unemployment for a sector of the population is one of those, and when you hear about unemployment numbers going down, please keep this chart in mind and remember this table:
The table above and excerpt below are from a recent study published in US News magazine, titled “Why the Middle Aged Are Missing Out On New Jobs”:
A major midlife job crisis. The overall job market is clearly healing, but middle-aged workers aren’t part of the revival. Workers between the ages of 45 and 54 are still losing jobs on net, with a decline of about 364,000 jobs in this age group so far this year. That seems remarkable–and worrisome–given these are people in their prime earning years, and they also ought to be at peak levels of expertise in their fields or careers. Yet they’re not yet participating in the jobs recovery, perhaps because their pay requirements are too high in an economy where employers still aren’t willing to bring back the most expensive workers. Many are most likely middle managers whose ranks were severely thinned during the recession, or construction and manufacturing workers who still can’t find work, and may never be able to in their current fields.
The official government statistics are a little bit misleading, because they don’t mention “underemployment“. Basically, the term ‘underemployment’ means people working at jobs below their skill level, or working part-time. Like a laid-off auto worker reduced to half-shifts or taking a job at a grocery store just to make ends meet. That worker is considered a worker in full capacity in government statistics, and I suspect that a significant number of those jobs created in the last 15 months fall into this category. Underemployment is hard to quantify, and I haven’t yet found a “plain-vanilla” database to get usable numbers (I did find some other extremely interesting data employment data, however, and I’ll write about it in the future). But it’s easy to see that if the unemployment and underemployment figures were combined, a worrying picture would begin to take shape.
The chart below is extremely interesting: it shows the evolution of Long Term Unemployment (people who have been out of work for more than six months). I tried to cram a lot of info in a single chart, and if you click ‘play’, you can see the Long Term Unemployment rates for both men and women over the last 10 years. While the little bubbles remain blue, things are in the ‘normal’ range.
Long-Term Unemployment in the US
It is alarming to see the exponential growth of Long Term Unemployment, beginning precisely after the collapse of Lehman Brothers and the beginning of the credit crunch. The bubbles growing and becoming red in such a short period of time are the equivalent of somebody who had a heart attack in 2008 due to an unhealthy lifestyle, had some short-term fix, and then continued with the unhealthy lifestyle. I compiled statistics all the way back to 1948, and the long-term unemployment levels we are currently experiencing are alarming.
The indicators that pressure is building and that a “dissipation” mechanism is needed are already in place. There is additional data related to this topic, but it’s too much for this post. Nevertheless, you already know 2 valuable things about Long Term Unemployment: Being 35 to 55 is a whammy, being a male in this range is a double whammy. Triple and quadruple whammys come from your educational level, ethnic origin, state where you live, and other factors.
Do you know someone who’s underemployed? Maybe your husband? Your wife? Yourself? A friend? I know a lot of them in my field. As I mentioned in my previous post, I am a senior ‘low-volatility’ Quant (minus the fat), enjoying my old and new hobbies, visiting family when I have time, coding in Python, back-testing trading ideas, reading, and writing a book. I started using Python more and more.It is a joy to code in Python. It allows you to create pretty advanced stuff, with thousands of super cool libraries such as numpy, etc. that are pretty sophisticated even compared to the expensive software I used in the early 90s to spot arbitrage trades for a hedge fund. Python and its entire analytical arsenal has that power. It allows you to code and analyze data easily, and nobody can beat the price of open source systems.