There are two questions to ask whenever you see a statistic.
First, what exactly is being measured? The statisticians crunching numbers know what they are measuring, but the people repeating the numbers know what they want to promote. And promote they do! There seems to be a lot of temptation to misrepresent data promoting political and social agendas.
For example, we are repeatedly told that the unemployment rate is less than five percent. Politicians and pundits are beating us over the head with this number and arguing over which President should get the credit.
The only thing is, it doesn’t “feel” like full employment. I do not know anyone taking a loan for a new car, buying a bigger house or signing a lease on a new apartment. According to polling company Rasmussen 46% of us know someone out of work. Although that is less than it has been in the past, it does not support the idea of full employment. What can we do to find the truth?
This is where the first question comes in…
What exactly is Being Measured?
In other words, what does it mean to be employed?
According to the Bureau of Labor Statistics (BLS), people are employed if they work at least 15 hours a week. But they don’t have to make a living wage, or even be paid.
For example, a stay at home mom might help her entrepreneur husband keep the books on weekends, but she is not paid for it. However, because she benefits from her work, she is considered employed.
Likewise, contingent workers cobble together a living from as many gigs as they can find and make up about 40% of what the BLS considers employed, but they do not generally make a living wage.
We tend to think that being employed equals making a living wage, but that isn’t true anymore. A better measure of economic health of the average American might be the midpoint of all annual W-2 income. That number has hovered around $30,000 for years.
How are they collecting their numbers?
The way numbers are collected means a great deal.
For decades, the education industry insisted that the more degrees one has the more money one makes. But wait a minute! I work at a community college where all instructors are required to have at least a master’s degree, but more than half are part timers because they cannot find a full time job. This is a well-known crisis across the country that has been getting a lot of attention. Also, the Department of Education (DOE) follows bachelor’s degree graduates for years and tells us that about 30% are unemployed or completely out of the labor force four years after graduation.
That does not sound like more education necessarily means a better job or more income.
How can this be?
Just a little sleazy data collection…
The education industry surveyed companies in which people with advanced degree worked. Sure enough the longer these people when to school the more money they made. But these people were already working. The graduates who could not find jobs are uncounted. The education industry does not want to know how many had to take low paying jobs because they could not find jobs for which they studied.
Think about it. Do you know anyone with an advanced degree working in a job that does not require it? The roofer who fixed a leak in my roof had a master’s in public administration and the tech who hooked up my high-speed internet had two masters’ degrees. The education industry will never detect those people because they looked only at jobs requiring an advanced degree.
The DOE can tell us because it follows students for four years after graduation. That is a longitudinal study and it is the most accurate method of detecting cause and effect.
What do they find?
in 2012, four years after graduation, 15% of bachelor degree holders are unemployed, about half suffering long-term unemployment and the other half short-term unemployment. The other 15% have left the labor force, either going back to school or finding other ways to get by without a job.
You probably have never a funny book about statistics. Here are two — Drunkards Walk and Naked Statistics. I promise they will make you laugh out loud at the same time that they explain how statistics are manipulated and misinterpreted.