Our overly-rosy unemployment statistics (and its math) ignore millions.

To understand why the MMT-designed job guarantee is so critical, we must first see the absolute devastation wrought by involuntary unemployment and underemployment. Before that, however, we must also understand that there is involuntary unemployment (and underemployment) to begin with.

This post contains a brief summary of how official unemployment statistics ignores millions of the most disadvantaged in society. That overly-rosy picture is used as an excuse by those in power to proclaim there is no problem and therefore nothing to solve.

At the end you will find a brief discussion about the math of unemployment statistics.

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This post was last updated September 12, 2020.

Disclaimer: I have studied MMT since February of 2018. I’m not an economist or academic and I don’t speak for the MMT project. The information in this post is my best understanding but I don’t assert it to be perfectly accurate. In order to ensure accuracy, you should rely on the expert sources linked throughout. If you have feedback to improve this post, please get in touch.

Unemployment statistics versus reality

Despite the overly-rosy (Wray 2017) reports by the United States Bureau of Labor and Statistics (BLS), millions remain involuntarily unemployed and underemployed. Even if unemployment statistics were captured perfectly, it would still necessarily ignore millions (Forstater 2012).

The reports put out by the BLS give no indication of the many millions who are not reached by their survey. This includes everyone without a home or phone (because surveys are conducted by phone!), as well as members of the military and the currently incarcerated – in other words, the destitute and desperate.

Most unfortunately, because the central government does not provide what is needed to prevent mass suffering (despite clearly being able to do so), the military has become our nation’s de facto employer of last resort. Also, de facto slavery has been perpetuated by, among many other things, the Thirteenth Amendment and the for-profit prison system, the War on Drugs, and the myth of taxpayer money.

No one chooses to be homeless or phoneless. No one chooses to be put in jail. And too many enter the military not out of a sense of patriotism but instead out of desperation. In other words, the most desperate members of society are forced into these terrible situations because of the active policy decisions and deliberate neglect of a government that could clearly prevent most of it. Therefore, those ignored by unemployment statistics are not just “coincidentally and unfortunately left behind,” they are actively pushed out of existence.


Finally, here is a realistic assessment of unemployment in the US, by Bill Mitchell in this August, 2020 post: US labour market improvement continues but there is still a long way to go. (Here are all related posts marked “labour market” on Bill’s blog.)

Link to tweet

A word about the math of unemployment statistics

Let’s pretend there are ten people in the country and all are employed. Happily, of course. That’s ten people employed and ten people in the labor force:

10/10 = 1 = 100%

In this scenario we are at 100% employment and 0% unemployment. Full employment.

Say one person becomes unemployed. Now we have nine employed, and ten in the labor force:

9/10 = .9 = 90%

Now, instead of that person just losing their job, let’s say they become homeless or phoneless, decide to join the military, or end up in jail. This means that they are no longer part of the labor force. So instead of 90%, it becomes

9/9 = 1 = 100%

Because that person is no longer in the labor force, we are once again at officially full employment!

So, for every unemployed person that leaves the labor force, official unemployment becomes rosier and rosier. It does this by ignoring more and more, creating a perverse incentive for those who don’t want the system to change, to disappear those farthest away from the levers of power.

Related post: Using numbers to hide real-world, mass suffering (and immorality).