I saw the headline The unemployment rate doubled under Bush. It’s fallen by more than one-third under Obama. when I was reading Vox this morning, and I got ready to bust out the stat that “the labor-force participation rate is still way down” — as indeed it is:
That is, the fraction of Americans working hit its peak under Clinton, fell under Bush, really fell when the housing bubble popped, and hasn’t really recovered.
Some of that drop can come from young people deciding to stay in school and get graduate degrees when the economy is doing poorly, or from older people deciding to retire early. So what if you focus on ages 25 to 54, i.e., the “prime-age labor-force participation rate”? The story there is somewhat better:
The rate still took a noticeable hit in 2008, but we’ve regained some ground. Let’s zoom in on the period starting in 2005:
Moving slowly in the right direction. Now, much of the gain since 1948 can be attributed, one assumes, to women entering the workforce. Do the data bear that out? Seemingly yes:
That’s interesting: women’s labor-force participation seems to have flat-lined starting in 1990. Why? And what can be done to get it moving again?
On the flip side, how about the male labor-force participation rate? That’s quite striking:
It has decreased more or less continuously since 1960.
There’s no real moral here. I just find it interesting that, as you dig into the data, there’s something more going on than a story about the 2009 recession. Seems like, recession or not, men are leaving the workforce. And women aren’t entering it fast enough to offset that drop.
P.S.: A friend asks whether labor-force participation is really an end in itself. The short answer is probably “No, though it’s a good proxy for what we actually care about.”
Perhaps, for instance, people choose to stop working because they want to be full-time parents. Let’s call that a “happy” labor-force detachment. On the other hand, perhaps they drop out of the labor force because they know they’ll never get a job. Or maybe (I’ve seen this happen a lot) they’re mothers who want to spend time with their kids, but the only jobs that they could get would hardly cover the cost of child care; they want to work, but for economic reasons they choose not to. Call that a “sad” labor-force detachment: they’d like to work, but can’t.
It’s going to be hard to measure this in full detail, of course, and there are going to be almost as many boundary cases as there are people who aren’t working. But if you want to measure “how is the economy doing?” you have to set your boundaries somewhere. That’s why the Bureau of Labor Statistics has a number of different measures of unemployment:
U-1, persons unemployed 15 weeks or longer, as a percent of the civilian labor force;
U-2, job losers and persons who completed temporary jobs, as a percent of the civilian labor force;
U-3, total unemployed, as a percent of the civilian labor force (this is the definition used for the official unemployment rate);
U-4, total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers;
U-5, total unemployed, plus discouraged workers, plus all other marginally attached workers, as a percent of the civilian labor force plus all marginally attached workers; and
U-6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all marginally attached workers.
U-6, for instance, has improved noticeably over the last few years.
There are a lot of terms in here with precise definitions, and the definitions matter, and you need to think carefully about what you’re counting and aren’t. For instance, what does “civilian labor force” mean? Who’s in it and who’s not? This isn’t secret or mysterious at all; the BLS explains it in clear language. Here you go:
Civilian noninstitutional population: Persons 16 years of age and older residing in the 50 states and the District of Columbia, who are not inmates of institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces.
Civilian labor force: All persons in the civilian noninstitutional population classified as either employed or unemployed.
Note well: this means that if you’re in prison, you’re not part of the labor force. This is where unemployment definitions intersect with Becky Pettit’s Invisible Men: Mass Incarceration and the Myth of Black Progress. To put it briefly: if every single black man but one were in prison, and that remaining black man had a job, then by the official statistics the unemployment rate among black males would be zero. Obviously we would consider this situation horrifying. So “a low rate of unemployment” is not necessarily synonymous with “a happy economy”. Maybe we want to add the institutionalized population to the current definition of the labor force. Or maybe not: those in prison surely cannot work and are not looking for work. And if we’re going to add those who can’t work for reasons of imprisonment, why then wouldn’t we add back lots of other people who cannot work and aren’t looking for work because, e.g., they’re permanently disabled? It’s certainly useful to measure all such populations. Different data series have different uses. Probably the best you can say is that different questions require different sorts of data, that no one data series can answer all questions, that you really need to look carefully at multiple sources of data, and that you should carefully look at the assumptions embedded in each.
What if you count the total civilian labor force (which, again, includes the noninstitutionalized population) and divide it by the overall population? You get this:
Earlier, we were tallying the “labor force participation rate”, which is defined as “The labor force as a percent of the civilian noninstitutional population.” As more people are imprisoned (“institutionalized”) or enter the military (i.e., they’re no longer “civilian”), the denominator goes down, which means the participation rate goes up. Whereas if you divide by the total population, an increasing prison population would cause the participation rate to decrease — arguably closer to what we actually want.
Again, this graph is likely dominated by women’s entry into the workforce. FRED seems to track the right thing here, namely the employment-to-population ratio over time for males. In the numerator, that’s going to include men who choose to stay in school longer, and men who choose to retire early, so one wants the employment-to-population ratio among prime-age males. In the denominator, it’s going to include the full U.S. population rather than just the labor force, so the ratio will decrease as more black men are imprisoned. FRED has the correct series, seemingly, but it’s via a different (OECD) data source that I’ve not dug into yet. It has the parallel data source for females.
The moral is just that there are many ways to measure unemployment, and which measure you pick will depend on which question you want answered. If you want to measure whether people are opting out of the labor force for happy reasons or sad reasons, the government tracks that. If you hear someone say that government statistics are bunk and that they don’t address Objection Objection x, your first assumption should be that the speaker is wrong.