I don't think that the particular example that you're giving is "fraught with peril". Note the lack of an upper bound on the labor force participation rate that you cite - 16+ includes people of retirement age, whereas the measure given in the article shows that the official unemployment rate for men 25-55 is just 1/3 of the "true" unemployment rate that includes disaffected workers. This is significant.
Using that as the "true" unemployment rate is, frankly, bullshit. The number they're citing is the OECD "employment rate"[0][1], defined as the employed share divided by the total population in that demographic. Thus it includes the disabled, stay-at-home-parents, the leisure class, those enrolled in education, and anyone else who is not working but has no desire to do so. The decline is almost entirely driven by the reduction in labor force participation rate from 97+% in that demographic in the 1960s to 88.8% today.[2] Is it unreasonable to expect males may on average voluntarily spend 3 years outside the labor force during their prime years?
If you want to count discouraged workers, use U4 — which currently stands at 4.1% vs. the U3 at 3.9%.[3] (U3 is 3.0% for the demographic in question.[4]) U6, which adds all other marginally attached workers and those employed only part-time who'd like to be full-time, stands at 7.4%.
If your concern is falling LFPR, say so. If your concern is discouraged workers, use U4/U6. But don't change the denominator on the unemployment rate from the labor force to the whole population and act like it's some huge hidden increase the authorities have been concealing from us.
[0] https://data.oecd.org/emp/employment-rate.htm
[1] https://fred.stlouisfed.org/series/LREM25MAUSA156S
[2] https://fred.stlouisfed.org/series/LRAC25MAUSM156S
No it doesn't. Aside from it being a nonsensical measure of 'health', the overall 'employment rate' is well above pre-1990 rates (as women have continued to enter the workforce).[0]
>If you deny this, then you're forced to argue that somehow the number of "disabled, stay-at-home-parents, the leisure class, those enrolled in education, and anyone else who is not working but has no desire to do so" has increased within the same demographic (25-55 males, so generally post-school),
Of course it has. Being a stay-at-home-dad was unthinkable in 1950. Post-graduate education is increasingly common, as is mid-life career switching. I can think of many reasons why we shouldn't expect a 98% labor force participation rate from that demographic in this century.
>Of course it has. Being a stay-at-home-dad was unthinkable in 1950. Post-graduate education is increasingly common, as is mid-life career switching. I can think of many reasons why we shouldn't expect a 98% labor force participation rate from that demographic in this century.
All of the points that you raised should not show such a sudden effect in the past < 10 years.
I don't know how the statistics are gathered, but I wonder if they separate those who wish to/need to work from those who don't. For those who have given up searching, that is.
Indeed they do. The rate you most commonly see tries to measure unemployment in the active labor force. If you're not actively looking for work, you're not counted as unemployed. There are other measures which do count "discouraged workers" and others not usually included. They're much higher.
This article[1] gets into a bit, but
"Some men choose not to work and can afford not to. That’s great, Furman says. But for many, probably most, dropping out of the work force not only means a lack of income but also a loss of the dignity that comes with not working."
still sounds like conjecture, to me.
[1]: https://www.brookings.edu/blog/up-front/2016/08/15/men-not-a...
I don't know if I agree with this. I mean okay, if your house is on fire and your thermometer is showing a comfortable 75 F, you should probably question your thermometer. But in the overwhelming majority of situations, especially involving extremely complex phenomena such as a national economy, one should absolutely not trust their perception or use it to question the validity of empirical evidence that has been collected.
On the first Friday of every month when the Employment Situation report is released, we get new analysis on jobs created, hours worked and hourly wages. This is great information, the only issue is that the hours and wage information is an average, not a median [2].
If economic reality changes to a point where citizens/politicians/economists become concerned with income inequality, this measure begins to lose it's significance. Average wages could increase while median wages fall. It is still "empirical evidence" but it isn't necessarily measuring what we think or want, labor force participation rates before/after women joined the workforce is an example. We should always be questioning the validity of our economic measures over time.
[1] https://www.cnbc.com/2018/09/07/us-nonfarm-payrolls-aug-2018... [2] https://www.bls.gov/news.release/empsit.b.htm
This was explored, but most of the article was about enhancing existing stats:
> She argues — rightly, I think — that the government should not focus on creating wholly new statistics. It should instead change and expand the ones that are already followed closely.
This is basically Anscombe's Quartet -- https://en.wikipedia.org/wiki/Anscombe%27s_quartet -- four completely different sets of points that have the same mean, variance, linear regression, and other stats but plotted out represent drastically different realities.
But instead of abstract datasets, we're saying drastically different underlying economic circumstances for different populations may be reported with the same GDP number.
So a single summary statistic "GDP is up!" without more detailed breakdowns can mean either "everyone is doing better!" or "the investor-class is making bank while everyone else is stagnant or falling behind". The point of the article is one of those seems to explain the populist anger, and our focus on the single summary statistic creates cognitive dissonance and makes the problem worse when people say to themselves "hey, this shit doesn't match what I'm struggling with everyday."
Or perhaps their parents are better off, more people are going to college, so fewer of them are forced to work menial jobs to pay the bills. I have no idea if that's true, but that's kind of the point; you have to dig deeper.
https://www.epi.org/publication/charting-wage-stagnation/
suggests that, in inflation adjusted terms, most workers wages are up a modest amount (6%) since 1979, while the 10th percentile workers have declined by 5% in that period.
The employment to population ratio has fallen 5-6% over the same time period (and 10% from its peak) . It may be recovering somewhat now, but it's not part of the charts and not close to the peak.
https://en.wikipedia.org/wiki/Employment-to-population_ratio
Worse still, comparing to household income, you see that a higher employment ratio is necessary just to maintain the income. That causes childcare, prepared food, and transportation expenses to rise faster than inflation... because even if prices are constant, more people need them. That's ignoring the falling percentage of jobs with insurance and pensions that that also reduce total compensation... it also ignores stock options.
It was common for 12-18yr olds to work part time at groceries, fast food, retail, theaters, delivery to earn gas money or save for a car or college/trade. That is largely gone. Those jobs seem to have been taken by desperate adults and seniors.
That's literally the exact opposite of what the author did. In fact the author painstakingly laid out how the government is doing exactly what you've accused the author of doing.
There are statistics that are being ignored because it does not fit the narrative.
Is to be expected. Easier access to college, general push to get a degree no matter what, plus raising cost of labour (minimal wage, healthcare regulations, etc.) equals drop in participation from youngsters.
Not an auspicious start, David. People believe lots of things that aren't true, for example that crime is going up. That's why reliance on objective measures is crucial.
Of course, the larger point about using the right measures is well taken. But switching to new measures to validate your preconceived gut feeling is fraught with peril. For example, labor force participation rate, which measures the non-institutional population 16 and older, is down to 62% from a peak of 67% in 2000: https://www.bls.gov/opub/mlr/2016/article/labor-force-partic... (from 67% to 62%). Is it because discouraged workers are leaving the workforce? Not really--the labor force participation rate of high-school and college-aged people (ages 16-24) is down dramatically. But the rate among those aged 25-55 is down just a few points.