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Unemployment in the UK is Now So Low It's in Danger of Exposing the Lie Used To Create the Numbers (businessinsider.com)
Unemployment in Britain is now just 4.5 percent. There are only 1.49 million unemployed people in the UK, versus 32 million people with jobs. This is almost unheard of. Unemployment was most recently this low in December 1973, when the UK set an unrepeated record of just 3.4 percent. From a report: The problem with this record is that the statistical definition of "unemployment" relies on a fiction that economists tell themselves about the nature of work. As the rate gets lower and lower, it tests that lie. Because -- as anyone who has studied basic economics knows -- the official definition of unemployment disguises the true rate. In reality, about 21.5 percent of all working-age people (defined as ages 16 to 64) are without jobs, or 8.83 million people, according to the Office for National Statistics. That's more than four times the official number. For decades, economists have agreed on an artificial definition of what unemployment means. Their argument is that people who are taking time off, or have given up looking for work, or work at home to look after their family, don't count as part of the workforce.
Before Brexit the UK never had these problems at all.
They need the EU to take over so that unemployment numbers are never in danger of getting anywhere close to zero.
AntiFA: An abbreviation for Anti First Amendment.
To call it a "lie" implies some sort of bias. Assumptions are often built in to such statistical analysis. Why is it a lie this time?
"... don't count as part of the workforce" what is the lie? at worst it might be a case of badly defined? what is the lie?
people not looking for work... are not part of workforce. it would be a "lie" to include those that don't want/cant work as well!!
Maybe they need to switch to a new reporting metric: how many people are unemployed, or working part time/multiple part time jobs when they would rather work full time? Personally, up until about 2-3 years ago, I was making $13 an hour with a graduate degree. I wasn't unemployed, but I also certainly wasn't making the economic impact I could have. With enough people working minimum wage jobs, part time, or stuck in the gig economy, you are still going to have negative impact on the economy, social unrest, and reliance on government support programs just as if you had unemployment.
The only thing necessary for evil to triumph is for it to be pitted against a slightly greater evil
To call it a "lie" implies some sort of bias. Assumptions are often built in to such statistical analysis. Why is it a lie this time?
There's a clear word; "unemployment"; which means "people who want work but don't have work". That's not easy to measure, but it's not so difficult. However, the measure, w has been gradually changed so that the number published as the "unemployment rate" no longer tells you how much "unemployment" there is. At least some of the changes were done deliberately in order to mislead. This is called "lying".
An example of this is that long term unemployed people are forced to take training. These people used to be included in the "unemployed" because they were really people that wanted jobs but couldn't get them. Then they were removed without providing both figures for a long time so that we could compare the before and after rate. This is called lying.
Right, the real lie about unemployment figures is that they don't account for underemployment.
Sure, lots of people have jobs, but how many have an 8 hour contract, and are begging the company to let them come in and work minimum wage?
It doesn't matter how you measure unemployment. The data is only going to be used to compare to historical values. If the definition of unemployed were to be changed, the historical data would be useless.
This is the whole accurate versus precise argument. The author argues the number isn't accurate. However, the purpose of this data doesn't require accuracy. It requires precision, a repeatable outcome.
One of our competitors trademarked the term "hypothesis". From now on, we will call them "boneheaded ideas".
To call it a "lie" implies some sort of bias. Assumptions are often built in to such statistical analysis. Why is it a lie this time?
Because the poster has some weird ideology they're trying to push on us.
Any abstraction is going to hide information, does it really make sense to count someone who took early retirement, or is doing full time childcare as unemployed?
I stole this Sig
Absolutely. In the US, there are many metrics that are reported and that help understanding the state of the labor force. Called U-1, U-2, ... U-6 which represent different aspect of the questions.
Saying that the unemployment should be the fraction of the 16-64 year old that do not work is ridiculous.
I did not start working until I was 25. I was a student before. Counting me as unemployed at that time would have been ridiculous.
If I chose to stop working at 60 because I have enough money to retire, why should I count as unemployed?
There are different category of people that do not work which surely needs to be reported. The definition of unemployement used in the US (U-3) is the one quoted, because it is the one that matches better the definition that other country used.
But you need to account differently people not working because they are studying, people that are working but would like a different job, people that are working but not full time, people that stopped looking because they do not believe they can find a job.
There are all important numbers that should all be reported. But in a short piece, you can not give that much context, so you quote a single number "unemployment" which will always be kind of misleading. But calling it a lie is ridiculous.
Life is complicated, a single number can not summarize everything accurately.
If you can't force legally press someone into labor, then there's no point reporting on anyone that is unwilling to or incapable of working.
If you know that 4.5% of Britons want work, but can't find it, then you can act on that information: find them, find open jobs within their skill-sets, and make connections.
If you know that 21.5% of working-age Britons aren't working, you have to do a LOT MORE work to filter out who can/can't work and who won't work.
To call it a "lie" implies some sort of bias. Assumptions are often built in to such statistical analysis. Why is it a lie this time?
It's a lie because the original definition communicated to voters an indication of how the economy was doing, while the current definition leans on that previous definition to give the appearance of a healthy economy when in fact it's terrible.
It's a lie because there has been enormous political pressure to skew the definition towards "statistical assumptions" in a way that suppresses voter outrage and dissent.
It's a lie because the value has morphed from a valid "quick snapshot" of the health of the economy, to a propaganda tool of the government for partisan purposes.
A much better indicator is had by random sampling, such as the Gallup poll, which tracks both employment and "underemployment". Here, underemployment is "people employed under 30 hours a week, but want to work more"(*).
(Also: Gallup good jobs index, which indirectly tells how satisfied workers are with their jobs.)
The Gallup poll notes that the results(*) can't be directly compared because federal statistics are "seasonally" adjusted. Seasonally adjusted? Why should unemployment numbers be adjusted *at all*?
(*) The article is about the UK, not US, but the principles are the same.
We hear about "the Dow" as being some majestic heartbeat of the health of the stock market. It's not really that accurate and/or useful, and better metrics exist. It has history, so people latch on to it as some sort of magic number or indicator. In reality, not that great. But still reported on because it's easy and familiar. Unemployment is actually a complex and multivariate metric, too. It can be sliced and diced by region, ethnicity, age, martial status, gender, job seeking status (as well as combinations of such metrics). This is the kind of thing economists and data nerds get into but when people are listening to the news about all the news will report is the top line number, since reporting the complexity will make for a long report most people don't care about. But the metric has been gathered the same way for years, so it's not a "lie" per se -- it's just people don't generally care about the minutae of the underlying data. It would be worse if the metric were redefined on the whims of politics or popular opinion, then it would really be a lie, or just useless. Including retirees or people who aren't actively looking for a job -- students, children, stay at home parents and retirees -- can be very reasonable assumptions since all those people are doing something else that prevents them from entering the workforce, or they have left the workforce entirely with no plans to return.
Governments should be caring a lot about the minutae of these metric, though, for many reasons. Having high unemployment for young people (especially young men) can have severe consequences for tax revenues, security/unrest/happiness, ability to pay for entitlement programs. Also, young people may leave if they can find work elsewhere, and not come back to help your economy. As retirees live longer they take more financial resources for longer than previous statistical models used for long term budgeting allowed, leading to funding issues for healthcare and drugs.
Of course, you also have politicians who take good numbers as a sign of their brilliance, and bemoan bad numbers as "a result of the poor statistical design of metrics" or "not representing reality", etc. Success has many fathers, defeat is an orphan.
Because the poster has some weird ideology they're trying to push on us.
This has something to do with Bitcoin, doesn't it?
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Any abstraction is going to hide information, does it really make sense to count someone who took early retirement, or is doing full time childcare as unemployed?
Yes, because they are unemployed. The common definition of "unemployed" is "not employed". The first online dictionary entry that google returned says "person without a paid job but available to work." Neither one includes any mention of "retired" or "wants to work".
The "weird ideology" here is called "the English language".
Now, the politicians in power want to make the unemployment numbers look lower than "unemployed" would, so they include "seeking work" as part of the measurement. Every administration in the US that has wanted to make themselves look proactive towards job creation has relied on the modified definition.
However, the answer to "does it make sense" when applied to a number that is being used to measure the employment economy is actually "no", because it is silly to count housespouses, retired, or those who are no longer seeking employment as "unemployed" for the sake of how much money to invest in creating new jobs.
It's also silly (or dishonest) to hide them by using the word "unemployed" incorrectly. There is a better word: "underemployed". People who are employed less than they want to be. That would naturally include part time workers who want to work full time, and any government action to try to increase the number of jobs should include consideration of those folks, too.
Given the way the term "unemployed" is deliberately misused, it is not a "ideology" to point that fact out occasionally. It is a valid reminder of what the government is actually telling us, and not telling us.
In the US, there are many metrics that are reported and that help understanding the state of the labor force. Called U-1, U-2, ... U-6 which represent different aspect of the questions.
To pad this out - from Wikipedia:
The Bureau of Labor Statistics also calculates six alternate measures of unemployment, U1 through U6, that measure different aspects of unemployment:
U1: Percentage of labor force unemployed 15 weeks or longer.
U2: Percentage of labor force who lost jobs or completed temporary work.
U3: Official unemployment rate per the ILO definition occurs when people are without jobs and they have actively looked for work within the past four weeks.
U4: U3 + "discouraged workers", or those who have stopped looking for work because current economic conditions make them believe that no work is available for them.
U5: U4 + other "marginally attached workers", or "loosely attached workers", or those who "would like" and are able to work, but have not looked for work recently.
U6: U5 + Part-time workers who want to work full-time, but cannot due to economic reasons (underemployment).
#DeleteChrome
No, his argument is spot on. Other people in this thread are saying things like, "The common definition of 'unemployed' is 'not employed'.... The 'weird ideology' here is called "the English language'." That pretty closely matches the spirit of the original article [summary], which said that unemployment statistics should include everyone who is not currently in a job, including "people who are taking time off ... or work at home to look after their family."
The grandparent provided an enlightened discussion of why the current approach to unemployment statistics makes more sense than the original article, and pointed out that there are many useful ways to count unemployment. In that context, your response made no sense at all. You seem to be saying, "the current system would count you correctly, so you shouldn't defend the current system."
At least some of the changes were done deliberately in order to mislead. This is called "lying".
Where is the evidence of that? The article itself lacks any evidence of deliberately misleading information. However, the authoer of the article itself is very misleading when s/he claims that the "true" figure is 21.5% which they apparently obtain using all people of working age. This does not exclude stay-at-home parents, students and those too disabled or sick to work and so is clearly going to be a wild overestimate.
While it might be true that the current statistics are not giving a true picture but if you want to claim that this is due to lying i.e. a deliberate attempt to mislead, you need to explain why. Governments may be untrustworthy but so are the media so I'm certainly not going to take the word of some random website without a solid, evidence-backed argument.
...most people create no value in their shitty jobs.
If that's so, why do you suppose someone is paying them?
I'm not sure what you include in the shitty job category. Cleaning bathrooms, perhaps? Yup, shitty job, literally. But I sure value having clean bathrooms here in my office.
The "% of people actively looking for work" definition of employment is entirely valid for it's intended audience.
The people that track unemployment don't give a crap about newspaper articles or politicians.
Instead they are trying to tell people how hard much competition there is to find a job. The employers need to know if they are going to get 1,000 applications, or just 1. So do the job seekers.
Just as Mode and Median are perfectly valid types of "Averages", so is the "% looking" valid for unemployment.
Stop misunderstanding what people are saying and then blaming them for your own stupidity.
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I've bolded the important part. TFA makes no such claim, and in fact states that the same measure has been used for decades. If you have evidence that the definition of unemployment was changed to make the economy look better than it actually was, please present it. The argument TFA presents is that the economy has changed so that the definition no longer paints as clear a picture of the economy as it did in the past.
From a statistical perspective, as long as the definition and method of measurement remains consistent over time, it is useful data. It is even more useful when paired and analyzed together with slightly different measures like the inactivity rate as TFA does. But it's not a lie. It is data. Not everything in life has a clear-cut and straightforward definition. So you come up with a definition that is clear-cut and straightforward (and usually selected because it's easier to measure), and you use it to collect data. If you don't like the definition, you can come up with a different definition and collect data on it. But calling the data set you dislike a lie is nothing but an ad hominem attack.
I also find the title of TFA (and summary) highly suspect. The title claims the unemployment figures are very close to exposing the purported lie in the definition of "unemployment". But for that to actually happen, the unemployment rate would have to go negative.. That is, everyone who is looking for a job gets one. And a few people who don't want a job have one (how, I dunno - slavery?).
I'm all for educating people that the definition of "unemployment" is not as clear-cut as they might assume at first glance. But calling it an outright lie is nothing but grandstanding.
The big question is what you want to measure. The unemployment rate (as conventionally defined) is trying to measure what fraction of people who want jobs can't find them. The author of the cited article is correct that the official unemployment rate is leaving out some people who probably ought to be counted, like people who have given up looking for work. This can be really important, because bad data may cause economists to recommend bad policy. In the USA during the 1990s, for instance, sustained low official unemployment wound up encouraging "hard core" unemployed people who were left out of the official statistics to start looking for work. That meant low unemployment didn't cause inflation to take off the way economists predicted. A different measure of unemployment that made fewer assumptions about who was employable might have prevented them from making that mistake.
That said, there are problems with the author's proposal of including everyone between 16 and 64 as the pool of potential workers. The economy has changed over time in ways that systematically change who is likely to look for work. Higher education is far more important than it used to be, so that college age people probably shouldn't be looking for full-time work, and 16 to 18 year olds certainly shouldn't be. At the same time, though, there are fewer stay-at-home parents, which increases the expected size of the workforce. That means using the entire 16-64 year old population as the potential workforce will make comparisons to historical data much less useful, which also undermines the value of the data for policy decisions.
Probably the best solution is to give up on the idea of capturing the state of employment in a single number. The US government, for instance, calculates no fewer than 6 versions of the unemployment rate and a "labor participation rate" that is closer to the kind of calculation the original author wants. One of those rates is the official unemployment rate, but it can be compared against other rates to see if they're changing in sync. A common comparison is between U3 (the official rate) and U6 (which counts part time workers who would like to work full time as unemployed and includes people who have given up looking for work as part of the potential workforce). U3 is what has traditionally been used to measure unemployment, but U6 probably gives a better idea of how much real slack there is in the labor force.
There's no point in questioning authority if you aren't going to listen to the answers.