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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.
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.
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
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.
Britain is currently in the situation where uncertainty is preventing immigration, and convincing current residents to leave, =
Explain the record increase in the UK population and that actually since the referendum that net immigration has actually increased. This year since June 2016 the net increase was over 300,000, the highest we've ever seen.
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It little behooves the best of us to comment on the rest of us.
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.