It's becoming increasingly clear that there are serious problems at Statscan, Canada's statistics agency.
In 2014, they released jobs numbers which were suddenly abysmal, far below the average, then they retracted them and replaced them with more normal numbers, some say a little too normal.
In retrospect, it looks as if the bad numbers were accidentally released, although they were true, then quickly retracted and replaced with normal numbers in hopes of calming the public down.
It all seemed to subside, until today, when Statscan abruptly shaved 35% off the entire 2014 job creation numbers, going from 180,000 or so to 121,000.
This is a problem for many reasons.
For starters, jobs data is reviewed and revised each month, and any errors or alterations have ample time to be done during the year.
Given this system, it's very difficult to see how Statscan would need to reduce the total figure by 35% at the end of the year.
Something is very fishy, but they did.
This gets to the heart of the very issue of government statistics, most people believe they're reliably attained, credible, and accurate.
In fact, they are not, they are more of a political tool than reliable statistics.
Case in point, the government does not count you unemployed if you lost your job as a contractor, because contractors don't pay into EI.
Unless you pay into EI, you are not considered to be "unemployed.
" Yet, Statscan will consider you employed, so long as you have a job, business, or heck, even if you did one day of work mowing the neighbour's lawn for $10.
Here's the definition of employment, according to Statscan: a.
did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment.
It also includes unpaid family work, which is defined as unpaid work contributing directly to the operation of a farm, business or professional practice owned and operated by a related member of the same household; or b.
had a job but were not at work due to factors such as own illness or disability, personal or family responsibilities, vacation, labour dispute or other reasons (excluding persons on layoff, between casual jobs, and those with a job to start at a future date).
So, as we can see, jobs data is massaged for the best effects.
And even this massaging isn't enough for the government, so an extra 35% could be tacked on as well, if need be.
And if that weren't enough, Statscan stops counting you as unemployed after 6 months, presuming you no longer want a job.
This really helps perk up the job numbers too, by shoving all that dirty laundry under the carpet, in the closet, or anywhere it will fit.
For reference sake, the US is no better, they use the same sneaky tactics to convince the public the economy is doing great.
A far better measure of employment is the "Labour Participation Rate.
" This simply refers to the percentage of working age people(15 and over)who are working, versus the total number in this category.
So, it's a ratio.
If 10% of the population is not working, the Labour Participation Rate would be 90%.
Now with this, there is an element of differential, in that people unable to work are not factored in, so the seriously handicapped for instance.
So, we would factor in a margin for this, let's say 5%.
Given that Statscan reports Canada's unemployment at about 6.
6%, and we add 5% for handicapped people, you might guess that the Labour Participation Rate would be around 89% or so, right? Wrong.
It's 65.
9% at the time of this writing.
That's a 24% difference! Shouldn't the unemployment rate and Labour Participation Rate at least resemble each other? And as you might guess, the number most reported in the media, used by business, and quoted by politicians, is the unemployment rate.
And again, the same holds true in the US.
Since 2008, jobs have been scarce, and skilled people still have trouble finding work.
This doesn't fit with a mere 6.
6% unemployment rate though, but it would fit with a 15%-20% unemployment rate wouldn't it? Many economists are finally coming to the conclusion that government statistics cannot be trusted, and rightly so.
What's surprising is that businesses use these flawed statistics.
With so much on the line, needing accurate forecasts and reliable job and income data, one might wonder why businesses don't demand better data.
Well, there's an answer for that too.
Businesses pay for good data, they don't use government statistics.
But not all businesses, I'm speaking of the biggest and best companies, the ones run by insiders who know how the system works.
With these type of hurdles, it's clear that succeeding in business or investing can be harder than it should be.
And worse still, many people may never know why they're having such a hard time.
They look at a 6.
6% unemployment rate and think the economy is doing well, then are confused by why they can't find work, or their business sets a forecast for growth according to government projections, but fail to reach their targets because the economy didn't grow at the pace they were told it did, or would.
Therefore, faulty data put out by governments has consequences, and does damage.
So, why do governments do it? I think you know, governments are run by people, people who want to be elected or re-elected, it's that simple.
In 2014, they released jobs numbers which were suddenly abysmal, far below the average, then they retracted them and replaced them with more normal numbers, some say a little too normal.
In retrospect, it looks as if the bad numbers were accidentally released, although they were true, then quickly retracted and replaced with normal numbers in hopes of calming the public down.
It all seemed to subside, until today, when Statscan abruptly shaved 35% off the entire 2014 job creation numbers, going from 180,000 or so to 121,000.
This is a problem for many reasons.
For starters, jobs data is reviewed and revised each month, and any errors or alterations have ample time to be done during the year.
Given this system, it's very difficult to see how Statscan would need to reduce the total figure by 35% at the end of the year.
Something is very fishy, but they did.
This gets to the heart of the very issue of government statistics, most people believe they're reliably attained, credible, and accurate.
In fact, they are not, they are more of a political tool than reliable statistics.
Case in point, the government does not count you unemployed if you lost your job as a contractor, because contractors don't pay into EI.
Unless you pay into EI, you are not considered to be "unemployed.
" Yet, Statscan will consider you employed, so long as you have a job, business, or heck, even if you did one day of work mowing the neighbour's lawn for $10.
Here's the definition of employment, according to Statscan: a.
did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment.
It also includes unpaid family work, which is defined as unpaid work contributing directly to the operation of a farm, business or professional practice owned and operated by a related member of the same household; or b.
had a job but were not at work due to factors such as own illness or disability, personal or family responsibilities, vacation, labour dispute or other reasons (excluding persons on layoff, between casual jobs, and those with a job to start at a future date).
So, as we can see, jobs data is massaged for the best effects.
And even this massaging isn't enough for the government, so an extra 35% could be tacked on as well, if need be.
And if that weren't enough, Statscan stops counting you as unemployed after 6 months, presuming you no longer want a job.
This really helps perk up the job numbers too, by shoving all that dirty laundry under the carpet, in the closet, or anywhere it will fit.
For reference sake, the US is no better, they use the same sneaky tactics to convince the public the economy is doing great.
A far better measure of employment is the "Labour Participation Rate.
" This simply refers to the percentage of working age people(15 and over)who are working, versus the total number in this category.
So, it's a ratio.
If 10% of the population is not working, the Labour Participation Rate would be 90%.
Now with this, there is an element of differential, in that people unable to work are not factored in, so the seriously handicapped for instance.
So, we would factor in a margin for this, let's say 5%.
Given that Statscan reports Canada's unemployment at about 6.
6%, and we add 5% for handicapped people, you might guess that the Labour Participation Rate would be around 89% or so, right? Wrong.
It's 65.
9% at the time of this writing.
That's a 24% difference! Shouldn't the unemployment rate and Labour Participation Rate at least resemble each other? And as you might guess, the number most reported in the media, used by business, and quoted by politicians, is the unemployment rate.
And again, the same holds true in the US.
Since 2008, jobs have been scarce, and skilled people still have trouble finding work.
This doesn't fit with a mere 6.
6% unemployment rate though, but it would fit with a 15%-20% unemployment rate wouldn't it? Many economists are finally coming to the conclusion that government statistics cannot be trusted, and rightly so.
What's surprising is that businesses use these flawed statistics.
With so much on the line, needing accurate forecasts and reliable job and income data, one might wonder why businesses don't demand better data.
Well, there's an answer for that too.
Businesses pay for good data, they don't use government statistics.
But not all businesses, I'm speaking of the biggest and best companies, the ones run by insiders who know how the system works.
With these type of hurdles, it's clear that succeeding in business or investing can be harder than it should be.
And worse still, many people may never know why they're having such a hard time.
They look at a 6.
6% unemployment rate and think the economy is doing well, then are confused by why they can't find work, or their business sets a forecast for growth according to government projections, but fail to reach their targets because the economy didn't grow at the pace they were told it did, or would.
Therefore, faulty data put out by governments has consequences, and does damage.
So, why do governments do it? I think you know, governments are run by people, people who want to be elected or re-elected, it's that simple.
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