Monthly US Labor Dept. jobs data not matching employment, Where are Donald Trump Rush Limbaugh Sean Hannity??, 6 month comparison reveals total employment only up 639k, White employment down 155k, Financial markets react to flawed monthly data
“There’s no other way to say this. The official unemployment rate, which cruelly overlooks the suffering of the long-term and often permanently unemployed as well as the depressingly underemployed, amounts to a Big Lie.”…Gallup CEO Jim Clifton
“But actually, he thought as he re-adjusted the Ministry of Plenty’s figures, it was not even forgery. It was merely the substitution of one piece of nonsense for another. Most of the material that you were dealing with had no connexion with anything in the real world, not even the kind of connexion that is contained in a direct lie. Statistics were just as much a fantasy in their original version as in their rectified version. A great deal of the time you were expected to make them up out of your head. For example, the Ministry of Plenty’s forecast had estimated the output of boots for the quarter at one-hundred-and-forty-five million pairs. The actual output was given as sixty-two millions. Winston, however, in rewriting the forecast, marked the figure down to fifty-seven millions, so as to allow for the usual claim that the quota had been overfulfilled. In any case, sixty-two millions was no nearer the truth than fifty-seven millions, or than one-hundred-and-forty-five millions. Very likely no boots had been produced at all. Likelier still, nobody knew how many had been produced, much less cared. All one knew was that every quarter astronomical numbers of boots were produced on paper, while perhaps half the population of Oceania went barefoot. And so it was with every class of recorded fact, great or small. Everything faded away into a shadow-world in which, finally, even the date of the year had become uncertain.”…George Orwell “1984″
“We are being lied to on a scale unimaginable by George Orwell.”…Citizen Wells
Why are the financial markets reacting to flawed monthly data from the US Labor Dept. instead of employment trends over several or more months from the same source?
Why is the media, including conservative media, regurgitating the monthly fictional jobs data as if it were the gospel truth?
Where are Donald Trump, Rush Limbaugh, Sean Hannity and others on this Orwellian misportrayal of reality?
Most of us paying attention know that the monthly jobs data from the US Labor Dept. does not reflect reality.
We know this from the enormous numbers of people who have dropped out of the labor force, economic indicators and hunger around us.
We also know this because of the record number of millenials and other age groups who have been forced to live with family and friends.
Let’s examine the latest jobs report.
“Total nonfarm payroll employment increased by 215,000 in July, and the unemployment rate was unchanged at 5.3 percent, the U.S. Bureau of Labor Statistics reported today.”
For the rest of the data we will access the same US Labor Dept. Historical tables.
Change from June to July:
Total employed + 101,000
White – 62,000 (you read that right, minus)
Black + 33,000
Asian + 21,000
Hispanic – 27,000
See anything wrong with that?
215,000 jobs added???
It gets worse.
Change from January to July:
Regardless of which revision to the monthly jobs report that you use, if you add up the mythical jobs added from February to July 2015 you get well over 1.2 million.
How does this square with the employment changes from the US Labor Dept?
Total employed + 639,000
White – 155,000 (you read that right, minus)
Black + 463,000
Asian + 211,000
Hispanic + 69,000
See any problems there?
The financial markets, the Fed are making decisions based on the flawed monthly data and it keeps getting reported.
People on this site often ask what can I do.
My answer: help get the word out, help counteract the Orwellian lies we are constantly being bombarded with.
From the US Labor Department on how they conjure up these numbers.
“1. Why are there two monthly measures of employment?
The household survey and establishment survey both produce sample-based estimates of employment, and both have strengths and limitations. The establishment survey employment series has a smaller margin of error on the measurement of month-to-month change than the household survey because of its much larger sample size. An over-the-month employment change of about
100,000 is statistically significant in the establishment survey, while the threshold for a statistically significant change in the household survey is about 400,000. However, the household survey has a more expansive scope than the establishment survey because it includes self-employed workers whose businesses are unincorporated, unpaid family workers, agricultural workers, and private household workers, who are excluded by the establishment survey. The household survey also provides estimates of employment for demographic groups.”
“5. Does the establishment survey account for employment from new businesses?
Yes; monthly establishment survey estimates include an adjustment to account for the net employment change generated by business births and deaths. The adjustment comes from an econometric model that forecasts the monthly net jobs impact of business births and deaths based on the actual past values of the net impact that can be observed with a lag from the Quarterly Census of Employment and Wages. The establishment survey uses modeling rather than sampling for this purpose because the survey is not immediately able to bring new businesses into the sample. There is an unavoidable lag between the birth of a new firm and its appearance on the sampling frame and availability for selection. BLS adds new businesses to the survey twice a year.”
“Reliability of the estimates
Statistics based on the household and establishment
surveys are subject to both sampling and nonsampling error.
When a sample, rather than the entire population, is
surveyed, there is a chance that the sample estimates may
differ from the true population values they represent. The
component of this difference that occurs because samples
differ by chance is known as sampling error, and its
variability is measured by the standard error of the estimate.
There is about a 90-percent chance, or level of confidence,
that an estimate based on a sample will differ by no more
than 1.6 standard errors from the true population value
because of sampling error. BLS analyses are generally
conducted at the 90-percent level of confidence.
For example, the confidence interval for the monthly
change in total nonfarm employment from the establishment
survey is on the order of plus or minus 105,000. Suppose the
estimate of nonfarm employment increases by 50,000 from
one month to the next. The 90-percent confidence interval on
the monthly change would range from -55,000 to +155,000
(50,000 +/- 105,000). These figures do not mean that the
sample results are off by these magnitudes, but rather that
there is about a 90-percent chance that the true over-themonth
change lies within this interval. Since this range
includes values of less than zero, we could not say with
confidence that nonfarm employment had, in fact, increased
that month. If, however, the reported nonfarm employment
rise was 250,000, then all of the values within the 90-percent
confidence interval would be greater than zero. In this case,
it is likely (at least a 90-percent chance) that nonfarm
employment had, in fact, risen that month. At an
unemployment rate of around 6.0 percent, the 90-percent
confidence interval for the monthly change in unemployment
as measured by the household survey is about +/- 300,000,
and for the monthly change in the unemployment rate it is
about +/- 0.2 percentage point.”