Posted on 10/06/2012 10:11:58 AM PDT by loucon
I've been trying to wrap my head around this stuff today and this is some of the stuff I came up with.
Based on a survey sample of 60,000: (avg. sample size used by the BLS)
Sep 2012
civilian labor force - 38,166 (63.6%)
employed - 35,191 (93.2%)
unemployed - 2,975 (7.8%)
not in labor force - 22,834 (36.4%)
An error in reporting of 40 out of 60,000 as employed vs. unemployed would result in a reduction of the unemployed rate of 0.1%, thus a 0.3% reduction (8.1%-7.9%) would be the result of 120 more recorded as employed vs. unemployed. 120 out of 60,000 is about 0.2%. At a +/- 1.0% error margin the swing could be 1.5%. For example, if the actual (no errors) unemployment rate was calculated at 8%, based on an error margin in the sampling of the 60,000 +/- 1%, the actual unemployment rate could fall anywhere between 6.5% and 9.5%. If the +/- 1% error margin was only applied to the work force, the swing in the unemployed number would be about half of that or 7.25% to 8.75%.
The BLS uses something called the 90- percent confidence interval. (see "the fine print" below) According to them, the 90-percent confidence interval for the monthly change in unemployment as measured by the household survey is about +/- 280,000. They show an employment increase of 873,000 jobs in Sep.. By their example, the 90- percent confidence interval on the monthly change would range from +593,000 to +1,153,000 (873,000 +/- 280,000). Therefore, in their opinion, it is likely (at least a 90-percent chance) that employment had, in fact, risen that month.
So here's my "therefore" and you can correct me where I may be off, as like I said, I'm only trying to wrap my head around this:
The equivalent error margin they are using is about 280,000/155,063,000 or +/- 0.18%. (see +/- 0.19% below) This seems like a ridiculous error margin to consider that you are 90% correct in your analysis and reporting.
http://www.bls.gov/news.release/pdf/empsit.pdf
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 exact difference, or sampling error, varies depending on the particular sample selected, and this 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 100,000. 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 -50,000 to +150,000 (50,000 +/- 100,000). 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-the-month 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 5.5 percent, the 90-percent confidence interval for the monthly change in unemployment as measured by the household survey is about +/- 280,000, and for the monthly change in the unemployment rate it is about +/- 0.19 percentage point.
In general, estimates involving many individuals or establishments have lower standard errors (relative to the size of the estimate) than estimates which are based on a small number of observations. The precision of estimates also is improved when the data are cumulated over time, such as for quarterly and annual averages.
The household and establishment surveys are also affected by nonsampling error, which can occur for many reasons, including the failure to sample a segment of the population, inability to obtain information for all respondents in the sample, inability or unwillingness of respondents to provide correct information on a timely basis, mistakes made by respondents, and errors made in the collection or processing of the data.
For example, in the establishment survey, estimates for the most recent 2 months are based on incomplete returns; for this reason, these estimates are labeled preliminary in the tables. It is only after two successive revisions to a monthly estimate, when nearly all sample reports have been received, that the estimate is considered final.
(emphasis mine)
my wonderful father always told me that figures don’t lie but liars figure.
i know what that means now.
blessings, bobo
Obama changed the work requirements for welfare to include bed rest, watching children, taking care of elderly. A lot of these new part time jobs may be women previously counted as unemployed / on welfare now counting as working by watching their own children.
Another Radical Obama Nominee
Matthew Vadum September 3, 2012
http://frontpagemag.com/2012/matthew-vadum/another-radical-obama-nominee/
A real communist, Erica L. Groshen, enough to make you sick. Nominated by Obama as Commissioner of Labor Statistics. Her job will be to release a favorable Jobs Report just a few days before the election.
That would explain the increase in total jobs available as well as the increase in the employed numbers.
“” Note that some of these part-time workers counted as employed by U-3(official unemployment rate) could be working as little as an hour a week.”
http://portalseven.com/employment/unemployment_rate.jsp
Unionized bureaucracy!
It all comes down to a report issued by two women who love Obama.
Logic has nothing to do with it.
Add 38166 + 22834. If you get 60000, you need new batteries in your calculator.
Whatever - statistically the chances are very very very small that Obama’s going to get next month a number on household employment nearly as large as in this month’s report (highest in thirty years) - that means the unemployment rate will be going back up, maybe to 8% or higher, four days before the election - and if somehow he does get another exceptionally high jobs number, we can be sure that “somehow” is because they’re juicing the figures.....
And from Zerohedge
Rosenberg On The Unemployment Rate: “If It’s Too Good To Be True, Then It Probably Is”
oops..
that must be 21,834 not in labor force. thanks for the correction.
Bottom line: the job growth came from college-aged kids (20-24) who took part-time jobs in record numbers. Then, this number was almost tripled by flawed seasonal adjustments.
Bottom line: the job growth came from college-aged kids (20-24) who took part-time jobs in record numbers. Then, this number was almost tripled by flawed seasonal adjustments.
“Read the individual state websites’ press releases on employment, see if it adds up:)”
I looked for those numbers but I could only come up with the numbers for Aug.. They say Sep. won’t be available until Oct. 30th.
This is what I found at census.gov:
Current Population Survey (CPS)
The Current Population Survey (CPS) is a monthly survey of about 50,000 households conducted by the Bureau of the Census for the Bureau of Labor Statistics. This survey covers Employment, Unemployment, Earnings, Educational Attainment, Income, Poverty, Health Insurance coverage, Job Experience and Tenure, School Enrollment, Voting and Registration, Computer Usage, Internet Usage, Veterans.
We need careers, Not temporary gift wrap jobs.
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.