I don't believe the 8.3% number either. I'm sure it's much higher. The government is playing with the numbers to make it appear to be better than it truly is. Anyone paying attention can see it's not as good as they say.
So what you're saying is, you can't come up with the true number because there's not enough data provided to do so?
X-12-ARIMA isn't for the faint of heart, it involves some statistical knowledge. It's an auto-regressive moving average if that means anything to anybody.
In English, it smooths out cyclical spikes that are well developed patterns. Case in point, someone is a fisherman or works the fishing docks. There will be a huge hiring spike during say crab season and then a huge spike down when it's over. Seasonal adjustments smooth that out over the course of a year so you don't get those spikes.
The reason they do that is to see the "real change" in levels vs. just seeing "huge spikes" that are simply due to the season every year. By smoothing out those "huge spikes" over time, one can more easily see if there was actual job growth or was it just "fishing season".
Another example which I found very weird. In December, transportation carriers, i.e. UPS, Fed-Ex, DHS etc. added 50,000 jobs in a month. Well, hot damn I thought for sure those would be seasonal, but it appears not this month. I guess UPS, Fed-Ex, DHS etc. just decided to do their permanent hiring right at the start of the holiday season, which in a way makes sense.
Hey, login, you can track your comments and publish immediately, no moderation queue!
You can download the software for X-12-ARIMA even. I have it. It's the initial unemployment claims, done weekly, where seasonal adjustments get weird but I think you can even get that version of the seasonal adjustments. Initial unemployment claims are weird because the data lags, comes in slowly from the states plus is a weekly release, vs. monthly and so there is more variance.
But trying to claim seasonal adjustment is some great, huge mystery isn't true.
Check out Chinn, over on Econbrowser. He runs X-12-ARIMA all of the time. Now he's "way up there" in the theoretical clouds sometimes so translating his thoughts to English gets lost but you can indeed, pull down the not seasonally adjusted data, run X-12-ARIMA on it and come up with the matching seasonally adjusted version.
I think this guy is after a red herring if he's trying to claim seasonal adjustments are some grand conspiracy. Hiring is seasonal, jobs are seasonal. Anybody who has tried to land a career position in the last half of December knows this. Anyone trying to land a construction job in January knows this.
What's irksome is how the BLS does not seem to have a statistical approach that's valid to retrofit new annual population adjustments across past months of data. I plain think they need to update their population controls from annual to at least quarterly or something, but that's just me.
Hey, login, you'll bypass all of the CAPTCHA plus registered users can create little "mini blogs" in the comments, links, images, videos.
I think I caught one my own errors in trying to break down and re-state what you had about the census bureau data.
I stated that "a decade's worth" of census bureau population data gets poured into January, all at once, when in reality, I believe you had actually written that one year's worth of population adjustment data gets poured into the month of January.
For what it's worth, Biderman of TrimTabs states outright that the formula/formulae that the BLS uses in coming up with its "seasonal adjustment" is unknown, so I'm still trying to wrap my head around how it's possible that such an important formula can be proprietary knowledge, if in fact Biderman is correct in that assessment.
Here's an excerpt of Biderman's statement from his article on this subject:
"For those of you who care, look at Table B-1, Total Nonfarm Employment in today’s BLS press release. Start with the non seasonally adjusted table that shows that in November 2011, there were 133.172 million actual jobs. Actual jobs dropped by 220,000 jobs in December and actual jobs dropped an additional 2.7 million in January. Only as a result of unknown seasonal adjustments, could the BLS report 243,000 new hires in January."
As to the issue of Shadowstats, I believe John Williams is currently reporting approximately 23% as U6 (which your readers will understand is the broader measurement of unemployment + underemployment), but I am also unsure as to how he's arriving at that number, as I do not believe even the BLS or Fed Reserve data would produce that high of a % (even though neither formally reports U6 to the best of my knowledge).
Thanks again for your outstanding research and writing, Robert.
The annual difference is in thousands, which is should be, but taking the difference in seasonally adjusted numbers from not seasonally adjusted ones, the cyclical pattern swings into the millions. I'm trying to say trimlabs is focusing in on something that is just a cyclical pattern, yet at the same time, also showing that the financial crisis added some error into the seasonal adjustment algorithm itself (it appears to me anyway).
Hey thanks. We link to Zerohedge and they to us, right hand column. I'm pretty dedicated to this site, so if people want to read things they have to enter a new URL. (how hard is that!) ;) but I've run over and commented in ZH before and if they find a goodie, I'll link it up.
I should ask ZeroHedge how they block out spam because our system is pretty kludged. You have to respond to the registration email to prove you're a person. I went in an hand approved your account, you're good to go here.
That's right on unemployment rates. The unemployment statistics are ratios, created by subsets of population ratios. So, if one wants to believe only the official unemployed make up the real unemployed and must be part of the BLS definition of civilian labor force, then the rate is 8.2%. I'm thinking of shadowstats, which I think has unemployment around 24% but I cannot find out exactly how he is calculating that so I often don't mention it.
For those of you wanting to have Robert "just tell you" the answer as to whether the BLS U3 is or isn't "accurate," he already has provided the best answer possible to that question, and if you had bothered to read the excellent synopsis he provides, you won't get any clearer or better answer anywhere (to the best of my knowledge).
If I took a stab at answering your "just tell us" question, I'd respond by writing that as Robert Oak has already pointed out, the BLS U3 data is accurate only inasmuch as:
1) It is consistent with past months where a decade's worth of revised population based on new census bureau data was suddenly dumped into the total labor pool,
2) It has produced the same type of month-to-month (December to January) wild gyration in a very similar manner as it has three times prior when this census bureau data has been 'dumped' into the BLS computations,
3) The question of whether the BLS U3 January data is "accurate" is the wrong question to ask, given points 2 & 3 above, and the more important point is whether it deviates significantly in terms of December-to-January skewed effect from similar past periods (when 10 years worth of census bureau data gets dumped into and merged, all at once, with one month of BLS U3 statistical analysis; in this case, it appears that it does so deviate.
I hope I read & understood Robert's explanation correctly, and that I was able to at least roughly accurately answer the only question that can be fairly be asked at this point regarding the U3 report for January, to wit, whether it is statistically reliable (rather than whether it accurately reports absolute unemployment levels in the U.S. for the month of January in 2012, which it almost certainly does not).
Robert, please feel free to correct me or clean up any errors I've made in attempting to understand this and break it down.
Thanks
*This is TruthInSunshine, but the system wouldn't accept my response when I tried to use that moniker, so I abbreviated my name in order to get this posted
Thanks for that excellent & prompt response, Robert!
I have just registered on Economic Populist, but I see that you've already found the Zero Hedge article I referenced and that you've also already drilled down on the TrimTabs data that Charles Biderman compiled regarding January's BLS NFP report to identify even more curiosities.
I am trying to digest the TrimTabs data and what you extrapolated from it right now, but I do believe I have the basic gist.
You'd be a pure asset to the readership at Zero Hedge if you were to reproduce your essays and thoughts on this critical issue over there!
Every one picks the statistic that suits him well.
The News and Media Industrie always picks the Hyped up one.
If it fails the have a reason to write a correction the next day.
The avarage Unemployment did not get better at all. It cant.
The hausing is still depressed, we have not enough production in the US itself , and there are on the same news page plenty of Job Layoff anauncments.
So like it or not it will take a long time to get better , so be carefull with your spending.
And if the gasprice goes up again the economy will nosedive again.
Because of a depressed income situation there is not enough liquidty to keep spending ,to fill the car is priority and the other stuff has to wait , results in a nosedive again , its always a delay from about 60 to 90
Days until people get the Creditcard outmaxed.
One mayor economy push would be a stable gasoline price, but with wild swings from 10 to 15 % this wont happen. In the moment the Gas price is up the economy breakes are on. One way to solve this would be a Pay increase but the wages are actually down and not up.
The minimum wage should be linked to the Gasoline price,because of the major impact gasoline has.
Sorry, that's the official unemployment rate. U-6 is 15.1%, no much changed. If you want to calculate the real unemployment rate, read this post, What's the Real Unemployment Rate, and plug in the current numbers. In this new article overviewing some other data from January's employment report, I calculated 17%. That said, these estimates vary depending on assumptions and subgroups included. Point is to pay attention to the data and assumptions used. The real unemployment rate sure ain't 8.3%, not with record duration and people running out of benefits without a job and on and on.
The civilian non-institutional population was adjusted by an additional 1.510 million. Do you think, magically, the population of the United States, with a total population of 312,959,348, and the non-institutional population being 242,269,000, could magically increased by 1.510 million, in addition to the monthly growth of 175,000?....in a month?
Think about it. There are basically about 3 million immigrants in a year, so no way in just 30 days you could have that kind of population increase. The monthly change in total U.S. population hovers around 200,000 a month. Maybe in China or India monthly population could increase by a million, after all each of those countries has 1.4, 1.6 billion people, but not the U.S. with our population levels. Not unless all women suddenly turned into Octomom.
Or would the size of the population that are not in the labor force, before these population controls and Census data was added, 86.697 million people, also increase by proportion via the 2010 Census adjustments?
The real question is of the adjustments, only 17.1% were entered as part of civilian labor force. *That* is the yet to be answered question, which at the bottom of this article, I say "stay tuned", for we're going to dig into that one further.
But I am clearly stating one cannot claim 1.2 million dropped out of the labor force because you're comparing apples and oranges.
You're comparing two completely different population base numbers upon which everything else is derived and that is not statistically valid.
Yes it's hard to wrap your head around but that doesn't make it B.S. Just because someone whips out a few numbers, graphs and even an equation at you, does not mean they are full of shit, although they might be full of calculator.
Could it be possible for you to explain(succinctly) why the number 1.2 mil dropping out of the workforce is inaccutate. Your description has the "flare" of dazzling with Bullshit
Ah, seasonal adjustments are another thing seemingly going a little nuts. We've seen the modeling "blow up" on housing data, and even the manufacturing ISM report. Some of this is blamed on the financial crisis. Basically they all use the same algorithm, X-12-ARIMA, which is an auto-regressive moving average algorithm.
Remember black swans and fat tails? Seems history now has the financial crisis in it's data points which is throwing the thing out of whack.
The first is the monthly difference between the seasonally adjusted payrolls data and the not seasonally adjusted one. As one would expect, we do see massive spikes in job growth as seasonal adjustments. The worst month is January and that's because people fire at the end of the year and don't hire like they do, esp. over the summer. Point of this is there is a clear cyclical pattern.
The next graph is annual of payrolls, seasonally adjusted for the year minus payrolls not seasonally adjusted. The difference should be zero. Notice how it's divergenging in 2009, 2010. Now it's not by much the data is in thousands, but it shows, at least to me primilary that the financial crisis did throw off the X-12-ARIMA algorithm. It should be zero theoretically for the year (or damn close).
Can you register here on EP and then link up to what you're talking about? I don't cross post, simply because EP keeps my more busy, I simply cannot keep up with everything. But I have delved into BLS data now for years and do have a mathematical/statistical background.
They do have real problems with modeling population adjustments. But I'm not sure which post you're referring to, this is the "Numerian" thread. I'll try to go check out TrimTabs report.
Seems one thing all have in common, we want better statistics, more drill down and larger surveys....so bottom line, keep the politicians out of the gov. statistical agencies (thank you Clinton, get your fingers out of that pie!) and give them more funding (and stop hiring H-1Bs, get some out of work Americans, Jesus!)
I cited an excerpt of your outstanding essay over at zerohedge.com, in the comments section, and I hope that you do not mind.
If you care to have your essay published on Zero Hedge, please forward it to tips@zerohedge.com.
I am apolitical, and consider myself independent politically, but I do believe the BLS methodology for calculating U3 is extraordinarily flawed, for many of the reasons you cite so succinctly.
Thank you for taking the time and effort to write such an outstanding essay that highlights the flaws in the BLS methodology for measuring employment and the number of jobs gained or lost monthly.
p.s. - There is an article on Zero Hedge which essentially highlights why Charles Biderman of TrimTabs agrees with much of what you wrote, and for many of the identical reasons, titled 'TrimTabs Explains Why Today's "Very, Very Suspicious" NFP Number Is Really Down 2.9 Million In Past 2 Months.'
Thanks again for your contribution to this critical issue.
Partly of our own making by voting for Voodoo economics in 1980, 1984, 1988, 2000 and 2004. I was guilty in 88' because Dukakis freaked me out. I ranted about the debt from Reagan until the GWBush collapse. Now is not the time to take billions out of the economy hopefully soon but not now.
I wish the Republican candidates would receive closer scrutiny. Their "cures" for the economy are based on many, many unemployed as government spending collapses. How a whole political party can go insane is something we have not seen in my lifetime...maybe 1964? These people are truly scary.
I don't believe the 8.3% number either. I'm sure it's much higher. The government is playing with the numbers to make it appear to be better than it truly is. Anyone paying attention can see it's not as good as they say.
So what you're saying is, you can't come up with the true number because there's not enough data provided to do so?
X-12-ARIMA isn't for the faint of heart, it involves some statistical knowledge. It's an auto-regressive moving average if that means anything to anybody.
In English, it smooths out cyclical spikes that are well developed patterns. Case in point, someone is a fisherman or works the fishing docks. There will be a huge hiring spike during say crab season and then a huge spike down when it's over. Seasonal adjustments smooth that out over the course of a year so you don't get those spikes.
The reason they do that is to see the "real change" in levels vs. just seeing "huge spikes" that are simply due to the season every year. By smoothing out those "huge spikes" over time, one can more easily see if there was actual job growth or was it just "fishing season".
Another example which I found very weird. In December, transportation carriers, i.e. UPS, Fed-Ex, DHS etc. added 50,000 jobs in a month. Well, hot damn I thought for sure those would be seasonal, but it appears not this month. I guess UPS, Fed-Ex, DHS etc. just decided to do their permanent hiring right at the start of the holiday season, which in a way makes sense.
Hey, login, you can track your comments and publish immediately, no moderation queue!
X-12-Arima - thanks! That's the next go-to source for me in wrapping my head around the latest & greatest from the BLS.
TIS
You can download the software for X-12-ARIMA even. I have it. It's the initial unemployment claims, done weekly, where seasonal adjustments get weird but I think you can even get that version of the seasonal adjustments. Initial unemployment claims are weird because the data lags, comes in slowly from the states plus is a weekly release, vs. monthly and so there is more variance.
But trying to claim seasonal adjustment is some great, huge mystery isn't true.
Check out Chinn, over on Econbrowser. He runs X-12-ARIMA all of the time. Now he's "way up there" in the theoretical clouds sometimes so translating his thoughts to English gets lost but you can indeed, pull down the not seasonally adjusted data, run X-12-ARIMA on it and come up with the matching seasonally adjusted version.
I think this guy is after a red herring if he's trying to claim seasonal adjustments are some grand conspiracy. Hiring is seasonal, jobs are seasonal. Anybody who has tried to land a career position in the last half of December knows this. Anyone trying to land a construction job in January knows this.
What's irksome is how the BLS does not seem to have a statistical approach that's valid to retrofit new annual population adjustments across past months of data. I plain think they need to update their population controls from annual to at least quarterly or something, but that's just me.
Hey, login, you'll bypass all of the CAPTCHA plus registered users can create little "mini blogs" in the comments, links, images, videos.
Thanks, Robert.
I think I caught one my own errors in trying to break down and re-state what you had about the census bureau data.
I stated that "a decade's worth" of census bureau population data gets poured into January, all at once, when in reality, I believe you had actually written that one year's worth of population adjustment data gets poured into the month of January.
For what it's worth, Biderman of TrimTabs states outright that the formula/formulae that the BLS uses in coming up with its "seasonal adjustment" is unknown, so I'm still trying to wrap my head around how it's possible that such an important formula can be proprietary knowledge, if in fact Biderman is correct in that assessment.
Here's an excerpt of Biderman's statement from his article on this subject:
"For those of you who care, look at Table B-1, Total Nonfarm Employment in today’s BLS press release. Start with the non seasonally adjusted table that shows that in November 2011, there were 133.172 million actual jobs. Actual jobs dropped by 220,000 jobs in December and actual jobs dropped an additional 2.7 million in January. Only as a result of unknown seasonal adjustments, could the BLS report 243,000 new hires in January."
As to the issue of Shadowstats, I believe John Williams is currently reporting approximately 23% as U6 (which your readers will understand is the broader measurement of unemployment + underemployment), but I am also unsure as to how he's arriving at that number, as I do not believe even the BLS or Fed Reserve data would produce that high of a % (even though neither formally reports U6 to the best of my knowledge).
Thanks again for your outstanding research and writing, Robert.
TIS
The annual difference is in thousands, which is should be, but taking the difference in seasonally adjusted numbers from not seasonally adjusted ones, the cyclical pattern swings into the millions. I'm trying to say trimlabs is focusing in on something that is just a cyclical pattern, yet at the same time, also showing that the financial crisis added some error into the seasonal adjustment algorithm itself (it appears to me anyway).
Hey thanks. We link to Zerohedge and they to us, right hand column. I'm pretty dedicated to this site, so if people want to read things they have to enter a new URL. (how hard is that!) ;) but I've run over and commented in ZH before and if they find a goodie, I'll link it up.
I should ask ZeroHedge how they block out spam because our system is pretty kludged. You have to respond to the registration email to prove you're a person. I went in an hand approved your account, you're good to go here.
That's right on unemployment rates. The unemployment statistics are ratios, created by subsets of population ratios. So, if one wants to believe only the official unemployed make up the real unemployed and must be part of the BLS definition of civilian labor force, then the rate is 8.2%. I'm thinking of shadowstats, which I think has unemployment around 24% but I cannot find out exactly how he is calculating that so I often don't mention it.
"...they have decided to start the family" ????
Do you have a brain?
For those of you wanting to have Robert "just tell you" the answer as to whether the BLS U3 is or isn't "accurate," he already has provided the best answer possible to that question, and if you had bothered to read the excellent synopsis he provides, you won't get any clearer or better answer anywhere (to the best of my knowledge).
If I took a stab at answering your "just tell us" question, I'd respond by writing that as Robert Oak has already pointed out, the BLS U3 data is accurate only inasmuch as:
1) It is consistent with past months where a decade's worth of revised population based on new census bureau data was suddenly dumped into the total labor pool,
2) It has produced the same type of month-to-month (December to January) wild gyration in a very similar manner as it has three times prior when this census bureau data has been 'dumped' into the BLS computations,
3) The question of whether the BLS U3 January data is "accurate" is the wrong question to ask, given points 2 & 3 above, and the more important point is whether it deviates significantly in terms of December-to-January skewed effect from similar past periods (when 10 years worth of census bureau data gets dumped into and merged, all at once, with one month of BLS U3 statistical analysis; in this case, it appears that it does so deviate.
I hope I read & understood Robert's explanation correctly, and that I was able to at least roughly accurately answer the only question that can be fairly be asked at this point regarding the U3 report for January, to wit, whether it is statistically reliable (rather than whether it accurately reports absolute unemployment levels in the U.S. for the month of January in 2012, which it almost certainly does not).
Robert, please feel free to correct me or clean up any errors I've made in attempting to understand this and break it down.
Thanks
*This is TruthInSunshine, but the system wouldn't accept my response when I tried to use that moniker, so I abbreviated my name in order to get this posted
Thanks for that excellent & prompt response, Robert!
I have just registered on Economic Populist, but I see that you've already found the Zero Hedge article I referenced and that you've also already drilled down on the TrimTabs data that Charles Biderman compiled regarding January's BLS NFP report to identify even more curiosities.
I am trying to digest the TrimTabs data and what you extrapolated from it right now, but I do believe I have the basic gist.
You'd be a pure asset to the readership at Zero Hedge if you were to reproduce your essays and thoughts on this critical issue over there!
Thanks again,
TIS
Every one picks the statistic that suits him well.
The News and Media Industrie always picks the Hyped up one.
If it fails the have a reason to write a correction the next day.
The avarage Unemployment did not get better at all. It cant.
The hausing is still depressed, we have not enough production in the US itself , and there are on the same news page plenty of Job Layoff anauncments.
So like it or not it will take a long time to get better , so be carefull with your spending.
And if the gasprice goes up again the economy will nosedive again.
Because of a depressed income situation there is not enough liquidty to keep spending ,to fill the car is priority and the other stuff has to wait , results in a nosedive again , its always a delay from about 60 to 90
Days until people get the Creditcard outmaxed.
One mayor economy push would be a stable gasoline price, but with wild swings from 10 to 15 % this wont happen. In the moment the Gas price is up the economy breakes are on. One way to solve this would be a Pay increase but the wages are actually down and not up.
The minimum wage should be linked to the Gasoline price,because of the major impact gasoline has.
Chris Schmidt
Sorry, that's the official unemployment rate. U-6 is 15.1%, no much changed. If you want to calculate the real unemployment rate, read this post, What's the Real Unemployment Rate, and plug in the current numbers. In this new article overviewing some other data from January's employment report, I calculated 17%. That said, these estimates vary depending on assumptions and subgroups included. Point is to pay attention to the data and assumptions used. The real unemployment rate sure ain't 8.3%, not with record duration and people running out of benefits without a job and on and on.
Cut to the chase, what is the true number of unemployed people as a percentage of the workforce.
That's just for us, the regulars, but glad people like it cause I personally have to take a good laugh at this insanity at least once a week.
The civilian non-institutional population was adjusted by an additional 1.510 million. Do you think, magically, the population of the United States, with a total population of 312,959,348, and the non-institutional population being 242,269,000, could magically increased by 1.510 million, in addition to the monthly growth of 175,000?....in a month?
Think about it. There are basically about 3 million immigrants in a year, so no way in just 30 days you could have that kind of population increase. The monthly change in total U.S. population hovers around 200,000 a month. Maybe in China or India monthly population could increase by a million, after all each of those countries has 1.4, 1.6 billion people, but not the U.S. with our population levels. Not unless all women suddenly turned into Octomom.
Or would the size of the population that are not in the labor force, before these population controls and Census data was added, 86.697 million people, also increase by proportion via the 2010 Census adjustments?
The real question is of the adjustments, only 17.1% were entered as part of civilian labor force. *That* is the yet to be answered question, which at the bottom of this article, I say "stay tuned", for we're going to dig into that one further.
But I am clearly stating one cannot claim 1.2 million dropped out of the labor force because you're comparing apples and oranges.
You're comparing two completely different population base numbers upon which everything else is derived and that is not statistically valid.
Yes it's hard to wrap your head around but that doesn't make it B.S. Just because someone whips out a few numbers, graphs and even an equation at you, does not mean they are full of shit, although they might be full of calculator.
Could it be possible for you to explain(succinctly) why the number 1.2 mil dropping out of the workforce is inaccutate. Your description has the "flare" of dazzling with Bullshit
Ah, seasonal adjustments are another thing seemingly going a little nuts. We've seen the modeling "blow up" on housing data, and even the manufacturing ISM report. Some of this is blamed on the financial crisis. Basically they all use the same algorithm, X-12-ARIMA, which is an auto-regressive moving average algorithm.
Remember black swans and fat tails? Seems history now has the financial crisis in it's data points which is throwing the thing out of whack.
check this Trimlabs post out. This is really worth further exploration.
That said, check out these two graphs.
The first is the monthly difference between the seasonally adjusted payrolls data and the not seasonally adjusted one. As one would expect, we do see massive spikes in job growth as seasonal adjustments. The worst month is January and that's because people fire at the end of the year and don't hire like they do, esp. over the summer. Point of this is there is a clear cyclical pattern.
The next graph is annual of payrolls, seasonally adjusted for the year minus payrolls not seasonally adjusted. The difference should be zero. Notice how it's divergenging in 2009, 2010. Now it's not by much the data is in thousands, but it shows, at least to me primilary that the financial crisis did throw off the X-12-ARIMA algorithm. It should be zero theoretically for the year (or damn close).
Can you register here on EP and then link up to what you're talking about? I don't cross post, simply because EP keeps my more busy, I simply cannot keep up with everything. But I have delved into BLS data now for years and do have a mathematical/statistical background.
They do have real problems with modeling population adjustments. But I'm not sure which post you're referring to, this is the "Numerian" thread. I'll try to go check out TrimTabs report.
Seems one thing all have in common, we want better statistics, more drill down and larger surveys....so bottom line, keep the politicians out of the gov. statistical agencies (thank you Clinton, get your fingers out of that pie!) and give them more funding (and stop hiring H-1Bs, get some out of work Americans, Jesus!)
Robert,
I cited an excerpt of your outstanding essay over at zerohedge.com, in the comments section, and I hope that you do not mind.
If you care to have your essay published on Zero Hedge, please forward it to tips@zerohedge.com.
I am apolitical, and consider myself independent politically, but I do believe the BLS methodology for calculating U3 is extraordinarily flawed, for many of the reasons you cite so succinctly.
Thank you for taking the time and effort to write such an outstanding essay that highlights the flaws in the BLS methodology for measuring employment and the number of jobs gained or lost monthly.
p.s. - There is an article on Zero Hedge which essentially highlights why Charles Biderman of TrimTabs agrees with much of what you wrote, and for many of the identical reasons, titled 'TrimTabs Explains Why Today's "Very, Very Suspicious" NFP Number Is Really Down 2.9 Million In Past 2 Months.'
Thanks again for your contribution to this critical issue.
Partly of our own making by voting for Voodoo economics in 1980, 1984, 1988, 2000 and 2004. I was guilty in 88' because Dukakis freaked me out. I ranted about the debt from Reagan until the GWBush collapse. Now is not the time to take billions out of the economy hopefully soon but not now.
I wish the Republican candidates would receive closer scrutiny. Their "cures" for the economy are based on many, many unemployed as government spending collapses. How a whole political party can go insane is something we have not seen in my lifetime...maybe 1964? These people are truly scary.
Pages