Paul Krugman in 2/6/12 article “America’s European Exposure” posits “it’s still very questionable whether Europe’s looming recession will actually have that much negative impact here” because “exports to Europe are just 2 percent of Europe.”
He seems to think manufacturing is the primary determinate of American wellbeing.
It seems to me that given the role of financial institutions (AKA Wall Street) in bringing on the recession, one should be analyzing what affects the EU will have on those type of institutions and in turn the overall economy.
For example, Credit Default Swaps. If Greece defaults what affect will that have on Banks that are obligated to reimburse to cover bondholder loses?
Apparently this statement must have been made at the press conference. There was also some reference to young teenage girls, or maybe it was unwed mothers, but the whole point being that these people whom they discovered existed from the new census wouldn't have made any difference to unemployment. They weren't in the labor force to begin with.
What we seem to have, then, is not so much 1.7 million people who've dropped out of the labor force all at once in January (or 1.2 million people if you use some other measure), but that number of people who existed all along and have to be added to the NILF totals all at once just because of a statistical revelation. I guess that's fine, but unless you put an asterisk on the chart, it still looks like a sharp drop in the labor participation pool occurred in January.
It reminds me of something which has always bugged me about the BLS, and that is the wording they use in their press release. This month was typical: the opening paragraph talks about how job creation in January was strong across the board, in business services, manufacturing, retail, hospitality, etc. Except it wasn't really. January lost 2 million + jobs, just like it always has in the past five or so years, as a result of the post-Christmas economic letdown.
The BLS could be more honest about the way it presents things. It could have said "hospitality (etc. etc.) fired fewer workers than would normally be expected," or "if we statistically compensated for the well-known post-Christmas economic letdown, employment picked up", or even "using seasonal adjustment factors, we estimate the economy created 243,000 jobs in January."
The fact that it does none of this but just blatantly mplies the economy is firing along creating all this employment is outright misleading. The press gobbles it up and the markets accept it as truth. The BLS could be accused of playing politics, but I suspect they are doing something different. I think they are playing the time-honored bureaucratic self preservation game. The BLS and the Labor Department know they have something valuable on their hands - the one piece of monthly economic data that everybody wants, that moves markets, and than can seal a president's fate at reelection time. They are hyping up the result because that sounds so much more important. The reality is more mundane, and why damage their franchise with reality? That would include letting people know that a small change in their assumptions about the labor pool could produce a radically different headline, political result, and market reaction.
This site is ours and this is where I write. The Economic Populist is a news source, so we're staying put. Being a news source has a slightly higher quality standard than a blog and because we are one, I take data extremely seriously to make sure what is written here is accurate.
On "old people were discovered" instead of dead, I'm wanting to get to some detailed analysis on Census data breakdown. I have to extrapolate this out of some databases and create some custom graphs, plus analyze it.
So, check back, maybe late this evening or tomorrow, that's in the works but it takes a lot time because I must get the raw data and number crunch.
On the seasonally adjusted issue, yeah, I think there is something there, it only takes 100k to be "off" and my main point is 243k payrolls just isn't an incredible miracle.
I honestly think the monthly BLS is too "statistically rough" to jump on monthly changes.
I read Zerohedge and sometimes he picks up on things that no one else sees, but I personally double check his data too. He caught a sudden increase, basically swaps to foreign banks, in the flow of funds report, which I do not think anyone else did...
This particular issue with the BLS has fooled major financial press, including the associated press thought.
You are correct, I believe, in that ZH mistakenly concluded that there was a fallout of 1.2 million people from the labor force in January, but on the other hand, ZH has rightfully raised some other suspect data in this latest NFP Report (as have you), indicating that there's at least the prospect of an existing larger-than-average anomaly in the January figures (given the 2010 Census Bureau affect) than December-to-January prior ones.
I tend to believe revisions and future BLS U-3 monthly reports will confirm this January data as very flawed, but only time will tell.
I really think you should start writing for some larger websites, since I'm of the opinion that your analysis on statistical reporting, and economics in general is quite excellent, and you were one of the only sources I could find to succinctly, apolitically and thoroughly break down how to accurately interpret the latest NFP Report.
I just want to end by saying that I found the following amusing (or maybe annoying is more an appropriate adjective), back on the subject of January's NFP Report:
"There was not a big increase in discouraged workers," economist Betsey Stevenson commented on Twitter. "What happened was Census found a bunch of old people we had assumed died." [The Wall Street Journal, 2/3/12]
Okay, so Betsey Stevenson (Betsey Stevenson, the chief economist at the Department of Labor, who works directly under the Secretary of Labor), is essentially saying a predominant majority of the people the 2010 Census 'discovered' were "old people [they] had [previously] assumed died."
You see, it's a "bunch of old people" that they discovered, who are presumably too old to be counted for purposes of measuring the unemployment rate, and therefore would not have affected the overall reported unemployment rate in any event....if her statement is to be taken at face value.
It is astounding and to this day nothing really is being done. It's like the Banks decided that people's homes were casino chips and something to do a catch-22 on, even if one fabricates a catch-22 on the fly, to take people's homes.
Not to diminish Mr. Lavelle's efforts under what must have been the more stressful circumstances, but this seems to happen in other areas.
Even when the law is one your side, few have money to pursue legal action. Even when you have the law on your side and the anger, money to do something, the judge ignores the law. I'm thinking of other civil cases, from ripping off contractors, consultants to pretty much any civil suit where the funds being screwed over on are less than $500,000.
Even when one has a mufti-million dollar lawsuit, it will be buried in litigation, delays and no justice for years. Then, even if you win, trying to collect the judgment is almost impossible.
The story surfaced this morning in Gretchen Morgensen's column in the NY Times. Mr. Lavalle became involved in trying to save his family's home in a suburb of Detroit in the 1990s. Despite the fact that the family was wealthy and paying its mortgage on time, the note holder, EMC, kept insisting it was behind on payments and foreclosed anyway. The Lavalle family sued but the judged ruled for EMC, apparently because a bank wouldn't lie about such things.
An incensed Mr. Lavalle then spent most of his spare time and $500,000 of his own money investigating the mortgage broker industry, Fannie Mae and Freddie Mac, the bank servicers, the securitization process, MERS, and the foreclosure process. What he found horrified him: routine errors in mortgage documents, banks submitting falsified statements regarding their foreclosure rights, notes missing or suddenly showing up after the bank told the court they were missing, notes held by banks that should have been marked cancelled and returned to the homeowner, but were instead kept in bank files and exposing the homeowner to a foreclosure even though they paid off the mortgage.
In 2003 Mr. Lavalle packaged his findings together and sent them off to Fannie Mae and its board of directors, showing them how they could be liable to hundreds of billions of dollars of lawsuits for failure to police itself, brokers, servicers, and the banks. Fannie Mae's board hired a law firm to study the matter, and the resulting 147 page report is what has been unearthed or given to Gretschen Morgensen. The report confirms much of what Mr. Lavalle exposes, but it argues in some cases that Fannie Mae need do nothing. For example, the law firm believed homeowners did not have the legal right to know which bank now owned their mortgage and note, because securitization made that impossible. In other cases, the law firm said that Mr. Lavalle was correct - for example that MERS did not have legal standing to file foreclosures in many states, even though it claimed it did and was filing foreclosures anyway. The law firm pointed out that case history through the courts left this matter very unsettled.
What we have now is the smoking gun of all smoking guns. Mr. Lavalle's work was also sent to the big bank servicers, and nothing was done by them to stop what he described as fraudulent behavior. Fannie Mae is now owned by the federal government, so it will be difficult to sue them for what they knew but did nothing to correct. But the banks? That's another story. The problems that Mr. Lavalle predicted have all come to pass, but the banks ignored his warnings. He was one lonely voice out there, showing how corrupt and unstable the mortgage system was in the US, but to do anything about it would disrupt the enormous revenue stream the banks were reaping from the system.
Lawyers now have yet another substantial piece of evidence that shows systemic failure to correct illegalities and flaws in the mortgage business.
Over on the right hand column are mainly government and private reports (that are used by governments) overviews. I started doing these overviews because so many in the MSM plain get them wrong or didn't explain much. Be nice to know if I'm successful in translating them to English for people to understand. Yeah, I'd say once one goes into seasonal adjustment algorithms, it helps to have a statistics course or 5, no doubt about it.
Yes this is a big help. I can't say I fully understand it, but obvious this is a specialized field which one needs training. Most important lesson is that the MSM commentators are clearly 'blowing smoke" when they give their so called 'analysis'.
I think also, I kind of did a hack to show if the seasonal adjustments are off and there does seem to be a magic pattern now that January posts "high" payrolls, that wee little bit can overstate payrolls.
That's what I was referring to in this comment here, where I made those difference graphs on seasonal adjustments, payrolls.
First, the charts are not population, but non-institutional civilian population. This is the biggest super-set from where all unemployment statistics are derived. So, that excludes kids, people in the military, people in prison (right, let's ignore prison labor via private prisons), people in hospitals, mental institutions, nursing homes.
Ok, so those huge "upward" spikes are the Census adjustments. It helps to look at the bottom of the graph where the dates are. You can see those three upward "spikes" correlating to the 10 years when the new Census (taken every 10 years) is incorporated into the non-institutional civilian population numbers.
That said, if the Census had shown there were less people in the country than 2000, those spikes could have been the opposite, downward, meaning the U.S. non-institutional population would have shrank.
It did not of course, the U.S. population and non-institutional civilian population has grown since 2000.
Then, those "downward" spikes, are primarily the yearly, or end of year population adjustments. This is done annually. What happens is non-institutional civilian population comes off of the base Census survey. Then, there are additional real world survey data, plus statistical algorithms, to project how much non-institutional civilian population will increase each month.
You have the 10 year Census, then the "interyear" or yearly Census quality controls to population growth estimates. Every year the Census looks at a bunch of stuff, i.e. birth records, death records, inter-state migration, out of the country migration, immigration (now you see why it can be so wrong!), ex-pats and a bunch of other stuff. Then the annual growth of the population and also the "age bracket" groups of population are adjusted.
Once a year the "miss" or error between the projections and the real world data are updated and it's plopped into the January data.
That's what I mean about a year of cumulative error being dumped into just one month's worth of data. This is also why one cannot compare December-January monthly change. You've got a year's worth of cumulative error corrections being added to January.
You might also look at those "downward spikes", which could just as easily be "upward"
as the BLS hitting the "reset button".
It's like to resets the rate of growth of the non-institutional population to real worth current rates.
So basically the Census is the base number from where everything "starts" and then statistical algorithms give the monthly increases for each month, plus there is real world data that comes in which adjusts the statistical algorithm to what's really happening.
This month got a double whammy, the 2010 Census was added plus those yearly adjustments.
If N is non-institutional civilian population and is the monthly growth in non-institutional population and C is the base census, then is the current non-institutional population and is adjusted by the Census bureau through the quality controls annually, i.e. those population control adjustments happen once a year and those are the discontinuities or "downward spikes" in the above graphs.
Every 10 years:
Every month:
Every year the growth of population is adjusted by quality controls and statistical agorithms:
The civilian non-institutional population is not seasonally adjusted.
Then, as if that's not enough adjustments, there is also a seasonal adjustment algorithm. It's basically X-12-ARIMA but also has to be "recalibrated" using a years worth of data which is one of the reasons you see this "plop" in one month.
But bottom line this wild spikes, up or down are the yearly population controls. They represent a year's worth of error and change, plopped into the January data as a do over.
Whew! I hope that helps, without starting to whip out the real mathematics (up there is just a little concept), I'm running out of words and images, concepts to explain this, although I think a flash video could really help.
I suggest playing around with FRED too, the St. Louis graphing system which is where I made the above graphs. The changing visuals might help with the concept.
I’m afraid to ask this because you may have answered it; but this stuff is really thick for me.
I think I understand that the UP “Spicks” are population INCREASES for the year “plopped” into the database in January. But, I don’t understand is the meaning of the DOWN “spikes” in the “Civilian Noninstitutional Population."
He still (sorry) I don't think is getting it on the "not in the labor force" spike out, but on the seasonal adjustments to nonfarm payrolls, that's where the above two graphs do come into play. Just a "little bit" off on the seasonal adjustment, which now has the financial crisis, "great recession" data in it's algorithmic history here, but regardless, a "wee bit off" and bam, you've got over-inflated jobs numbers. The above is showing a "wee bit off" or an introduced bias and this is what I'm referring to with those wild ride outlinear historical numbers and rambling on about black swans and long tails. Auto-regression, moving averages will be skewed with enough "outlinear" data points.
But another point is 100k on payrolls is within the margin of error just on the survey alone, so why Wall Street goes nuts and think all is well over 243k jobs tells us they don't get proportion to save their souls! They are so used to crappy payrolls reports that when one pops up that's more in the normal range they think that's a miracle. Gez, a 400k payrolls change is a miracle, not one 200-300k range.
Anywho, I might go write up some stuff and enter the conspiracy universe of the birth/death model since so many seem to be debating BLS methods and numbers. Go digging around in some other statistics.
That said, I stand by the need for more "drill down" data at the BLS, more funding, much larger surveys and probably another one to mention is actual raw data collection. Some of this comes from the states (payrolls, birth/death) and they all must be using paper and pencil and dropping forms on the floor. That entire reporting process to me should be modernized, tightened up.
Your voodoo economics comment is entireley about taxes and doesn't consider the growth in spending during that period. The 1992 and 1996 periods had a low growth in spending (and a dot-com boom that collapsed as GWBush took office). But overall growth in the economy would have taken care of the deficits if spending hadn't far exceeded inflation-adjusted growth. And, no, the wars don't make up the difference.
I know it's popular to blame a bunch of geeky economists and statisticians sitting inside the BLS, but the one's to blame are the politicians and Congress. They control sometimes the definitions and they control the funding to the BLS, which is under the U.S. department of Labor. Nuf said the actual department of labor has been turned into a political hack spot, but the BLS itself is just statistics and numbers. I think you can also blame the Census, but that too, runs into Congress.
I'm saying that the survey sizes need to be expanded to a larger sample set. They need to incorporate social and online surveys, similar to how one makes a purchase via a credit card online so they know it's "you" to get more drilled down raw data.
On population controls, I'm sorry but they really need something beyond a decade survey with hardly any questions on it. A hotly charged topic is immigration status, and I'm sorry but in this day and age of guest workers and illegal immigration, globalization, we need that data. The Demographics used are from the 1960's in my opinion. They need better resolution by occupational categories. They need to capture the under employed.
The USCIS needs to track who is here doing what on various work Visas and other Visas....
They need to breakdown on the payrolls data part-time jobs by hours against full time ones.
But a general "the government is lying to us" just isn't true. This is more a problem of large aggregate statistics, methods and definitions, not some conspiracy.
Absolutely the unemployment rate is higher than the official, but it's always been that way at least since 1996, so by ratios it's still a useful statistic, just gotta know what you're looking at.
Spinning with numbers is so common, it's a sad day when people believe some geeky group like the BLS are doing it on purpose. Nope, it's just math. It's advanced statistics, methods and raw data points, collection methods...
now forcing those can be political. Bottom line this is why Americans need to understand mathematics, statistics. You have to read every number to really separate out the wheat from the shaft here.
Paul Krugman in 2/6/12 article “America’s European Exposure” posits “it’s still very questionable whether Europe’s looming recession will actually have that much negative impact here” because “exports to Europe are just 2 percent of Europe.”
He seems to think manufacturing is the primary determinate of American wellbeing.
It seems to me that given the role of financial institutions (AKA Wall Street) in bringing on the recession, one should be analyzing what affects the EU will have on those type of institutions and in turn the overall economy.
For example, Credit Default Swaps. If Greece defaults what affect will that have on Banks that are obligated to reimburse to cover bondholder loses?
I had someone email people (please people, leave comments instead), asking for the actual report. I found this online at this link.
Apparently this statement must have been made at the press conference. There was also some reference to young teenage girls, or maybe it was unwed mothers, but the whole point being that these people whom they discovered existed from the new census wouldn't have made any difference to unemployment. They weren't in the labor force to begin with.
What we seem to have, then, is not so much 1.7 million people who've dropped out of the labor force all at once in January (or 1.2 million people if you use some other measure), but that number of people who existed all along and have to be added to the NILF totals all at once just because of a statistical revelation. I guess that's fine, but unless you put an asterisk on the chart, it still looks like a sharp drop in the labor participation pool occurred in January.
It reminds me of something which has always bugged me about the BLS, and that is the wording they use in their press release. This month was typical: the opening paragraph talks about how job creation in January was strong across the board, in business services, manufacturing, retail, hospitality, etc. Except it wasn't really. January lost 2 million + jobs, just like it always has in the past five or so years, as a result of the post-Christmas economic letdown.
The BLS could be more honest about the way it presents things. It could have said "hospitality (etc. etc.) fired fewer workers than would normally be expected," or "if we statistically compensated for the well-known post-Christmas economic letdown, employment picked up", or even "using seasonal adjustment factors, we estimate the economy created 243,000 jobs in January."
The fact that it does none of this but just blatantly mplies the economy is firing along creating all this employment is outright misleading. The press gobbles it up and the markets accept it as truth. The BLS could be accused of playing politics, but I suspect they are doing something different. I think they are playing the time-honored bureaucratic self preservation game. The BLS and the Labor Department know they have something valuable on their hands - the one piece of monthly economic data that everybody wants, that moves markets, and than can seal a president's fate at reelection time. They are hyping up the result because that sounds so much more important. The reality is more mundane, and why damage their franchise with reality? That would include letting people know that a small change in their assumptions about the labor pool could produce a radically different headline, political result, and market reaction.
This site is ours and this is where I write. The Economic Populist is a news source, so we're staying put. Being a news source has a slightly higher quality standard than a blog and because we are one, I take data extremely seriously to make sure what is written here is accurate.
On "old people were discovered" instead of dead, I'm wanting to get to some detailed analysis on Census data breakdown. I have to extrapolate this out of some databases and create some custom graphs, plus analyze it.
So, check back, maybe late this evening or tomorrow, that's in the works but it takes a lot time because I must get the raw data and number crunch.
On the seasonally adjusted issue, yeah, I think there is something there, it only takes 100k to be "off" and my main point is 243k payrolls just isn't an incredible miracle.
I honestly think the monthly BLS is too "statistically rough" to jump on monthly changes.
I read Zerohedge and sometimes he picks up on things that no one else sees, but I personally double check his data too. He caught a sudden increase, basically swaps to foreign banks, in the flow of funds report, which I do not think anyone else did...
This particular issue with the BLS has fooled major financial press, including the associated press thought.
Robert,
You are correct, I believe, in that ZH mistakenly concluded that there was a fallout of 1.2 million people from the labor force in January, but on the other hand, ZH has rightfully raised some other suspect data in this latest NFP Report (as have you), indicating that there's at least the prospect of an existing larger-than-average anomaly in the January figures (given the 2010 Census Bureau affect) than December-to-January prior ones.
I tend to believe revisions and future BLS U-3 monthly reports will confirm this January data as very flawed, but only time will tell.
I really think you should start writing for some larger websites, since I'm of the opinion that your analysis on statistical reporting, and economics in general is quite excellent, and you were one of the only sources I could find to succinctly, apolitically and thoroughly break down how to accurately interpret the latest NFP Report.
I just want to end by saying that I found the following amusing (or maybe annoying is more an appropriate adjective), back on the subject of January's NFP Report:
"There was not a big increase in discouraged workers," economist Betsey Stevenson commented on Twitter. "What happened was Census found a bunch of old people we had assumed died." [The Wall Street Journal, 2/3/12]
http://blogs.wsj.com/economics/2012/02/03/whats-behind-the-unemployment-...
Okay, so Betsey Stevenson (Betsey Stevenson, the chief economist at the Department of Labor, who works directly under the Secretary of Labor), is essentially saying a predominant majority of the people the 2010 Census 'discovered' were "old people [they] had [previously] assumed died."
You see, it's a "bunch of old people" that they discovered, who are presumably too old to be counted for purposes of measuring the unemployment rate, and therefore would not have affected the overall reported unemployment rate in any event....if her statement is to be taken at face value.
Or maybe I'm reading too much into this?
Thanks again.
TIS
I updated this article with Naked Capitalism pointing out both of these recent developments are stealth bank bail outs in disguise.
Here is NC's original post.
Naked Capitalism is a great watchdog resource for what's going on here, but hoodwinking seems to be the state of play. Lovely.
It is astounding and to this day nothing really is being done. It's like the Banks decided that people's homes were casino chips and something to do a catch-22 on, even if one fabricates a catch-22 on the fly, to take people's homes.
Not to diminish Mr. Lavelle's efforts under what must have been the more stressful circumstances, but this seems to happen in other areas.
Even when the law is one your side, few have money to pursue legal action. Even when you have the law on your side and the anger, money to do something, the judge ignores the law. I'm thinking of other civil cases, from ripping off contractors, consultants to pretty much any civil suit where the funds being screwed over on are less than $500,000.
Even when one has a mufti-million dollar lawsuit, it will be buried in litigation, delays and no justice for years. Then, even if you win, trying to collect the judgment is almost impossible.
The story surfaced this morning in Gretchen Morgensen's column in the NY Times. Mr. Lavalle became involved in trying to save his family's home in a suburb of Detroit in the 1990s. Despite the fact that the family was wealthy and paying its mortgage on time, the note holder, EMC, kept insisting it was behind on payments and foreclosed anyway. The Lavalle family sued but the judged ruled for EMC, apparently because a bank wouldn't lie about such things.
An incensed Mr. Lavalle then spent most of his spare time and $500,000 of his own money investigating the mortgage broker industry, Fannie Mae and Freddie Mac, the bank servicers, the securitization process, MERS, and the foreclosure process. What he found horrified him: routine errors in mortgage documents, banks submitting falsified statements regarding their foreclosure rights, notes missing or suddenly showing up after the bank told the court they were missing, notes held by banks that should have been marked cancelled and returned to the homeowner, but were instead kept in bank files and exposing the homeowner to a foreclosure even though they paid off the mortgage.
In 2003 Mr. Lavalle packaged his findings together and sent them off to Fannie Mae and its board of directors, showing them how they could be liable to hundreds of billions of dollars of lawsuits for failure to police itself, brokers, servicers, and the banks. Fannie Mae's board hired a law firm to study the matter, and the resulting 147 page report is what has been unearthed or given to Gretschen Morgensen. The report confirms much of what Mr. Lavalle exposes, but it argues in some cases that Fannie Mae need do nothing. For example, the law firm believed homeowners did not have the legal right to know which bank now owned their mortgage and note, because securitization made that impossible. In other cases, the law firm said that Mr. Lavalle was correct - for example that MERS did not have legal standing to file foreclosures in many states, even though it claimed it did and was filing foreclosures anyway. The law firm pointed out that case history through the courts left this matter very unsettled.
What we have now is the smoking gun of all smoking guns. Mr. Lavalle's work was also sent to the big bank servicers, and nothing was done by them to stop what he described as fraudulent behavior. Fannie Mae is now owned by the federal government, so it will be difficult to sue them for what they knew but did nothing to correct. But the banks? That's another story. The problems that Mr. Lavalle predicted have all come to pass, but the banks ignored his warnings. He was one lonely voice out there, showing how corrupt and unstable the mortgage system was in the US, but to do anything about it would disrupt the enormous revenue stream the banks were reaping from the system.
Lawyers now have yet another substantial piece of evidence that shows systemic failure to correct illegalities and flaws in the mortgage business.
You're delusional!
You're delusional!
You're delusional!
Over on the right hand column are mainly government and private reports (that are used by governments) overviews. I started doing these overviews because so many in the MSM plain get them wrong or didn't explain much. Be nice to know if I'm successful in translating them to English for people to understand. Yeah, I'd say once one goes into seasonal adjustment algorithms, it helps to have a statistics course or 5, no doubt about it.
Yes this is a big help. I can't say I fully understand it, but obvious this is a specialized field which one needs training. Most important lesson is that the MSM commentators are clearly 'blowing smoke" when they give their so called 'analysis'.
thanks again. This site is a gem!
Tom
Excellent write up. Poked holes in all the mainstream press of how 'great' things are suddenly going. Kudos.
I think also, I kind of did a hack to show if the seasonal adjustments are off and there does seem to be a magic pattern now that January posts "high" payrolls, that wee little bit can overstate payrolls.
That's what I was referring to in this comment here, where I made those difference graphs on seasonal adjustments, payrolls.
First, the charts are not population, but non-institutional civilian population. This is the biggest super-set from where all unemployment statistics are derived. So, that excludes kids, people in the military, people in prison (right, let's ignore prison labor via private prisons), people in hospitals, mental institutions, nursing homes.
Ok, so those huge "upward" spikes are the Census adjustments. It helps to look at the bottom of the graph where the dates are. You can see those three upward "spikes" correlating to the 10 years when the new Census (taken every 10 years) is incorporated into the non-institutional civilian population numbers.
That said, if the Census had shown there were less people in the country than 2000, those spikes could have been the opposite, downward, meaning the U.S. non-institutional population would have shrank.
It did not of course, the U.S. population and non-institutional civilian population has grown since 2000.
Then, those "downward" spikes, are primarily the yearly, or end of year population adjustments. This is done annually. What happens is non-institutional civilian population comes off of the base Census survey. Then, there are additional real world survey data, plus statistical algorithms, to project how much non-institutional civilian population will increase each month.
You have the 10 year Census, then the "interyear" or yearly Census quality controls to population growth estimates. Every year the Census looks at a bunch of stuff, i.e. birth records, death records, inter-state migration, out of the country migration, immigration (now you see why it can be so wrong!), ex-pats and a bunch of other stuff. Then the annual growth of the population and also the "age bracket" groups of population are adjusted.
Once a year the "miss" or error between the projections and the real world data are updated and it's plopped into the January data.
That's what I mean about a year of cumulative error being dumped into just one month's worth of data. This is also why one cannot compare December-January monthly change. You've got a year's worth of cumulative error corrections being added to January.
You might also look at those "downward spikes", which could just as easily be "upward"
as the BLS hitting the "reset button".
It's like to resets the rate of growth of the non-institutional population to real worth current rates.
So basically the Census is the base number from where everything "starts" and then statistical algorithms give the monthly increases for each month, plus there is real world data that comes in which adjusts the statistical algorithm to what's really happening.
This month got a double whammy, the 2010 Census was added plus those yearly adjustments.
If N is non-institutional civilian population and
is the monthly growth in non-institutional population and C is the base census, then 
is the current non-institutional population and is adjusted by the Census bureau through the quality controls annually, i.e. those population control adjustments happen once a year and those are the discontinuities or "downward spikes" in the above graphs.
Every 10 years:
Every month:
Every year the growth of population is adjusted by quality controls and statistical agorithms:
The civilian non-institutional population is not seasonally adjusted.
Then, as if that's not enough adjustments, there is also a seasonal adjustment algorithm. It's basically X-12-ARIMA but also has to be "recalibrated" using a years worth of data which is one of the reasons you see this "plop" in one month.
But bottom line this wild spikes, up or down are the yearly population controls. They represent a year's worth of error and change, plopped into the January data as a do over.
Whew! I hope that helps, without starting to whip out the real mathematics (up there is just a little concept), I'm running out of words and images, concepts to explain this, although I think a flash video could really help.
I suggest playing around with FRED too, the St. Louis graphing system which is where I made the above graphs. The changing visuals might help with the concept.
I’m afraid to ask this because you may have answered it; but this stuff is really thick for me.
I think I understand that the UP “Spicks” are population INCREASES for the year “plopped” into the database in January. But, I don’t understand is the meaning of the DOWN “spikes” in the “Civilian Noninstitutional Population."
Thanks for great analysis
Tom
He still (sorry) I don't think is getting it on the "not in the labor force" spike out, but on the seasonal adjustments to nonfarm payrolls, that's where the above two graphs do come into play. Just a "little bit" off on the seasonal adjustment, which now has the financial crisis, "great recession" data in it's algorithmic history here, but regardless, a "wee bit off" and bam, you've got over-inflated jobs numbers. The above is showing a "wee bit off" or an introduced bias and this is what I'm referring to with those wild ride outlinear historical numbers and rambling on about black swans and long tails. Auto-regression, moving averages will be skewed with enough "outlinear" data points.
But another point is 100k on payrolls is within the margin of error just on the survey alone, so why Wall Street goes nuts and think all is well over 243k jobs tells us they don't get proportion to save their souls! They are so used to crappy payrolls reports that when one pops up that's more in the normal range they think that's a miracle. Gez, a 400k payrolls change is a miracle, not one 200-300k range.
Anywho, I might go write up some stuff and enter the conspiracy universe of the birth/death model since so many seem to be debating BLS methods and numbers. Go digging around in some other statistics.
That said, I stand by the need for more "drill down" data at the BLS, more funding, much larger surveys and probably another one to mention is actual raw data collection. Some of this comes from the states (payrolls, birth/death) and they all must be using paper and pencil and dropping forms on the floor. That entire reporting process to me should be modernized, tightened up.
Your voodoo economics comment is entireley about taxes and doesn't consider the growth in spending during that period. The 1992 and 1996 periods had a low growth in spending (and a dot-com boom that collapsed as GWBush took office). But overall growth in the economy would have taken care of the deficits if spending hadn't far exceeded inflation-adjusted growth. And, no, the wars don't make up the difference.
I know it's popular to blame a bunch of geeky economists and statisticians sitting inside the BLS, but the one's to blame are the politicians and Congress. They control sometimes the definitions and they control the funding to the BLS, which is under the U.S. department of Labor. Nuf said the actual department of labor has been turned into a political hack spot, but the BLS itself is just statistics and numbers. I think you can also blame the Census, but that too, runs into Congress.
I'm saying that the survey sizes need to be expanded to a larger sample set. They need to incorporate social and online surveys, similar to how one makes a purchase via a credit card online so they know it's "you" to get more drilled down raw data.
On population controls, I'm sorry but they really need something beyond a decade survey with hardly any questions on it. A hotly charged topic is immigration status, and I'm sorry but in this day and age of guest workers and illegal immigration, globalization, we need that data. The Demographics used are from the 1960's in my opinion. They need better resolution by occupational categories. They need to capture the under employed.
The USCIS needs to track who is here doing what on various work Visas and other Visas....
They need to breakdown on the payrolls data part-time jobs by hours against full time ones.
But a general "the government is lying to us" just isn't true. This is more a problem of large aggregate statistics, methods and definitions, not some conspiracy.
Absolutely the unemployment rate is higher than the official, but it's always been that way at least since 1996, so by ratios it's still a useful statistic, just gotta know what you're looking at.
Spinning with numbers is so common, it's a sad day when people believe some geeky group like the BLS are doing it on purpose. Nope, it's just math. It's advanced statistics, methods and raw data points, collection methods...
now forcing those can be political. Bottom line this is why Americans need to understand mathematics, statistics. You have to read every number to really separate out the wheat from the shaft here.
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