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The BLS Jobs Report Covering December 2012: Good, Bad, Indifferently Bad, Take Your Pick

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By Hugh, who is a long-time commenter at Naked Capitalism. Originally published at Corrente.

The current BLS jobs report covering December 2012 states, without qualification, that the official or U-3 unemployment rate remained unchanged at 7.8%. It is only on page 5 of the pdf in a table that you find that the November rate was originally reported (a few days before the election) as a more favorable 7.7% down from 7.9%. This revision is part of the BLS’ yearly revision of its numbers in the Household (people) survey. This complicates matters because revisions to the Establishment (jobs) survey will not happen until next month. There is also the further wrinkle that in the February report covering January Household data will reflect updated estimates from the Census going forward but not backward, meaning that the Household data for January 2013 cannot be directly compared with data from December 2012 and before. The way the BLS stretches its yearly revisions out over 2-3 months means that about a quarter of the time, its reports have even more problems than they usually have.

I also had an interesting experience of déjà vu this month. I was watching NBC Nightly News last night and they had a preview of this month’s jobs report. I could have misheard and I have tried unsuccessfully to track down a transcript but I could have sworn I heard their business correspondent report offhandedly that experts thought this month’s jobs creation would be in line with last month’s 161,000. The problem with this is that the November jobs number cited by NBC is the revision for November in the December report. In other words, NBC I believe broke the embargo on the December report by some 14 hours and its prediction that this month’s report would be much like last month’s report wasn’t a prediction at all. As with many other news organizations, the BLS had passed NBC an advanced copy and the correspondent was just reading off from the report. This sloshing around of supposedly privileged information raises an important point. If you don’t think that Wall Street insiders don’t have access to this information ahead of time, I have a bridge in Brooklyn I would like to sell you. Only rubes, muppets, and bloggers like this one, have to wait for the public release.

Turning to the report, as I said, official unemployment was 7.8% (seasonally adjusted) and the economy added 155,000. The revisions in the jobs number for the last two months look like this:

October 171,000 > 138,000 > 137,000
November 146,000 > 161,000

The potential labor force as represented by the civilian non-institutional population over 16 (NIP) increased 176,000 from 244.174 million to 244.350 million. The employment-population ratio was 58.6%. If we multiply this by the NIP, we get 103,000, a rough estimate of the number of jobs needed to keep up with population growth. The official number of jobs created 155,000 beat this by 52,000. That would be a rate of 624,000 over population growth (beginning now) per year, but we are still 4.268 million below the jobs peak in November 2007. At that rate, it would take us 6.8 years to work through that backlog. At the same time, that 4.268 million jobs shortfall does not take into account that the November 2007 peak reflected several years of poor jobs growth during the Bush Administration. Nor does it take into account prior population growth.

In the Household data, the labor force increased 192,000 seasonally adjusted from 155.319 million to 155.511 million but declined unadjusted 49,000 from 145.953 million to 154.904 million.

The variance in the labor force numbers, adjusted and unadjusted, reflect deeper changes in the employment levels as the Christmas hires go away. Seasonally adjusted, employment increased 28,000 from 143.277 million to 143.305 million. Unadjusted, employment dropped 489,000 from 143.549 million to 143.060 million.

Again it is important to note that the seasonally adjusted numbers are reported in the media as the official numbers and treated as if they show where the economy is actually at. They do not. Seasonally adjusted numbers are normalized points on a line. This line takes out the lows and the highs, hopefully exposing the underlying trend. The underlying trend is not where we live. We live in the here and now with all its ups and downs. This is what the “unofficial” unadjusted numbers measure.

You can see some of this skewing in the adjusted numbers where both employment and unemployment increased. Seasonally adjusted, unemployment rose 164,000 from 12.042 million to 12.206 million. The unadjusted numbers are more consistent. Corresponding to the 489,000 decline in employment, we see unemployment increasing 440,000 from 11.404 million to 11.844 million.

While the BLS now reports unemployment, seasonally adjusted, remained unchanged in December at 7.8%. Unadjusted and reflecting the end of the Christmas shopping season, unemployment rose from 7.4% to 7.6%. And we should see another big jump in the unadjusted rate next month as the remaining Christmas hires are let go.

The participation rate is the ratio of the actual labor force (employed plus unemployed, as defined by the BLS) to the potential labor force, the NIP. Adjusted, it remained unchanged at 63.6%. Unadjusted, it decreased 0.1% to 63.4%.

In the broader U-6 measure of un- and under employment, or disemployment, seasonally adjusted, it was unchanged at 14.4%. Unadjusted, there was a 0.5% increase to 14.4%.

The seasonally adjusted U-6 un- and under employed represent 12.206 million U-3 unemployed (up 164,000 from November), 7.918 million involuntary part timers (down 220,000 from November), and 2.614 million marginally attached (those who have looked for work in the last year but not in the last 4 weeks before the survey) (up 109,000 from November).

The BLS has a restrictive, though internationally recognized, definition of unemployment: without a job but have looked for one in the last 4 weeks. The marginally attached are not counted as part of the labor force and their use in the U-6 is an indication that this is what the BLS considers its functional undercount to be.

The BLS also has a more extended category: Not in Labor Force, Want a Job Now (seasonally unadjusted). This was up 37,000 in December to 6.532 million and could also be taken as a measure of its undercount. The problem which I state each month at this point in my analysis is that this number does not reflect very well actual changes in the economy. So I have developed an alternative to it. In my alternate calculation, I compare the current labor force to where we would expect it to be in a solid economic expansion: labor participation rate of 67% (as boomers retire I may have to adjust this figure). The difference between these two is my measure of the undercount.

.67(244.350 million) = 163.715 million (where the labor force should be)
163.715 — 155.511 million = 8.204 million (the real undercount)

This is a decrease of 102,000 from the November number of 8.306 million. This is my estimate for the capture of the full undercount, those who do not have jobs but would work if jobs were available to them.

With this number we can now go back and calculate where the U-3 and U-6 really are, that is the real unemployment and real disemployment rates.

Real unemployment: 12.206 million (U-3 unemployment) + 8.204 million (undercount) = 20.410 million (up 75,000 from 20.335 million in November)

Real unemployment rate: 20.410 million / 163.715 million = 12.5% (up from 12.4% in November)

Real disemployment: Real unemployment + involuntary part time workers = 20.410 million + 7.918 million = 28.328 million (down 183,000 from 28.511 million in November)

Real disemployment rate: 28.328 million / 163.715 million = 17.3% (down 0.1% from November)

The long term unemployed, those without a job who have been looking for one for 6 months or more, changed little, decling 18,000 to 4.766 million.

By race, unemployment among whites increased slightly (0.1%) seasonally adjusted to 6.9%. African American unemployment which tends to be more volatile even seasonally adjusted increased 0.8% to 14.0%. White teen unemployment, seasonally adjusted, was 29.1%. African American teen unemployment was 40.5%.

______________________________________________________________

In the Establishment or business survey, the private sector created 168,000 jobs seasonally adjusted. Government lost 13,000, netting 155,000 for a total of 134.021 million jobs. Unadjusted, the number of jobs fell 243,000. This is a minor part of the fall off in jobs after Christmas. The really big part of this drop will occur next month, even as the seasonal numbers will likely show a healthy increase. Again seasonal numbers are part of a trend line. Unadjusted numbers are where you live.

Adjusted, healthcare added 44,500 jobs; food services and drinking places, 38,000; construction, 30,000; and manufacturing, 25,000. Part of the odd bubble in clothing store employment dissipated with a loss of 18,700 jobs. Education at the local level lost 11,500 jobs.

Unadjusted, healthcare added 57,400 jobs, food services and drinking places lost 14,000; construction lost 162,000; manufacturing gained 15,000. State government education lost 64,900; local government education lost 37,300; and local government excluding education lost 50,600 jobs.

The average work week for all employees increased 0.1 hour to 34.5 hours. Average hourly pay increased 7 cents to $23.73, and average weekly earnings increased $4.79 to $818.69.

The average work week for production and nonsupervisory (blue collar) employees also increased 0.1 hour 33.8 hours. Average hourly pay increased 6 cents to $19.92 and average weekly earnings increased $4.02 to $673.30.

These numbers would indicate that wages may have beaten inflation for the year by a few tenths of a percent. The December CPI will be out later this month.

Conclusion:

These end of the year reports with their various revisions tend to be something of a muddle. Additionally, we begin to get a significant separation between the adjusted and unadjusted numbers, that is between the trend and the reality. Adjusted, this looks like a reasonably solid report. Jobs are up if not brilliantly. Wages are up. However, many of the jobs “created” remain McJobs.

Unadjusted, the Christmas hiring season is over and the economy is shedding workers and jobs. There are also significant job losses at the state and local level.

On the macro level, real unemployment and real disemployment remain high and little changed.

I suppose you could look on this as three reports. Good, bad, and indifferent. Take your pick.

Household data (Employment/unemployment)
Statistical significance: +/ – 400,000
The A tables: http://www.bls.gov/cps/cpsatabs.htm
A 1 for most information and categories
A 2 Unemployment by race
A 8 Part time workers
A 12 Duration of unemployment
A 15 U 6 un- and under employment
A 16 Persons not in labor force

Establishment date (jobs)
Statistical significance: +/ – 100,000
The B tables: http://www.bls.gov/ces/cesbtabs.htm
B 1 Total jobs and jobs by industry/type
B 2 Weekly hours, all employees
B 3 Hourly and weekly earnings, all employees
B 6 Weekly hours, blue collar
B 7 Hourly and weekly earnings, blue collar

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27 comments

  1. Glen

    We would have more clarity on our current situation if valid comparisons of current unemployment could be made to historical Depression era unemployment numbers. I have seen a few of these comparisons (very few) and was not surprised to see that current measurements of unemployment are close (if not the same as) Depression era unemployment. It’s only the MSM lack of coverage of homeless families, and the exisitng safety net which makes our current depression effects much less viable.

    It’s interesting that the one commonly cited alternate unemployment measurement, Alternate Unemployment Charts Shadow Stats, shows unemployment as still rising rather than decreasing:

    http://www.shadowstats.com/alternate_data/unemployment-charts

    Probabaly a better indicator if the large number of people that have given up looking for employement and have become “invisable” to the offical numbers.

  2. run75441

    Hugh:

    Even though I think 67% is too high, it does makes sense as a measure:

    “have developed an alternative to it. In my alternate calculation, I compare the current labor force to where we would expect it to be in a solid economic expansion: labor participation rate of 67% (as boomers retire I may have to adjust this figure). The difference between these two is my measure of the undercount.”

    I got used to using 66.8% which was in Oct/Nov of 2001 as I always felt 67% occurred when the economy was super active. In any case, either is a measure of what the Civilian Labor Force should be today and how far we need to go to get there. Thoughts as to what year, you may pick to measure CLF with babyboomers retiring?

  3. Chris Engel

    No news here unfortunately.

    Nothing will change in the labor market until we get real inflation, real stimulus, and credible reductions in inequality.

    1. Capo Regime

      Thats the day monkeys will fly and rivers will flow with chocolate and rainbow fairies will grant your wishes for peace, equality, sustainability and of course fairness…..

  4. Riggsveda

    Hugh, I’ve always been confused by the BLS’s “average hourly pay” and “average weekly earnings” numbers. I’ve scoured the BLS site to try to figure out if they are really conflating the incomes of everyone in the country to get these averages, and can’t verify it. That’s certainly what using the term “average” would imply, but I just wanted confirmation. My concern is that trhowing the wage of CEOs and part-time fast food workers together heavily weights toward an increase because people at the top of the money food chain always get rises and people at the bottom seldom do. Just the amount given as the average hourly wage–$19.92–shows how heavily weighted by the top end numbers this appears to be. The Census showed a per capita median income in 2011 of $27,554, which, even at full employment 40 hours a week is only $13.25 hr. For HALF the population. And you know they aren’t all working at full employment.

    Wouldn’t it give a more accurate picture of the country’s economic progress to divide the averaged wages and earnings into quintiles, to avoid the over-weighting caused by hedge fund managers and billionaires?

    Anyway, I’d be interested to hear your response, and any corrections to this if I’m misinformed in some way. Thanks.

    1. diptherio

      Even better than quintiles, imho, is 5% increments, which actually allows you to start seeing the shape of the distribution. Even chunking into quintiles glosses over important differences, since it places my ‘rents, for instance, in the same category as Mitt Romney (the cut off for the top 1/5th is around $100,000/yr [household], last I saw).

      This income distribution chart, for example, is far more telling than the standard quintile view.

    2. Hugh

      I was bemused back before the election when charges were being thrown around that the jobs numbers were being politically manipulated. While there were some interesting coincidences, I thought it missed the point. The jobs reports are very political in how they are put together, what they look at, and how they look at it.

      I harp a lot on the official definition of unemployment and how this does not accord with people’s common sense definition of what unemployment is. So when they hear 7.8%, they think it means one thing when in fact it means something else entirely.

      The same with seasonality. I shake my head when reporters and pundits talk about the seasonally adjusted numbers, which are the “official” numbers as if they reflect what actually happened in the economy that month. The adjusted numbers could reflect a gain in jobs or workers in a month when the economy actually lost them. And then too we all treat these numbers as fairly precise when all of them have huge margins of error.

      Or there are the differences between the Household (workers) and Establishment (business/jobs) surveys. These survey somewhat different populations, but they should be much closely in agreement than they are. The Household survey has a margin of error of 400,000. The Establishment, 100,000. Even so, if the government is serious about collecting reliable data, it could increase the size of the Household data regularly. At the least, they could explore more why the two surveys are often so out of whack with each other and take steps to correct the discrepancies, but they never do.

      Then there is the wage data. The most common comment on it is the one you make that the hourly and weekly wages are a lot higher than fits with your personal experience. And yes, the reason is that a lot of higher paid people or higher paying professions are lumped together. And yes also, the average is often not the best measure of wages. The median is. If you have one guy who makes ten million a year and nine others who make ten thousand a year. The average will be just over one million, but the median will be ten thousand. I think politicians like averages for precisely this reason. It makes things look better than they are for most people.

      If you are interested in various breakdowns of wage data, you could start here:

      http://www.bls.gov/bls/blswage.htm

      or just go to the home page and under “subject areas”, look at the options for “pay and benefits”.

        1. jake chase

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          1. Hugh

            The trick is trying to tease out any useful information that might be contained in the numbers. What is measured and how it is measured often don’t address the questions we have. They are rather like the GDP. Nice number, but what kind of a society does it represent? How are we all faring? Why should any of us care what the GDP is?

            Part of what I do is simply to point out that there is a discrepancy between what is measured and what we out here think is being measured. Part is coming up with simple transformations to get some idea of the scope of the problem.

            And sometimes I fail. Even reworking the numbers does not convey the blight that has descended on all but a few. What faith can you put in calculations that equate a Warren Buffett job with that of a part timer making minimum wage or a “contract” worker making even less, neither earning a living wage? The incarcerated who work are not counted at all. Neither are those in uniform in the military. Illegals are supposedly not counted but there is no effort to control for them, one way or the other. All this raises questions. What does it mean to be employed if the only work you can find is a Mcjob? What does it mean to be unemployed if you are working hard each day whether as a parent, a caregiver, or a lowly blogger?

            And what about the sheer insanity of the waste? People are a society’s greatest resource. I used to shake my head at countries like Saudi Arabia that effectively wrote off half their population, the female half, right off the bat. But in this country, we are doing something even worse. Everyone not in the 1% is being written off. Nearly all of our society’s greatest resource is being trashed, made expendable, and thrown away.

            Finally, if we had a more equitable society. We would not need to store up riches to pass on to our children. Our society, that is we, would provide the building blocks for a good, fair, and decent life for them, not individually by inheritance but as a commitment that all make to all.

  5. Eureka Springs

    I think this article was recently posted in Links. Though I haven’t checked the math the sourced numbers are via the St. Louis Fed.

    Unemployment and Poverty in America:
    75 Economic Numbers From 2012 that are Almost too Crazy to Believe…
    http://www.informationclearinghouse.info/article33415.htm

    #9 In September 2009, during the depths of the last economic crisis, 58.7 percent of all working age Americans were employed. In November 2012, 58.7 percent of all working age Americans were employed. It is more then 3 years later, and we are in the exact same place.

    1. lambert strether

      It’s “the new normal.” Mission accomplished! Preparatory to decreased life expectancy (less prosaically, die back) a la the USSR, if you’re super-paranoid, by which I mean realistic.

  6. charles sereno

    Hugh:I always look forward to your employment reports and commend NC for making them available. I hope this gives you a chuckle. You say — “If you don’t think that Wall Street insiders don’t have access to this information ahead of time, I have a bridge in Brooklyn I would like to sell you.” I don’t know if you did a double negative purposely, but I for one appreciated it. Hell, Shakespeare did it too. Besides, it counters your sometime calvinistic preaching style (which I also appreciate). Again, thanks for your meticulous reports.
    Read more at http://www.nakedcapitalism.com/2013/01/the-bls-jobs-report-covering-december-2012-good-bad-indifferently-bad-take-your-pick.html#1gZ57P0HBcY22iwZ.99

  7. Daniel Kroner

    The jobs situation is only going to get worse and worse over time. The elephant in the room that everyone seems to be missing is that continued advancements in technology and automation are going to continue to exacerbate the problem. There is simply not enough work necessary to accommodate the number of workers any longer and this is only going to get worse as more and more industries fall prey to automation and further increases in productivity.

    I wrote more about this topic recently, my article can be found here: http://lofalexandria.blogspot.com/2011/09/where-are-all-jobs.html

    1. Hugh

      There are at least three points to consider. First, there are many professions, such as doctors, nurses, caregivers, teachers, lawyers, artists, musicians, politicians, etc. where improved technology may or may not improve the final product or service but will have little effect on increasing productivity. Second, you only have to go to the store of your choice and look at where its goods are produced to realize that offshoring has far more to do with US job losses than automation. It’s as easy, indeed probably easier, to run a machine here than in China. Third, there is the question of energy usage. If automation is more energy intensive than less automated alternatives, then in about 15-20 years it is going to cause us to hit the peak energy wall even harder.

      1. American Slave

        So the question is how many people are employed makeing robots

        http://www.kuka-ag.de/en/career/

        As you can see for the whole company including the programers there is only 6,000 people who work there and they are a huge automation company like Funac aswell, but what I dont get is is there any fking person who talks about jobs and robots who have a damn clue about what there talking about ive installed only PLC’s before but automation takes huge amounts of jobs away as ive seen first hand trust me and they dont eaven really program them much anymore they still use the lines of code they made in the 80′s they just change around the numbers a lil bit for the new models.

      2. diane

        Am I correct in understanding that you’re saying technology won’t be reducing the amount of those human professions you’ve named?

        If so, HUH?

        There are now med visits online, check out “nonprofit” UPMC (University of Pittsburgh’s Global “Medical” Monster), online pre-college schools, software bots which write sports articles, etcetera, etcetera etcetra, all with the intent to significantly reduce salaries, and insanely increase the: patient to doctor/nurse; student to instructor; reader to bot; etecetera, etcetera, etcetera ratios.

        Cloud Computing’s intent is to gut out billions of remaining ‘in house’ workers and have software, enormous databases, and overwhelmed, nonexperienced rare and few human inbetweens crunching figures (with no reasonable analysis) no matter how bogus those figures are.

        1. diane

          Honestly Hugh, I’ve loved much of what you’ve posted, but in your ‘post,’ you seem to be appearing as a still paid stoic … in the undisputed face of other humans thoroughly devastated vocations and loss of a means for a roof over the head.

        2. Hugh

          I am writing here as an analyst and chronicler. To understand and resolve the problems that confront us, neither quantification nor its rejection will get us where we need to go. If I was stoic about all this, I would not be writing. And as for being paid, as a blogger, that is one of the more humorous suggestions I have come across.

        3. diane

          I wasn’t referring to your being paid as a blogger – which I doubt any but a tiny handful can make a reasonable living at – it was a presumption perhaps wrong, that you were (outside of blogging) economically comfortable enough (i.e. not yet affected as so many have been) to have thoroughly missed the point that technology is in fact destroying more jobs than it’s creating, particularly cloud computing.

          I’m not clear at all what you mean by stating:

          … neither quantification nor its rejection will get us where we need to go.

          but what I took issue with was your comment (my boldfacing):

          First, there are many professions, such as doctors, nurses, caregivers, teachers, lawyers, artists, musicians, politicians, etc. where improved technology may or may not improve the final product or service but will have little effect on increasing productivity.

          Online professional services and instruction most certainly will, and most likely have, increased ‘productivity’ – with no concurrent increase in jobs (if not an actual reduction even), along with salary decreases – and, I would argue, to the detriment of both quality and intangible but crucial social benefits.

          It’s very difficult to find online arguments against cloud computing, which I believe is no accident given the powerful entities who have been unrelentingly pushing it, but I did manage to find this one from March 2012:

          Microsoft Makes Bogus Job Creation Claims – A Microsoft study claims cloud computing will create 14 million jobs worldwide by 2015. But it will destroy even more
          http://www.pcmag.com/article2/0,2817,2401151,00.asp

          … cloud computing is a consolidation technology that is used to fire IT staffs and centralize their efforts into a larger framework run by someone else, you have to assume at least 28 million jobs will be lost in the process.

          Unfortunately that author’s argument neglects to mention that it isn’t, and won’t be, just technicians losing jobs to cloud computing.

          1. Hugh

            This gets back to a criticism of the Marxian labor theory of value, that as their productivity rises the value of their labor should rise accordingly. This generally applies to classic manufacturing situations but not to others, such as those I mentioned. In K-12, a teacher can only effectively teach about 20-25 students. You can load the teacher and the classroom with all the technology you want. This will allow the teacher to teach different things in different ways, but it will not allow the teacher to teach larger numbers of students. As class size increases above 20-25, the quality of instruction will decrease regardless of the number of bells and whistles. In these occupations, productivity has built in limits. The classic example of this is the violinist. Playing a concerto twice as fast does not mean the violinist is being twice as productive.

            Cloud computing is just another in a lengthening list of reasonable sounding cons, like offshoring, automation, computerization, consolidation, etc. created in the name of efficiency but used essentially to loot. How many people with a problem are satisfied working through endless telephone or online menus and either not getting a human on the line at all or one in India? How many are happy about how media consolidation has limited their choices, the same crap but on a hundred different channels, or turned their local newspapers into a couple pages of stale news held together by a few ads? Efficiency, like productivity, like GDP, like job numbers, is not what it is cracked up to be. Efficiency as used nowadays is just a gimmick to improve short term profits so they can be looted. Real efficiency would actually improve our society. This is the reason that the social good component has been assiduously excised by the rich and elites from any discussion of economics and finance. It exposes their looting for what it is.

  8. tiebie66

    Hugh, is there any way to create an employment quality quotient (EQQ) that could account for both unemployment and the “McJobs” quality of employment?

    For example, the maximal potential income (appropriately normalized or referenced to some starting date) could be stated as:
    1900/12 person hours worked per month x $23.73/hour (suitable income reference to be used, here only for illustration the BLS Dec 2012 average used) x 330 million persons = $ 124 B in maximal earnings.
    Maximal potential Medicare income (MMI) from this at 1.45 % = $1.8 B for Dec. 2012. (Hopefully using the Medicare tax avoids skewing effects caused by income cutoffs.)

    Real Medicare income (RMI) for Dec. 2012 (I couldn’t find this, only a CBO estimate of $ 895 B for 2012 which implies roughly $ 8.1 B [from 1.45x895/{12x(6.2+4.2+1.45+1.45)}], thus ~4x more than possible given the other numbers…! :( ).
    Hence EQQ = RMI/MMI and should drop if unemployment increases and/or the remuneration rate decreases. This may provide further insight into the effectiveness of policy decisions.

    Though the details are undeniably pathetic, perhaps the gist of the argument has merit? (Or has already been tried and found wanting?) Prior comments about the median-average difference and the number of working age persons (e.g. 67% of 330 million) are also relevant here. Thus the use of medians may be advisable if they are available or could be estimated and one may have to adjust MMI for the fraction of the population of working age to control for demographic shifts.

    Regardless, your efforts are appreciated and the numbers seem much more credible than what is bandied about in the MSM.

  9. rjs

    re: the odd bubble in clothing store employment..

    November’s retail employment figures were inflated by a late reference week and an early thanksgiving (ie, BLS collected data closer to the holiday shopping season than normal), so this decrease in December retail jobs is likely just the unwinding of the aberrant November seasonal adjustment..

  10. caregiver

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