Again a Good BLS Jobs Situation in June 2013

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The June 2013 BLS jobs report was above expectations.

  • the unadjusted non-farm private jobs gain comparing the changes between Mays and Junes was better than last year – and is about average for gains in 10 years when the economy was not in a recession.
  • economic intuitive sectors of employment were mixed.
  • This month’s report internals are relatively more inconsistent between the survey portion and the establishment portion. There were some positive trends beginning, but not reflected in both portions.

A summary of the employment situation:

  • BLS reported: 195K (non-farm) and 202K (non-farm private). Unemployment = 7.6% (unchanged)
  • ADP reported: 188K (non-farm private)
  • Market expected: 166K to 175K (non-farm), 180K to 190K (non-farm private), 7.6% unemployment
  • Econintersect‘s Forecast: 145K (non-farm private) based on economic potential
  • The NFIB released a statement (below) saying that small business employment growth not good in June 2013.

The BLS reports seasonally adjusted data. This data is highly manipulated, and Econintersect believes the unadjusted data gives a clearer picture of the jobs situation.

Non-seasonally adjusted non-farm payrolls rose 856,000 – better than last year, but 4 years showed better jobs growth in the last 10 years.

Historical Unadjusted Private Non-Farm Jobs Growth Between Mays and Aprils (Table B-1, data in thousands) – unadjusted (blue line) vs seasonally adjusted (red line)

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As always, the recent past data was revised.

Change in Seasonally Adjusted Non-Farm Payrolls Between Originally Reported (blue bars) and Current Estimates (red bars)

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Most of the analysis below uses unadjusted data, and presents an alternative view to the headline data.


The BLS reported U-3 (headline) unemployment was unchanged at 7.6% with the U-6 “all in” unemployment rate (including those working part time who want a full time job) jumped 0.5% to 14.5%.

BLS U-3 Headline Unemployment (red line, left axis), U-6 All In Unemployment (blue line, left axis), and Median Duration of Unemployment (green line, right axis)

Econintersect has an interpretation of employment supply slack using the BLS unadjusted data base, demonstrated by the graph below.

Employment-Population Ratio

The jobs picture when you view the population as a whole. and with this months data it appears there has been little change in the jobs situation since the end of the recession.

  • Econintersect uses employment-populations ratios to monitor the jobless situation.  The headline unemployment number requires the BLS to guess at the size of the workforce, then guess again who is employed or not employed. In employment – population ratios, the population is a given and the guess is who is employed.
  • In the latest BLS report employment-population ratio rose 0.1 to 58.7 – this ratio had been jumping back and forth between 58.5 and 58.6 for 5 months. The employment-population ratio tells you the percent of the population with a job. Each 0.1% increment represents approximately 300,000 jobs. [Note: these are seasonally adjusted numbers – and we are relying on the BLS to get this seasonal adjustment factor correct]. An unchanged ratio would be telling you that jobs growth was around 150,000 – as this is approximately the new entries to the labor market caused by population growth.

Employment Metrics

The 3 year growth trend is up, and the short term trends are mixed depending on the periods selected – however, it seems the growth trend in the last 18 months is relatively flat.

Unadjusted Non-Farm Payrolls Year-over-Year Growth

Another way to view employment is to watch the total hours worked which has been been growing at a slower and slower rate since the middle of 2010.

Percent Change Year-over-Year Non-Farm Private Weekly Hours Worked

The bullets below use seasonally adjusted data:

  • Average hours worked (table B-2) was unchanged at 34.5. A falling number does not indicate an expanding economy . This number has been in a narrow channel several months.
  • Government employment contracted 7,000 with the Federal Government down 7,000, state governments down 15,000 and local governments up 13,000.
  • The big contributor to employment growth this month was accommodation and food (57K), retail trade (37K) and administrative including temp services (36K).
  • The big headwinds this month was the state government (-13K) and education (-11K)
  • Manufacturing was down 6,000, while construction was up 13,000.
  • The unemployment rate for people between 20 and 24 (Table A-10) degraded from 13.2% to 13.5%. This number is produced by survey and is very volatile – and this month’s degradation only reversed last month’s improvement.
  • Average hourly earnings (Table B-3) rose ten cents to $24.01.

Private Employment: Average Hourly Earnings

Economic Metrics

Economic markers used to benchmark economic growth were mixed, but well away from recessionary levels.

The truck employment declined (3.5K). However, the year-over-year improvement is well into expansion territory, although it has a declining growth trend line.

Truck Transport Employment – Year-over-Year Change

Temporary help increased (9.5K). Note that many believe (I am not convinced), that Obamacare is creating a shift from permanent to temporary jobs. If this is the case, this metric would be inoperative.

Temporary Help Employment – Year-over-Year Change

Econintersect believes the transport sector is a forward indicator. Others look at temporary help as a forward indicator.

Food for Thought

Who is the victims in this mediocre employment situation. It is not people over 55.

Index of Employment Levels – 55 and up (dark grey line), 45 to 54 (purple line), 35 to 44 (orange line), 25 to 34 (green line), 20 to 24 (red line), and 16 to 19 (blue line)

Women are doing better than men.

Index of Employment Levels – Men (blue line) vs Women (red line)

Mom and Pop employment is sucking swamp water.

The less education one has, the less chance of finding a job.

Index of Employment Levels – University graduate (blue line), Some college or AA degree (orange line), high school graduates (green line), and high school dropouts (red line)

And being white is not helpful for employment. FRED does not have data series for Asians, but the BLS does – and indexed Asian employment levels are similar to Hispanic.

Index of Employment Levels – Hispanic (blue line), African American (red line), and White (green line)

Chief economist for the National Federation of Independent Business (NFIB) William C. Dunkelberg released the following statement in advance of this jobs report:

“Small firms are continuing to shrink as small employers in June reported an average gain of negative 0.09 workers per firm-essentially zero. We only have to look to Washington for reasons why our economy can’t seem to maintain steam and is on a painfully slow journey towards job creation. Graph

“Eleven percent of the owners surveyed by NFIB (up 2 points) reported adding an average of 3.6 workers per firm over the past few months.  Offsetting that, 12 percent reduced employment (unchanged) an average of 4.3 workers (seasonally adjusted), producing a seasonally adjusted gain of negative 0.09 workers per firm overall.  The remaining 77 percent of owners made no net change in employment.  Fifty-three percent of the owners hired or tried to hire in the last three months and 41 percent (77 percent of those trying to hire or hiring) reported few or no qualified applicants for open positions. While a higher percentage of the owners hired, those who reduced employment made cuts large enough to put employment growth among existing firms in the red.

“Nineteen (19) percent of all owners reported job openings they could not fill in the current period (unchanged) and 12 percent reported using temporary workers, little changed over the past 10 years.  The health care law provides incentives to increase the use of temporary and part-time workers, but this indicator has not registered a trend toward the use of more temps.

“Job creation plans rose 2 points to a net 7 percent planning to increase total employment, better, but still a weak reading. Not seasonally adjusted, 14 percent plan to increase employment at their firm (down 2 points), and 6 percent plan reductions (up 1 point).

“Uncertainty about the health care law continues to have a negative impact on small business. Small employers are still trying to figure out what labor will cost and what firm size will have to comply with which rules. As long as Washington is continues to create rolling disasters- exemptions, special deals, delays, confusion, contradictory regulations, small businesses will not be ready to bet on their future by hiring lots of workers with uncertain cost.”

Caveat on the use of BLS Jobs Data

The monthly headline data ends up being significantly revised for months after the initial release – and is subject also to annual revisions. The question remains how seriously can you take the data when first released.

The above graphic (updated through October 2011) is the month-over-month change in employment based on the original headline non-farm employment level and the current stated employment levels at month end. You will note some pretty drastic backward revision for a major economic release the market reacts to in real time.

Econintersect Contributor Jeff Miller has the following description of BLS methodology:

  1. An initial report of a survey of establishments. Even if the survey sample was perfect (and we all know that it is not) and the response rate was 100% (which it is not) the sampling error alone for a 90% confidence interval is +/- 100K jobs.
  2. The report is revised to reflect additional responses over the next two months.
  3. There is an adjustment to account for job creation — much maligned and misunderstood by nearly everyone.
  4. The final data are benchmarked against the state employment data every year. This usually shows that the overall process was very good, but it led to major downward adjustments at the time of the recession. More recently, the BLS estimates have been too low.

Econintersect has repeatedly pointed out questions about how the seasonal adjustment algorithms and data gathering methodology used by the BLS introduce uncertainty into interpretation of month to month changes in employment.

Econintersect believes the simplistic sampling extrapolation technique of ADP yields a far better picture of the employment situation than the complicated, convoluted Bureau of Labor Statistics (BLS) methodology. However, ADP is using a new methodology beginning with the October 2012 data – and only time will tell if their new approach was as good as their old one.

ADP (blue line) versus BLS (red line) – Monthly Jobs Growth Comparison

Because of the differences in methodology, many pundits ignore the ADP numbers – while waiting for the BLS numbers. Although there can be a low correlation in a particular month, the different methodologies tend to balance out, and the correlations are excellent outside of the data turning points. We are now 16 months past the post recession turning point in employment.

However, there is some discussion that neither the ADP or BLS numbers are correct – as both are derived by a sampling methodology. The answer could be that there is no correct answer in real time – and that it is best to look at the trends. As has been noted, all eventually end up correlating.

The BLS uses seasonal adjusted data for its headline numbers. The seasonally adjusted employment data is produced by an algorithm. The following graph which shows unadjusted job growth – seasonal adjustments spread employment growth over the entire year. Employment does not really grow in the second half of the year and always falls significantly in Januarys.

Non-Seasonally Adjusted Employment – Private Sector

There is the proverbial question on what is minimal jobs growth each month required to allow for new entrants to the market. Depending on mindset, this answer varies. According to Investopdia, the number is between 100,000 and 150,000. The Wall Street Journal is citing 125K. Mark Zandi said 150K. Econintersect is going with Mark Zandi’s number:

  • If Econintersect used employment / population ratios to determine the number, the exact number seems to be between 140,000 and 160,000. The graph below uses the historical employment-population ratios to show jobs growth per month if the population was 300 million.

Historical Monthly Jobs Growth Comparison if Population was 300 Million

  • If Econintersect uses employment – population ratios, the correct number would be the number where this ratio improved. Using the graph below, the ratio began to improve starting a little after mid-year. This corresponds to the period where the 12 month rolling average of job gains hit 150,000.

Employment to Population Ratio

Note: The ratio could be fine tuned by adjusting to the ratio of employment to working age population rather than the total population. However, this would not change the big picture that an increase of somewhere around 150,000 (+/-) is needed for the growing population numbers. We have estimated 140k – 160k. The number might possibly be within the range 125k – 175k. Econintersect cannot find reason to support the estimates below 125k.

The question of how changing demographics impact the employment numbers is at the margins of analysis. Econintersect will publish more on this fine tuning going forward, both in-house research and the work of others.

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9 replies on “Again a Good BLS Jobs Situation in June 2013”

  1. thanks for keeping your intellectual honest as usual.  no one has explained “the dip” to me yet. i remember CNBC simply staring into their camera sets when it happened…but now it’s “buy!buy!buy!” again.  “once bit twice shy.”  or should i say obliterated?  that collapse has some explaining to be made…no one is making it…i see a second one coming only unlike in the Great Depression it’s coming in the debt markets.  this is not something i want to see of course…but the math some seems too powerful here.  as the lack of recovery of proceeds the need for a greater one grows larger.  these two lines must “intersect”…and they will intersect when the need based line goes down to meet reality.  it could be worse.  indeed…it SHOULD be worse.  Ben Bernanke et al clearly did their homework.   it’s starting to look like he made have succeeded too well actually.

  2. Perhaps it was good from a Fed ans politicians standpoint, but it was bad for America. U^ ticked higher, manufacturing lost jobs and bar and restaurant employment increased. From the Fed and politician standpoint a job is a job, but I weep for America, folks that used to make $30/hr full time now work part time for minimum wage. Obamacare is killing us, NFIB employment is down, and politicians regulate everyone to death except their 2btf 2btj bankster buddies.

  3. Perhaps it was good from a Fed ans politicians standpoint, but it was bad for America. U6 unmemployment ticked higher, manufacturing lost jobs and bar and restaurant employment increased. From the Fed and politician standpoint a job is a job, but I weep for America, folks that used to make $30/hr full time now work part time for minimum wage. Obamacare is killing us, NFIB employment is down, and politicians regulate everyone to death except their 2btf 2btj bankster buddies.

  4. @taymere 
    yes, you are correct. from my standpoint – this is part of the disconnect between the establishment and the household surveys which always provide inconsistent answers. in theory, a good establishment gain (number employed) in the establishment survey should show employment / population ratio gain (it did) and lower unemployment (it did not). part of the reason could be the more jobs available – the more that people want a full time job.
    the automation trend in retail has yet to  kick in with a vengeance – don’t worry, if you like long enough this sector will be growing and the employment falling.

  5. @econintersect Mish says 326k full time jobs were lost, is he correct? Is he mixing and matching survey and household numbers to arrive at this 326k number or is it all household survey based? Can the numbers be added and subtracted like he does or is there an apples and oranges type of error in his calculations?

    “326,000 Full-Time Jobs LostInvoluntary part-time jobs increased by 322,000 while voluntary part-time jobs increased by another 110,000. Thus, of the 160,000 household survey gain, 486,000 of them were part-time jobs, a loss of 326,000 full-time jobs. “

  6. @taymere  @econintersect
    I have read Mish’s article.  Without digging into the BLS report I assume his arithmetic (and numbers quotes from BLS) are correct.  He usually does not make errors in that regard.
    There is one factor that Mish does not mention specifically in his article and that is the measurement error uncertainty reported by the BLS.  He does mention volatility once or twice, which is partially due to measurement error uncertainty.
    The problem with attributing significance to many of the numbers he discusses arise from two sources:
    1.  The BLS applies backwards revisions to data, the biggest coming once a year in March (I believe, I have not dug into the BLS website to confirm the exact month).  Mish discusses this in great depth as to the Birth-Death adjustment.  Additional adjustments come 1-3 months after the initial data as stragglers report input for one or two months past.
    2.  The sample size of the household survey is such that the measurement error uncertainty is between +/-300,000 and +/-400,000 each month.  (The BLS continually reports on the fluctuation of this value and the latest report can be found on the BLS site.  Please forgive me for not digging to retrieve the link.)
    Because of these two major contributions to uncertainty, I maintain there is little value in attributing any economic influences to changes less than 400,000 for certain (probably less than 500,000 until after backward revisions are applied).  All the data that Mish discusses in his sections “Initial Reaction” and “326,000 Full-Time Jobs Lost” falls within the uncertainty window.
    I have not been analyzing BLS data for the past couple of years.  When I was reporting on that years ago, I looked at 4-month and 6-month moving averages which reduced the uncertainty by approximately the square root of the number of measurements.  The 4-month ma uncertainty from measurement error became +/-150,000 to +/-200,000 and the 6-month ma uncertainty was +/-120,000 to +/-160,000.  That, of course did nothing to mitigate uncertainty due to the annual data adjustment early every year except in the month it was applied and the next couple of months afterwards.
    Dealing with the household survey, most months report numbers that are statistically indistinguishable from no change.  To make meaningful observations trends and moving averages should be analyzed.
    In Mish’s section “June BLS Jobs Statistics at a Glance”  all the data is from the Household survey except Payrolls.  The U-6 unemployment and the Participation Rate are numbers that are only marginally affected by the uncertainty because they have few significant figures.
    The Payrolls number is from the establishment survey and that is a much bigger sample which results in a smaller measurement error uncertainty, +/-100,000 according to the BLS.
    Mish has an excellent discussion of the factors and trends shaping the employment story.  The persistent increase in part-time employment is one area that he could have discussed in more detail (subject to my concerns about statistical significance).  I would like to see evidence that Obamacare is the reason for increased part-time employment.  It is a very logical hypothesis but other factors must be quantified (or eliminated) to prove the hypothesis.  At best, I can say he hypothesizes that Obamacare would encourage an increase in part-time employment and that increase is observed.
    So there is a correlation.  But correlation does not prove causation, as Reinhart and Rogoff and many others have conspicuously demonstrated over the years.
    The author of this article may want to add to (or correct) my thoughts.

  7. @taymere 
    first of all, part time employment levels are very noisy – and as Mish points out – this was a big increase month. from the establishment portion:

    Mish’s numbers came from the household portion alone – which is where the unemployment numbers exist.  Consider:
    – the establishment and household portions of the jobs report never match, and this month was worse than normal.
    – the household portion does not have the same type of backward revision as the establishment portion, and is basically fixed.
    – the household portion had an unusual jump in the size of the workforce which caused a jump in the U-6.  this strangeness reflects in the participation rate and employment – population ratios. Ratios like this are so broad that it is inconceivable that there is much movement from month-to-month in slack times.
    Neither Mish or I love the BLS Jobs report – it is a disaster of misguided bean counters trying to adjust data to make it seem coherent.  In process engineering, this complexity creates the data wobbles that the complexity was designed to eliminate.  Further, the establishment portion will have so much backward revision that the initial release is misleading. The BLS has violated KISS (keep it simple stupid).
    Mish’s theme is that this part time employment jump is caused by Obamacare.  I neither accept or reject this theory based on the data I am seeing, but from a logical point of view, the Obamacare applicability to people working above 25 hours has got to create more part time positions.
    We have a growth trend of 3 months now supporting Mish’s theory. There could be other explanations. 
    steven hansen

  8. @econintersect Thank you very much for your detailed reply. As an mREIT investor I need to pay attention to this type of data and try to understand what is statistically significant since the Fed specifies 6.5% unemployment as their threshold. They have picked such a noisy metric to use as a threshold.

  9. @econintersect Thank you very much John ans Steve for your detailed replies. As an mREIT investor I need to pay attention to this type of data since the Fed specifies 6.5% unemployment as their threshold. I am trying to understand what is statistically significant and what is conjuncture and both of your replies helped in that. The Fed has picked such a noisy metric to use as a threshold.

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