Employment Report Preview

Each month we ask the question, "What change in payroll employment
would be consistent with other economic data from the same time period
(the middle of the prior month)?

This is not a forecast, per se,
since we do not posit any causal relationship among these variables. 
They are all concomitant indicators of economic activity.  We use the
four-week moving average of initial unemployment claims (still very bad at 567K), the University
of Michigan sentiment survey (slightly worse at a reading of 66), and the ISM manufacturing report (much stronger at 48.9).  We
carefully choose data from the correct time period.

Our record has been pretty good, especially when compared to the final revised data.  This makes sense because our model was derived from the final data.

This Month's Prediction

Our indicators suggest a net job loss of 441,000, significantly worse than the Street estimates of about 350K.  Since the 90% confidence interval on the payroll survey (for sampling error alone) is +/- 100K jobs or so, it is unwise to place much emphasis on small differences.

While economic indicators have improved, probably to the point of showing actual GDP growth, the results are far below economic potential.  In addition, businesses may be slow to re-hire, waiting for additional confidence of a recovery.

Other Forecasts

It is always interesting to compare the job forecasts from different sources.  We follow several because of the interesting and widely varying methods they use.

ADP has proprietary data because of its payroll management business.  It sees a net job loss of 371K.

TrimTabs also uses real time data.  Their estimates are based upon tax deposits for salaried employees.  They see a net job loss of 488K.

WANTED Technologies, a relatively new entrant in this field, has a model based upon online help-wanted advertising.  This month they have added initial claims, one of our factors.  It is another approach to real-time data.  They see a net job loss of 440K.


Each of the sources we cite is attempting to measure the actual net job change.  A wise stat prof once said, "Suppose God whispered into your ear and told you the TRUTH."

The BLS is attempting to do the same thing, with dramatically different methods.  The BLS result is not TRUTH.  It is a statistical estimate.  Actual TRUTH for a specific month will not be known for many months, when the state employment data are analyzed.

Meanwhile, the forecasters will all be graded by how well they predicted the BLS number — the BLS estimate of TRUTH.

That is the wrong attitude.  The BLS number is just another estimate — and one which will not be official until all of the revisions are in.  Despite this, the market will trade on the preliminary estimate revealed Friday morning.

Briefly put, everyone is trying to estimate monthly changes in a work force of over 130 million.  The error band is small.  The BLS — and all of the other sources — are doing a great job with various differing approaches.

Market participants would like to have more data, faster data, more accurate data.

Investment Conclusion

There is evidence for a miss to the downside.  Meanwhile, if that prediction is wrong, one can depend upon the Bearish Blogging Network to attack the BLS, seasonal adjustments, the Birth/Death adjustment, or anything else to save the bacon of hedge funds shorting before the number.  Since there will be no one to refute these claims (the BLS only responds to media inquiries), the short trade has good risk/reward.

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  • John August 6, 2009  

    I see that you did see the TrimTabs commentary…

  • john clark August 8, 2009  

    TrimT -488
    Insight -441
    Wanted -440
    Consensus -350
    What number looks most “off” here? All different methodologies used, could BLS, with all it’s known flaws be right this time, and all the others are real wrong? If you throw out the outliers Trimtab and BLS and average the rest it’s 400 which would mean the BLS was 40% low with their monthly prelim est and they are off 40% or more half the time with the monthly estimates I’ve seen.