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, culminating in the week of the employment survey. This is the best direct indicator of new lob losses. The average was 571K for this month compared to 567K last month. No improvement.
- We look at the University of Michigan sentiment survey, which we found more useful than the Conference Board's sentiment index. Michigan uses a panel, where some families are carried over from month to month. This is a good technique. Sentiment is influenced by employment. When people have lost jobs, or are worried about losing jobs, it shows up in sentiment. It is a good concurrent indicator. The Michigan index is now at 65.7, about the same as last month's 66. Normally there is very high correlation between Michigan and the Conference Board. In the last month the Conference Board estimate improved from 47.4 to 54.1. We are surprised at the difference between the two surveys. (There is a good technical reason for not using both in the model -- something called multi-colinearity. We might consider combining the two surveys). Meanwhile, there is some "upside risk" in our estimate.
- We us the ISM manufacturing index, which showed dramatic improvement from 48.9 to 52.9 While this is modest expansion in the manufacturing sector, it is quite bullish for the overall economy. The ISM's research shows that this rating, if annualized, corresponds to a 3.7% increase in GDP.
Our long-term 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. In recent months we have been too bearish. We are still evaluating possible reasons for this. One possibility is unusual seasonal factors in July.
This Month's Prediction
Our indicators suggest a net job loss of over 400,000, significantly worse than the Street estimates of about 225K. 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, but we are outside this range.
While economic indicators have improved, some showing actual GDP growth, all of the results are far below economic potential. In addition, businesses may be slow to re-hire, waiting for additional confidence of a recovery. We are many months away from really good news on employment.
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. A wise interpretation would be to consider all of these disparate sources of information.
ADP has proprietary data because of its payroll management business. ADP sees losses of 298K.
TrimTabs also uses real time data. Their estimates are based upon tax deposits for salaried employees. They see a net job loss of 335K.
WANTED Technologies, a relatively new entrant in this field, has a model based upon online help-wanted advertising. This is an innovative and different approach to real-time data. They see a net job loss of only 190K
Conclusion
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. The BLS tries to count all of the jobs in one month, all of the jobs in the next month, and then report the difference. They do this very well, but it is inherently difficult. It does not focus direclty on the actual changes, as other methods attempt to do.
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.
Trading Conclusion
There is a very wide spread in this month's estimates. The non-BLS sources were all too bearish last month.
As usual, the best trade is the short side. If the number is poor, the market sells off. 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.
This proved out last month. The positive number caused a modest pop in stocks. (We covered our short hedges at a small loss.) Then the market moved higher. Two months ago there were rumors of a "fat finger" error, something that makes no sense to anyone who understands the reporting process.
The market continues to place too much emphasis on an estimate that is very difficult to do in real time.
