US Jobs Data Under Focus Today

This is a good explanation of how the market was responding.  I have tried to explain how and why this can happen — will happen — and quite often.  ADP may be proved correct.  Time will tell.

Link: US Jobs Data Under Focus Today.

David Jackson submits: Excerpt from our One Page Annotated Wall Street Journal Summary (which you can get emailed to you every morning by signing up here): AHEAD OF THE TAPE: Prediction Market Summary: The Labor Department releases its monthly jobs …

A Helpful Analogy

Let’s suppose that I get out my headphones and IPod and take the dog for a walk.  Let’s further suppose that someone has given me a gadget — a pedometer — and at the return from my walk it says that we have traveled exactly one mile — 5280 feet.  If my stride is even (sometimes a little tough on a dog walk) I might be pretty close to the estimated distance.  Let’s say the walk was actually 5290 feet.  Well getting it within ten feet would be excellent, an error of less than two-tenths of one percent.

Taking this little example another step, let’s suppose that the next day I choose a different route and I plan to stop for a break after walking exactly one mile.  Suppose that I estimated even better than the day before, missing by only one tenth of one percent, stopping after 5275 feet.

Now finally, let’s suppose that a Genie appeared and offered me a prize if I could tell him the actual difference in length between the two walks.  I would win only if my estimate of the difference was accurate to within two feet!

The problem in winning the prize is pretty clear.  While my estimate of each walk is excellent, my estimate of the relative difference in these two large distances is not so good.  An error which is small in percentage terms in the first case, is quite large when viewed as a percentage of the deviations.

The difference of two feet in the dog walks is the equivalent of a 50K change in the estimates for monthly non-farm payrolls.  No wonder it is difficult to win a bet with the market "genie" on this report.  Even if you knew the truth, you could lose because the estimate was wrong!

Employment Report Methodology

Today’s market focus was the monthly employment situation report.  The numbers get a lot of publicity, including the popular media.  Most active market participants know that the numbers are adjusted in various ways and that they also get revised.  Even the best-informed observers miss some key points.  If you read this through to the end, I’ll bet you learn something you did not know.

The featured number, the growth in non-farm jobs, uses the difference between the current and prior months.  Let’s see what that means.  (I’m going to put aside, at least for this particular discussion, the fact that there are seasonal adjustments and a "birth/death" model to account for the changing business population.  It is possible that there is significant non-sampling error.)

The reported results are based upon a survey.  About 400,000 workplaces are supposed to respond with information during the week of the month containing the 12th.  Most people figure that a survey that large must be pretty accurate, and it is.  The 90% confidence interval is about +/-0.1%.  This means that the Bureau of Labor Statistics is estimating the size of the workforce every month and doing it very accurately.

The problem is that the workforce is over 140 million, so a 0.1% error amounts to 100,000 jobs!

So today’s report estimated 135 million jobs.  This means that come September we can be 90% certain that the true number of non-farm jobs is 135 million +/- 100,000.

Why September?  The report was issued today.

Not all 400,000 workplaces report on time.  But they don’t.  Just as some percentage of people will be late filing their income tax returns, some businesses do not report employment data on time.  This is the source of the revisions in the payroll data.  (Sorry to disappoint all of the paranoid hedge fund managers who think that the President brings in a team to massage the numbers, but that is not how it happens.)

The first report, like today’s report for June employment, is based upon returns from about 65% of the workplaces in the sample.  That may seem like a good number, and it does provide meaningful data.  The problem occurs if there is some systemic bias in the businesses that are not filing on time — something business condition that relates to hiring or firing employees.  It does not take much of a bias to alter the result by a tenth of one percent — and that represents 135K jobs.

The second report, which we will not see until August, is based upon returns from about 80% of the workplaces.  The final revision, reported in September when everyone will see it as "old news" accounts for more than 90% of the reporting workplaces, which the government figures is good enough.

So what we did today was compare the first estimate for June with the second estimate for May and calculate the job growth.  We will not know the "official" job growth until September, when we have the final numbers for both periods.  Even then, the result for May and June are both +/- 100,000 jobs.

This is good to keep in mind when you see a parade of experts on CNBC trying to explain why there is a 50K difference from "expectations."

Oh — and here’s something they won’t tell you on TV.  Even those who realize that the job growth is an estimate forget it when they discuss the "internals" of the report.  (This is usually done in a deep and serious voice).

Well where does the BLS get the internals?  These are also survey results, of course!  While they do not report a sampling error for the hourly wage in the document, it is probably +/- five cents.  And to get the error down to that level we need to wait until September.

This is part of a consistent theme on "A Dash."  The immediate market reaction to data is often far too extereme, based upon the value of the new information.

Hedge Fund Managers and Data

In market-based activities, the errors of others present opportunities.  It is profitable to look for any aspect of analysis where many are getting it wrong.  Since hedge funds are such an important part of the current market, understanding their managers is also essential.

Understanding and interpreting government data is fertile ground.  It is especially good for me, because of my background as a former poli sci prof, government consultant, specialist in research methods, and long-time consumer of government information.

Contrast this with the average hedge fund manager.  Now don’t get me wrong.  These managers are among my best friends!  They are really smart and very talented, or they would never get a chance to run money.  Every last one of them talks a good game and has had meaningful success somewhere.

The problem is that it is a young man’s game.  (I could try to be politically correct, but it is a world of mostly men, and that is part of the point).  There is rapid burnout.  From the perspective of regular business people, the managers are limited in experience.  There is a danger in knowledge that is a mile wide and an inch deep, where you must have an opinion on everything.

We know a lot about what hedge fund managers think because they network, some of them blog, and others write columns online.  They generally want to be contrarian, fast thinking and acting, and willing to make bold moves.  A lot of confidence and machismo is de rigeur.

The idea of being contrarian is quite sound.  It is at the heart of exploiting market inefficiencies.  The irony is how to be a contrarian when all of the other managers are doing the same thing.

Disparaging government data becomes a way of showing off.  Acting like there is a conspiracy to manipulate results may seem like sophistication.  It is usually easy to find some argument and take it to the lowest common denominator.  It is very convenient to dismiss data, since it then becomes possible to argue anecdotally.  If you do not understand something, just dismiss it as irrelevant!

A hedge fund manager who really wanted to be contrarian would want to learn more about government data releases and how to interpret them.  This is the place.

The CPI as a measurement of inflation is such an easy target for pundits.  Let’s start there, but we’ll eventually look at nearly all of the government releases.

No Inflation???

Pundits on TV and websites express amazement that today’s CPI data show no change overall and only a .1% increase in the core rate.  Writers on Cramer’s site, experts on CNBC, and even Bill Gross all claim that government measures of inflation are silly and inaccurate.  To them, it is obvious that prices are much higher than reported.  Just look at medical care, gas prices, hamburger, or home prices.

That argument sure sounds good.  It is easy to understand, and most people do not think it through any more.  That means that for those willing to get a deeper understanding, there is real opportunity.

Let’s look at some evidence and then try to approach the problem with an open mind.

There are several government indicators of inflation, including the CPI, the PPI, the PCE (focused on wage related costs) and the GDP price deflator.  Greenspan favors the PCE, but the others all get some attention and each is a slightly different measure.  They all show inflation as running about 2 – 2.5%  This is not a bad reading.  It is consistent with a healthy economy.

Another way of looking at this is by turning to the market.  The Treasury now issues inflation-protected bonds.  You can look at the difference between the rate for TIPS and the rate for other government bonds and find the expected inflation.

The result is similar to the inflation readings for the next ten years.  This shows the verdict of one of the largest and most liquid markets — hardly the picture of stagflation that some expect.

So what is wrong with the anecdotal story?  Part II of this series will be the explanation.