ISM Report and Inflation

Ticker Sense, one of our featured sources, takes a look at future inflation prospects.  If their analysis is correct, some of the current market negativity may be misplaced.  We might (modestly) point to our own discussion of ISM numbers, something that traders should keep in mind.

Link: ISM Report and Inflation.

For several months now, we have been highlighting the commodity survey within the monthly ISM Manufacturing survey which asks respondents what commodities are rising in price and what commodities are falling in price. In the past, peaks in troughs in…

Comparing Two Charts — an Insight about Labor Force Participation

Thanks to FinancialRx for reminding us to check out Mike Panzer’s site for some interesting charts.  Among them was a chart showing an apparent relationship between a ratio of temp workers to all workers and the S&P 500.  While Mike does not make any extravagant claims about this, the text on the chart and the arrows sure make it seem like a potential decline in this ratio would be a bad sign for the market.  Take a look at the chart here or below (click to enlarge).

Temphelpspx
This is a powerful type of graph to do.  If there is a similarity in the pattern, one adjusts the scales to emphasize the fit.  The text boxes lead the viewer to the key question.  The skill in charting is worthy of Tufte (see recommended reading at right).

Since I taught the courses in this sort of analysis, I immediately had a couple of questions:

  • What did the data look like BEFORE the chart’s time period?
  • What sort of causal model might be at work?
  • Does one market cycle offer predictive power?

Taking the second of these questions (and empahsizing again that Mike was not beating the drum about this) I am suspicious of research that begins with data instead of with theory.  I have written about this approach and so has Brett Steenbarger.  I wonder why this ratio is such a good predictor.  Those who take courses in causal modeling approach these problems quite differently.

It is important to realize that the 1999-2000 employment era was extremely unusual.  David Malpass has written effectively on this point, as has Gene Epstein, the Barron’s economic columnist.  Labor force participation during this time was at an extreme, a subject which Gene covers in an entire chapter of his book, Econospinning, also in our recommended reading.

To summarize briefly this era, remember that there was a great fear about the consequences of the Y2K problem.  Companies could try to update their existing computers and software.  Many chose to advance purchases of computers, operating systems and software.  COBOL programmers were solicited.  It was all part of the fuel for a massive expansion of employment, drawing in marginal labor force members.  It is possible that this peak of labor force participation will never again be reached, so comparisons should be to longer-term trends, something we have covered in past insights.

I mentioned my curiosity about the data series in our office, and our newest staff member picked up the ball and ran with it (despite the distractions of her wedding, tomorrow — Best wishes Renae!)  She went to the BLS website and got the entire data series, beginning with the first tracking of the temporary workers.  Here is what she found:
Complete_temp_employment

You can see that the series did not fit so well, using Mike’s scale, in the earlier time period.

Did something change in this relationship?  There is not enough history to form a good conclusion.  That is often the answer when we are looking at apparent relationships.  We do not have enough data for many things we would like to explore.

Try This Test

In a prior post we described the wonderful class test used by Thomas Gilovich where he asks some students to simulate coin flips while another group records results of actual flips.  He can always spot the fakes because the students do not realize what random data looks like.

Readers of "A Dash" are more astute. They might be able to fool Gilovich on coin flips, but how about this challenge?

Let us suppose that the actual monthly growth in non-farm payrolls was known to be exactly 130,000 jobs each month for the next year.  Since the BLS report is based upon a big survey of 400,000 establishments, we can expect to get a good result — but how good?

So try it.  Write down twelve numbers that are consistent with these conditions.  Then check your answer against my actual simulation, or try your own simulation at The Payroll Employment Game.

Would you have fooled Professor Gilovich?

Consider the following data series:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Aug-06 93
Sep-06 257
Oct-06 155
Nov-06 172
Dec-06 101
Jan-07 204
Feb-07 49
Mar-07 139
Apr-07 184
May-07 44
Jun-07 107
Jul-07 138

Let us suppose that these figures represented the monthly change in payroll employment over the next year.  One can readily imagine the interpretation that might be placed upon the August number, due to be released tomorrow, that job growth is weakening dramatically.  The big increase in September might frighten those worried about future Fed policy, but delight those going on TV to talk about the President’s economic policy.  The October number, announced right before the election, would also be helpful.  And so forth through the year.

Here are the data in graphical form. (click to enlarge)
Job_growth

The data series was created using the advanced tools at The Payroll Employment Game site.  I simply specified the truth growth rate as a constant 130,000 jobs (the number Fed Chair Bernanke thinks we need to maintain employment and reasonable economic growth).  The resulting series is typical of the variation you would get from the BLS establishment survey.  The actual mean for the period is 137K and the average absolute deviation from "truth" was about 50,000 jobs.

I did it a few more times with very similar results.  Readers should go to the game site and give it a try. You will have an advantage over many of the experts you read about our see on TV!

(Next month we may make this and other experiments a bit easier to try).

Economic Pessimists In Denial

Rich Karlgaard has an intriguing commentary on upcoming economic data.  We strongly agree with this assessment, and suggest that readers follow the links in his article.

In interpreting the payroll employment report, however, be prepared for a lot of noise from the survey.  We suggest testing the prediction with our Payroll Employment Game.

Check out the story and links, and we’ll follow with more commentary as the week unfolds.

Link: Economic Pessimists In Denial.

Sure, we hit our Brian Wesbury quota yesterday — but what the heck. Today’s piece by First Trust Advisor’s chief economist is too good not to cite: This week’s economic data is going to be hard for the pessimists to…

Economic Strength?

The indicators for economic strength should be a factual matter.  One might write them down and then monitor them.  Many economists take this approach.  This week will see several important  government reports on the economy including the second quarter GDP revision, pointed to as overly weak when the first estimate came out.  There will also be the payroll employment report.  Interested traders can try out their guesses on our payroll employment game.

Barry RItholtz has done a lot of work on forecasting and explaining the employment numbers, and I am sure we’ll be seeing a prediction from him in the next two days.  You should look at his past work before playing the game.

Meanwhile, check out his latest observations about economic strength and then come back for our viewpoint.

Link: Consumer Confidence and Commodity Weakness Heralding An Economic Slowdown.

The data keeps coming, and its getting harder for the perma-bulls to rationalize the information. Earlier in the month, University of Michigan Consumer Confidence plummeted the lowest level since last October; the blame went to Terrorism fears and higher …

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The Payroll Employment Game

Sometimes a game makes everything clear.  The Payroll Employment Game is now available for your entertainment, education, and comment at this site: www.payrollemploymentgame.com.

Here is the background.

The big economic news for this week will be Friday’s report on the employment situation, highlighted by the payroll employment report.  There is always intense speculation about the pace of job growth.  The report has special significance because it is the first real data from the month just ended, and because employment growth is a fundamental aspect of economic growth.

At "A Dash" we have written about the problems in interpreting this report, provided an illustration of the measurement errors involved, and suggested some insight into how the Fed looks at the data.

Now we let readers simulate for themselves the perils of forecasting employment growth.

The Fed and the Employment Report

Today was one of almost non-stop speculation about Friday’s employment report and how the Fed will react to it.  ADP had a predicion of job growth under 100K while the consensus is for 140K.  Most of those interviewed on CNBC were talking about differences in Fed policy based upon 50K changes in the result.

Readers of "A Dash" can get an insight into how the Fed is likely to respond.  I tried to do this last month with a description of methodology and an example of the error rate.  Sometimes it takes a graphic analogy, well outside of the problem area, to make the point.  I shall try again.

As you read this, you should be aware that the Fed Governors and their excellent staff understand what I am explaining.  They get it perfectly.  Unlike most on the Street, I am not speaking to them, trying to tell them their job.  I am trying to help the rest of us understand what they already know.

Let us suppose that we are in a bar that has a dartboard, a tried and true Wall Street analogy.  Next let us suppose that we set the throw line fifteen feet from the dart board.  The bullseye represents "truth" as we call it in statistics classes.  It exists, but it can only be estimated.  In this case it is the actual payroll growth for the month.  A player (perhaps having consumed a few brewski’s) steps to the line and throws at the board.  We mark the location of the first dart.  That is the first payroll jobs estimate, based upon only partial returns from a survey.

Now we let the player step up a few feet to a twelve-foot line.  The player throws again, and we mark the location of the second dart.  This is based upon the first revision of the payroll survey results.

Finally, we let the player throw from a regulation distance of about eight feet from the board.  The result is the payroll number after both revisions, about 90% of those originally asked to respond.

Here is the key point:

We now go to the board and draw a new bullseye around the position of the first (and least accurate) dart.  We accept that as "truth."

Briefly put, it is quite possible that ADP, or Briefing.com, or Ed Yardeni, or some other economist made an accurate prediction of truth, because we actually score the game based upon where the first, and least accurate, dart lands.

Even the final dart has an error band of over 400K jobs at the 90% confidence level.

Most employment numbers, probably the vast majority, are off by more than 50K jobs even after the final revision.  Despite this, the Street will swing billions of dollars on this result.

The main  point is that the Fed does not do this.  They understand the nature of the estimate.  They look at three-month groupings and trends, where the error is reduced.

I’ll pursue this further with how an investor can make use of this information, but it is important to keep in mind when viewing Friday’s report — and the revisions for prior months.  Also please note that the revisions change the base for the current month — often forgotten.

The Cognitive Bias of Ed Yardeni Critics

I admire Barry Ritholtz’s enthusiasm for analyzing Street Research — not peer reviewed and often methodologically flawed.  His critcism of Dr. Ed Yardeni’s New York Times comments, however, is both incorrect and more than a little unfair.  I’ll cite specific errors, but first look at Barry’s argument:

Link: The Cognitive Bias of Ed Yardeni.

One of the more astonishing things I’ve come across recently was an utterly disengenuous article in Sunday’s Times: Navigating the Fog in Jobs Data. The article is a discussion with (former Prudential) Strategist Dr. Ed Yardeni. It seems that he has been …

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Redux: Household versus Establishment

While Barry Ritholtz’s blog is a big favorite for lots of us, I do not think that David Malpass, Chief Global Eocnomist for Bear Stearns, is going to drop by to comment on the employment numbers.

His work in the current cycle has been brilliant — right on target throughout, so let me summarize a few points.  The key idea is that he thinks the Household survey is a lot better.  But look first at the background from Barry, including some great charts from the BLS.

Link: Redux: Household versus Establishment.

One last item: The Labor Department’s payrolls report is also at odds with its own survey of households, which is used to calculate the unemployment rate. The household survey showed employment grew by 387,000 in June, in line with ADP’s figures.The …

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