Nearly everyone will agree that improving employment is crucial for economic growth. Understanding the various employment indicators is important for any investor who is interested in fundamental analysis. I write a monthly employment preview where I highlight forecasts using several different methods, including one developed by my team. Here is a good recent example.
In this article I want to take a different approach -- a focus on the Bureau of Labor Statistics and the monthly estimate of the change in payroll jobs. If you will take five minutes to look at a few charts, you will have a better understanding than all of the experts you see on TV.
I will make a few simple points and let some great charts (thanks to Feray) illustrate the key points. All of the data come from the BLS Business Dynamics series (seasonally adjusted). This means actual data from state employment offices -- no guesswork or revisions.
The discussion about job creation is very deceptive. Nearly everyone confuses "job creation" with "net job creation." The monthly changes in jobs are only the tip of a wave, concealing massive shifts below the surface.
This chart from the BLS shows that job creation, until the 2007 recession start, ran at 7.5 million to 8 million jobs per quarter. Even at the worst point of the recession, job creation was nearly 100,000 new jobs for every business day. The problem is the rate of job losses (the red line).
Conclusion #1: There is always job creation -- lots of it -- even in recessions.
Suppose we wanted to measure the change in employment. One method, the one embraced by the BLS, is to count all of the jobs in the country in one month, count them all again in the second month, and subtract to determine the change. Since the BLS cannot count every job, it relies upon a survey (and a good one) of existing businesses.
The problem? Some businesses do not respond to the survey. The BLS uses great methods to improve the response rate. 65% or more respond in time for the first report. 75% or more a month later. The final result includes response rates of about 90%, which is excellent for survey work.
But what about the missing 10%? Are these non-respondents or (drum roll...) are they companies that are out of business. The difference is crucial to the result. One interesting idea is that you could just take the outcome from the respondents and infer that non-respondents were the same.
This implies something important, what I call the 'Imputation Step." The question is whether we may infer, based upon actual data, that the behavior of business deaths and births is similar to the behavior of the businesses continuing in the sample.
From this chart you can see that the contribution to new jobs from opening establishments has a relatively constant proportion to continuing businesses. Recessions are indicated.
Conclusion #2: It is reasonable to infer that business deaths and births parallel the job effects of continuing businesses.
Let Us Verify
Taking the pattern from continuing businesses and imputing the same behavior to the net change from new and dying businesses is a big step. Let us take a closer look.
This chart looks at the ratio between jobs gained and jobs lost. It compares the ratio for continuing businesses with the ratio for new and dying businesses.
- Conclusion #3A: Over almost 20 years there has been a tight relationship.
- #3B: The relationship remained strong during recessions.
- #3C: The "birth/death" relationship always showed a premium to existing jobs -- a bit stronger result, perhaps requiring an additional adjustment.
The Recent Recession
The action in the latter part of the chart deserves a closer look.
- Conculsion 4A: The "birth/death premium" was accurate for many years.
- 4B: Recessions did not change this conclusion.
- 4C: Economic "turning points" made no difference.
- 4D: Something happened in mid-to-late 2009 --- after the recession ended!
Focus on the Key Groups
This is where it gets a little tricky. I am comparing a ratio to another ratio. We are looking at a comparison of the "death/birth" business group to the ongoing businesses in the BLS sample. What we would hope and expect to see is an ongoing pattern showing a "premium" of about about 5% -- the 1.05 level.
The chart highlights the dramatic change in the ratio. In the 2001 recession and the 2007 recession, the net change in business births and deaths was actually stronger than the trend. As the recession has ended, the relationship broke down.
There are many inferences to draw from this, but for now I'll stick to the basics.
- Most of the popular criticisms about the BLS are completely wrong. The basic methodology is not "guesswork" or "assumptions" or "creating phantom jobs." The data support the method.
- The key question is not related to the oft-criticized "birth death adjustment" but has more to do with the much larger and more significant "imputation step."
- Something unusual is happening within the last year.