I will be writing an occasional series of posts, discussing useful tips for reading the volumes of economic statistics that fill the airwaves daily, starting with this post on pulling apart time-series data.
In "True Lies and Economic Statistics", I pointed out the statement that May 2010 had the "biggest monthly increase in jobs in the past ten years" is a "true lie". Anyone citing the job growth number is making a judgment on whether the economy is healthy enough to create jobs. But the 431,000 number does not answer this question.
The key to reading the job growth statistic is to pull apart the multiple threads that it contains. Within the 431,000 figure are the 411,000 temporary workers for the Census, hiring that only happens once every 10 years; the remaining 20,000 new jobs are more reliable but to be meticulous, we ought to further ask:
- how many of these were temporary versus permanent jobs?
- Were there any statistical adjustments (e.g. seasonal adjustments, so-called birth/death model adjustments), and
- if so, how large were those adjustments?
Think about your electricity bill. It was $100 in May; it went up to $150 in June. You want to know why: in particular, you want to know if the $50 jump reflects a persistent shift in your usage level.
You realize that your energy use jumps at the start of every summer, because of air conditioning. Looking up the GE energy use website, you estimate that your room a/c should add about $30 per month to your bill during the summer. So at least $30 of the $50 jump is due to "normal" usage. This, in essence, is what statisticians mean by "seasonal adjustment".
Next, you throw a World Cup launch party for your college buddies, in June every four years. So every four years, your June electricity bill shoots up. Looking up past June bills, you can estimate how much energy your buddies use while they are in your house. This is what is known as a "cyclical adjustment" because such extra spending also says nothing about your "normal" usage level.
Similarly, we can pull apart many threads in the job growth number. Roughly speaking,
Observed job growth - seasonal effect - cyclical effect = economic growth effect + margin of error
For May 2010, according to the Census Bureau, this equation read thus:
1,090,000 - 659,000 - 411,000 = 20,000 +/- error.
Yes, the survey result reported an increase of 1.1 million jobs from April to May (you wouldn't know from published reports). However, 60% of this growth represent a spurt in hiring at the start of summer, something that happens every year and thus not an indication of a growth spurt. In addition, almost 40% of the observed growth are the temp Census jobs, which happens once every ten years, and also not an indication of a growth spurt.
To make matters worse, the sample size of the survey leads to a margin of error of +/- 100,000 jobs. And the 20,000 jobs created is much smaller than the possible error and so the best we can say about May jobs is that the job market flat-lined.
The Census automatically makes the seasonal adjustment (something they find so routine that they do not even mention, in the main text, that the published numbers are post-adjustment). But Census does not adjust for the once-in-a-decade spurt in Census hiring. I find that odd.
They may not do it, but you and I should do it.
P.S. Please see my older post ("The Real Climategate") for an example of how statisticians decompose time-series data into various components, basically a graphical representation of the above equation.