Pay No Attention to the Government Statistician Behind the Curtain
Okay, strap in for yet another tirade on why you should (for the most part) pay very little attention to the monthly nonfarm payroll data, also known as the Employment Situation. Its hype-to-usefulness ratio is abysmally low.
Bloomberg, January 10, 2014
Okay, strap in for yet another tirade on why you should (for the most part) pay very little attention to the monthly Non Farm Payroll data, also know as the Employment Situation. Its hype to usefulness ratio is abysmally low.
Long time readers know this is a peeve of mine (See list of prior articles below). For newer readers, here is the reasoning behind my disdain.
The first has to do with the idea of modeling the real word via assembled data. What you end up with is some form of artificial creation that bears only a passing resemblance to the complexity of the real world. That would not be such a problem, if only you humans remembered what the great professor George E. P. Box advised us: “Essentially, all models are wrong, but some are useful.”
The usefulness of a model that is wrong is that we can into what us useful and ignore what is wrong. And we know from each month’s revisions that the initial read is off, often by a substantial amount. It’s a noisy series, subject to many errors and subsequent corrections.
To put this into some context, consider what it is we are measuring: The change in monthly hires minus fires. A monthly change in a labor force of more than 150 million people. That turns out to be a tiny net number relative to the entire pool — about one tenth of one percent.
This is why I continually suggest ignoring any given month, and paying attention to the overall trend. That is the most useful aspect of the monthly NFP data. A single month can be too high or low relative to the unknown reality. What you want to know as an investor is whether the general trend in the economy is adding jobs, subtracting jobs, or staying the same. It becomes especially important to be able to identify when that trend is reversing — i.e., when a recession is bottoming, or when an expansion is petering out. But if you focus on the monthly numbers, you will be given so many false signals and head fakes that you cannot possibly trade on this information in an intelligent manner.
This is why some observers have remarked that we measure unemployment to the second decimal point only to show that economists have a sense of humor.
Next, even if you had perfect knowledge of the employment situation, understanding the impact is a challenge. Indeed, the weak employment gains this past cycle have not hurt the bull rally in stocks. It has taken quite a long time for many investors to understand that reduced labor costs, greater productivity and ever-increasing efficiency has led to higher earnings. The basic assumptions about “good” or “bad” job reports may not be accurate relative to what equities do over time.
Last, a relentless emphasis on what just happened – the recency effect — causes you to place a disproportionate emphasis on this month’s NFP. You do it again and again like clockwork every month, more or less ignoring the long data series for the high of the latest single data point. As I mentioned earlier this week, it behooves investors to consider the context of each data point in a series, looking at them as if they were a film, and not a photograph.
As to this month’s NFP: Maybe it was the weather. Maybe it’s noise. Perhaps it’s the end of the expansion and a recession begins . . . Now.
The problem is you have no idea which of these are true, and you probably cannot even put a decent probabilistic expectation on any of the above. Hence, we are left with merely another data report in a very long series, most of the time, of very little utility.
Invest on this information accordingly.
1. NFP Day: The Most Over-Analyzed, Over-Emphasized, Least-Understood Data Point(Feb. 4, 2011)
Contextualizing the NFP Data (April 1, 2011)
An Unusually Unusual NFP Payroll Day! (June 3, 2011)
THE MOST IMPORTANT EVER NFP blah blah blah (June 7, 2013)
‘What’s Your NFP Number?’ [Don’t have one] (Aug. 2, 2013)