To begin, it's useful to understand how the Bureau of Labor Statistics calculated the 243,000 increase in employment that it reported for January. Total non-farm employment in the U.S., before seasonal adjustments, fell by 2,689,000 jobs in January. However, because it's typical for the economy to lose a large number of jobs after the holidays, largely in retail trade, construction, and manufacturing, the BLS estimated that the "normal" seasonal decline in employment should have been 2,932,000 jobs in January. The difference between the two numbers, of course, was 243,000 jobs, which was reported as an increase in employment. The fact that the size of the seasonal adjustment was more than 12 times the number of reported jobs, and more than 30 times the "beat" in economists' expectations, should provoke at least some hesitation in taking the number at face value.
Notably, the January 2011 and 2012 seasonal adjustment factors ( seasonally adjusted payrolls divided by unadjusted payrolls) have been the two largest factors used by the BLS since the 1960's, at 1.0166 and 1.0165, respectively. This compares with a January seasonal factor of 1.0155 a decade ago, and a factor of 1.0152 as recently as 2009. Now, a range of 0.0014 in the seasonal factors for January may not seem like much, until you consider that non-seasonally adjusted payrolls are presently about 130 million jobs, so variation in the seasonal adjustment factor alone amounts to a difference of 182,000 reported jobs. I'm not suggesting there's anything nefarious going on here, it's just that part of what we're seeing here is most likely a statistical artifact of the adjustment process.
Moreover, we've had a remarkably mild winter in the U.S, particularly in January, and it's clear that this has favorably affected both construction and retail activity. Ironically, however, nothing in the seasonal adjustment actually adjusts for this purely seasonal effect. If the mild winter weather reduced the "normal" number of January layoffs by just 3-4%, that would account for the entire amount by which the January employment number "beat" economists' expectations.
Our understanding is that most economic series are seasonally adjusted using the same algorithm from the Census Bureau, and indeed, we've been able to closely replicate the labor department's adjustments to various data series using that software [Geek's note: take the option to log-transform the data]. One concern we are aware of is that some data providers such as the ISM use exceptionally short windows (such as 5 years) to estimate their adjustment factors, which appears to invite a large amount of statistical noise in these factors due to the deep and unusual weakness of the 2008-2009 period.
As a side note, because the ISM incorporated the newly released seasonal factors from the Department of Commerce, we saw some significant downward revisions in the December ISM figures that made the January figures appear stronger. For example, the January figure for new orders was 57.6, the same as the original December figure. But since the December figure was revised down to 54.8, the January report appeared to be an improvement. Compared with the original December figures, both production and employment actually dropped. The original December PMI was 53.9, inching higher to 54.1 in January, primarily due to higher inventories. The upshot is that the composite signal from Purchasing Managers Indices and regional Fed surveys has improved modestly, but the overall picture remains lukewarm.
I certainly don't want to push that argument to the point of suggesting that recent reports are irrelevant, or that they don't reflect actual improvements. There is enough conformity across multiple pieces of economic data to conclude that the positive economic performance of late is not purely statistical noise. The real issue is the extent, durability, and "leadingness" of those improvements, where we continue to be adamant that lagging data (such as the unemployment rate) should not be expected to lead. Indeed, job growth has typically been reasonably positive in the 1, 3, 6 and 12 months prior to a recession. Job growth was positive in the month prior to 8 of the past 10 recessions, and in the 3 months prior to 9 of the past 10 recessions. In other words, we shouldn't expect weak job reports to lead recessions, though the year-over-year growth rate in payrolls invariably drops below 1.5% in the early months of a downturn (a level that we're still below).
In any event, a reasonable interpretation of the January employment report is that fewer jobs were lost in January than the BLS estimated that the economy should have lost on the basis of seasonal patterns. The economy is essentially bouncing around the flatline, and the main question is how much longer we can avoid a negative shock of any kind.
