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The economy: weak leading, lukewarm lagging
The most important news in the financial markets last week was undoubtedly the January employment report, which showed a 243,000 increase in non-farm payrolls, outstripping the 150,000 figure expected by a consensus of economists. Two questions immediately arise. What does this news do to change the likelihood of an oncoming economic recession? And what does this do to change the prospects for the returns and risks in the financial markets?
With regard to recession risks, the January employment report increases the divergence between leading evidence on one hand, where the broad set of data remains in a conformation that is almost exclusively associated with oncoming recession, and the more favorable, if lukewarm, signs from coincident indicators (e.g. employment, purchasing managers index, weekly unemployment claims) and lagging indicators (e.g. unemployment rate).
There is always some element of information when divergences and inconsistencies emerge in the data. But you can't extract that information very well by throwing all the data in a high-speed blender and just taking the average. Rather, inferences should be based on which indicators are relevant in which contexts. Specifically, we know that leading indicators lead, lagging indicators lag, and coincident indicators are coincident. Given that coincident indicators have improved in recent months, we can easily conclude that economic activity has also improved in recent months. But to make a forward-looking statement, we can't just extrapolate those improvements, because we know that coincident data doesn't extrapolate reliably at all. So we have to focus primarily on leading indicators instead.
And that's our dilemma here. It's undeniable that coincident measures have improved in recent months, but we have not seen a convincing turn in the leading data. So either the leading data will uncharacteristically lag the recent improvements, or what remains more likely, the coincident data will taper off and deteriorate. I'll reiterate that we aren't table-pounders for recession, and that we certainly don't hope for a recession (though we would welcome higher prospective investment returns that would be brought about by lower market valuations). Overall, an economic downturn remains the most likely prospect, and it's not at all clear that the latest employment report changes that risk. I think the best way to see why, as always, is to show you the same things that I'm looking at.
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.
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- Feb 06, 2012 at 1:21 PM
