In the middle of its thorough analysis of U.S. labor markets, the New York Fed tucked in a direct look at whether persistently high unemployment can be plausibly ascribed to mismatches between the skill sets of unemployed workers and those skill sets required by available jobs. The operating hypothesis goes something like this: structural unemployment arises when the skills that are appropriate for declining sectors are not easily transferable to the jobs available in expanding sectors. In the current context, we can think, for example, about the challenge of turning construction workers into nurses (a metaphor offered a while back by Philadelphia Fed President Charles Plosser). If skill mismatch is an important source of postcrisis unemployment, it stands to reason that we would find its markers in the construction sector.
In fact, the authors (Richard Crump and Ayşegül Şahin) of a New York Fed study find no evidence that construction workers are “experiencing relatively worse labor market outcomes.” Though this observation comes with its caveats—in this space my colleagues Lei Fang and Pedro Silos noted that construction workers who are finding employment in nonconstruction businesses apparently have suffered unusually large wage reductions—the Crump-Şahin results generally conform to other research questioning the proposition that skill mismatch looks to be a larger-than-normal problem in the current recovery.
The idea that inter-sectoral flows of employment, or the lack thereof, is a source of structural unemployment has a venerable history in macroeconomics. But it is increasingly clear to me that the bigger story is not about skill mismatches as workers flow across sectors but about mismatches as workers are faced with changing skill requirements within sectors. In other words, the issue is not changing construction workers into nurses, but changing both construction workers and nurses from old-style workers to new-style workers.
“Old style” and “new style” here refer to jobs defined by the performance of routine tasks versus those that require the performance of nonroutine tasks. The labor market outcomes associated with this shift from old style to new style has come to be known as “job polarization.” Job polarization is the subject of a new paper by Nir Jaimovich and Henry Siu, described last week by David Andolfatto at MacroMania:
“Job polarization refers to the recent disappearance of employment in occupations in the middle of the skill distribution…
“Evidently, these classifications correspond to rankings in the occupational income distribution. Non-routine cognitive occupations tend to be high-skill jobs, and non-routine manual occupations tend to be low-skill jobs. Routine occupations—both cognitive and non-cognitive—tend to be middle-skill occupations.
“… across three decades, the share of employment in the middle of the skill distribution appears to be disappearing. Prime suspect: routine biased technological change (e.g., think of ATMs replacing bank tellers).”
The post-1980s job polarization trend has received a lot of attentions over the past decade—notable studies by MIT economist David Autor (here and here), for example—but the essential message of the Jaimovich-Siu study is the observation that trend changes are not smooth, but concentrated around downturns in the economy. Jaimovich and Siu explain:
“… job polarization is not a gradual phenomenon: the loss of middle-skill, routine jobs is concentrated in economic downturns. Specifically, 92% of the job loss in these occupations since the mid-1980s occurs within a 12 month window of NBER [National Bureau of Economic Research] dated recessions (that have all been characterized by jobless recoveries). In this sense, the job polarization ‘trend’ is a business ‘cycle’ phenomenon… Our first point is that polarization happens almost entirely in recessions.
“Our second point is that jobless recoveries are due to job polarization… jobless recoveries are observed only in… disappearing, middle-skill jobs. The high- and low-skill occupations to which employment is polarizing either do not experience contractions, or if they do, rebound soon after the turning point in aggregate output. Hence, jobless recoveries are due to the disappearance of middle-skill, routine occupations in recessions.”
A few posts back, I posed this question:
“[The pace of improvement in employment, overall and by sector,] draw a clear picture of labor markets that are underperforming by historical standards—a position that I take to be the conventional wisdom. An argument against following that conventional wisdom centers on the question of whether historical standards represent the appropriate yardstick today. In other words, is the correct reference point the level of employment or the pace of improvement in the labor market from a permanently lower level?”
The Jaimovich-Siu results really do suggest that the answer could well be the latter. That said, the levels of employment in the broad nonroutine job categories identified in Jaimovich and Siu’s paper remain below the peak levels associated with the 2001 recession—something that was not apparently true at this point in the recoveries after the 1990–91 and 2001 recessions.
“There is plenty of evidence pointing in the other direction, i.e. plenty of evidence indicating the problem is cyclical and we are nowhere near full recovery.
“With so much uncertainty remaining, the advice from Stevenson and Wolfers in a post… about how policymakers should react when they are unsure of how strong the recovery will be is appropriate:
‘… the cost of too little growth far outweighs the cost of too much. If we readily bear the burden of carrying an umbrella when there’s a reasonable chance of getting wet, we should certainly be willing to stimulate the economy when there’s a reasonable risk that doing nothing could yield a jobless generation.’
“The fact that the costs are asymmetric and what this means for policy—it should lean against the more costly outcome—seems strangely absent from policy discussions and decisions.”
It is worth noting that asymmetric costs referenced here are a matter of judgment, not theory. In fact, if the employment losses suffered through the recession are structural, stimulating the economy is exactly the wrong thing to do. (The classic exposition of this point, in math terms, was provided years ago by Michael Woodford.) In this sense, Thoma’s argument just begs the question.
And though there may be “plenty of evidence” pointing in the direction of labor market slack, there is also developing evidence of tightness directly related to the job-polarization phenomenon. From Kathleen Madigan, at The Wall Street Journal:
“The U.S. labor market is struggling with a paradox: despite an 8.3% unemployment rate, many jobs go begging.
“The Institute for Supply Management-New York said this week that 20% of its members say the shortage of skilled labor is an obstacle to business. On Thursday, the National Federation of Independent Business [NFIB] reported a rising share of small business owners who say they have jobs that are hard to fill.”
Care should be taken not to over-interpret these types of observations. Though the degree of skill shortages reported in the NFIB surveys was higher in 2011 than 2010, it is still well below prerecession levels. As I indicated in my earlier post, in the end the truth is likely to seen in the behavior of inflation. The asymmetry to which Thoma, and Stevenson and Wolfers, appeal is implicitly based on their belief that the risks of inflation are very low. With that in mind, this summary at Angry Bear of the March employment report warrants some notice:
“Recently, unit labor cost has been rising faster than prices, implying margin pressure and very weak profits. To sustain profits growth, firms have to reestablish stronger productivity growth. The weakness in March employment is a strong indicator that business is trying to rebuild productivity growth and profits growth.”
The other possibility, of course, is that businesses will try to rebuild profit growth by raising prices.
The story continues to develop. Watch this space.
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