What Can the Distribution of Unemployed Job Matches, by Duration, Tell us About the Long-Term Unemployed?

“Over 40 percent of currently unemployed workers have been out of a job for over six months, the highest percentage of long-term unemployment since World War II….The story runs as follows. Before the financial crash, there were lots of not-so-useful workers holding not-so-useful jobs. Employers didn’t so much bother to figure out who they were….Then came the 2008 recession, and it was no longer possible to keep so many people on payroll….In essence, we have seen the rise of a large class of “zero marginal product workers,” to coin a term. Their productivity may not be literally zero, but it is lower than the cost of training, employing, and insuring them.”
Tyler Cowen, Jayme Lemke, Foreign Policy, 10 Percent Unemployment Forever?

“Columbia’s Charles Calomiris was practically clicking his heels on the WSJ’s video site because Bernanke more or less ruled out another bond-buying round, a QE3, and essentially said long-term unemployment in and of itself was beyond the scope of the Fed’s powers, which could only attack unemployment generally.”
Dean Starkman, CJR, On Bernanke’s Speech

“You have the 99ers. Have you heard of the 99ers?…These people, some of which, frankly, I bet you’d be ashamed to call them Americans.”
Glenn Beck, Glen Beck Show, August 2010

The Bureau of Labor Statistics just released some data that I had spent the last year coveting like it was my neighbor’s ass. Summary data on unemployment to employment flows by duration of unemployment is finally online in this report – How long before the unemployed find jobs or quit looking?  The BLS was also kind enough to sent me the monthly data unadjusted too when I asked them. Super-sweet.  This data will hopefully help us unpack this meme of the situation of the long-term unemployed.

But before that, let’s recap some structural unemployment developments. First, the BLS dramatically overstated the number of job openings throughout 2010, leading policy makers and economic commentators to discuss structural unemployment with a much better job market in mind than ever actually existed in reality. Second, data regarding a decrease in mobility turned out to have major flaws, leading to a wave of research finding little impact, and perhaps even a positive relationship, between the housing bubble and mobility. The amount of people underwater correlates much better with de-leveraging than it does with less mobility. Third, education or gender job dynamics are not sufficient conditions for explaining our jobs crisis. And fourth, our back-of-the-blog estimates based on the Beveridge Curve give an increase in structural unemployment of about 1%; really sophisticated estimates also give an estimated increase of at most 1%.  Lots of room for more action.

The Long-Term Unemployed

There’s another argument we haven’t addressed, one that comes from bits and pieces of the quotes above, that goes like this: the unemployed have bifurcated, split into a normal-ish labor force of short-term unemployed and then a large group of long-term unemployed. The economy put a lot of people into unemployment during 2008 and 2009, and they’ve never been reabsorbed into employment.

In this argument, there’s something uniquely, economically bad about the long-term unemployed.  Their marginal productivity is near zero, which is why they were fired during the Recession in the first place and why employers won’t hire them now.  Hysteresis has set in, which means that being detached from the labor force for as long as they have been makes it less likely that they can be re-employed.  They may even be bad Americans.  To whatever extent monetary and fiscal policy can help with generic, short-term unemployment, it certainly can’t help this problem of the long-term unemployed.  There’s a reason they were fired in the first place.

Hypothesis Testing

How can we use this new data to help understand whether or not this is an accurate description? This data helps us understand the distribution of successful job matches across the duration of unemployment, which will separate out short-term versus long-term unemployment.  Are firms more likely to hire those who have only been unemployed a short period of time and less likely to hire the long-term unemployed, or are they more willing to hire the long-term unemployed?

Let’s say it is 2010 and you want to hire someone. If it is true that the long-term unemployed are unemployable due to low productivity, then it is more likely you will hire someone who has only been unemployed 14 weeks or less.  This hire rate should increase against historical averages, and the percentage of jobs that go to people over 26 weeks (technical definition of long-term unemployed) or 52 weeks (those associated with losing their jobs early in the Recession)  should decrease.

What do we see?

This is straight from the first table in the BLS document here.  As we can see, jobs are much more likely to be matched to the long-term unemployed and less likely to be matched to the short-term unemployed relative to their historical averages.   Now, there are many more people who are long-term unemployed than there have been in the past, but this theory requires them to be uniquely difficult to employ as a group post-Great Recession, and that doesn’t seem to be a problem.

Let’s watch this dynamic unfold by going into the month-by-month unadjusted data.  Here it is with more duration buckets:

The long-term unemployed are more likely, and the short-term unemployed less likely, to be assigned jobs in the distribution of job matches that successfully occur Post-Great Recession

Is the issue that the labor market for those recently unemployed has become so tight – that people are finding jobs very quickly – that employers are then turning to the long-term unemployed? The distribution of people among duration buckets is very uneven – there are more people long-term unemployed – so we need to see if the short-term unemployed have become tapped from a hiring perspective.

The following is the percentage of unemployed who find a job per month divided by the total unemployed ([U->E]/[U]), by duration of unemployment, with a 6 month average (the data is unadjusted):

The difficultly of finding a job has increase for all duration groups, particularly the short-term unemployed moreso than the long-term unemployed, and has stayed that way post-Great Recession.

It’s very tough out there for the large number of long-term unemployed.  But the idea that they are ultimately unemployable doesn’t jump out at us from this data.  If monetary or fiscal policy generated more jobs, this new unemployment-to-employment by duration data tells us that a historically disproportional number of jobs would go to the long-term unemployed, and that there is plenty of slack among all duration buckets for more jobs.

I’m still playing with this data and making up my mind on some of these conclusions, so I’m very interested in what you all think.  But this is making me think we don’t need job retraining, mobility support, or other magic tricks to help the long-term unemployed as a matter of necessity; we should be focused on first exhausting the simple mechanism of creating more jobs through a mix of monetary and fiscal policy.

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12 Responses to What Can the Distribution of Unemployed Job Matches, by Duration, Tell us About the Long-Term Unemployed?

  1. Davis X. Machina says:

    Folks have a moral point to make, and are willing to enlist economics, even in the teeth of the evidence to help them make it.

    The challenge facing us is that only economists go out the door each morning into an economy.

    The rest of us go out the door into a team sport-cum-morality play where ideas like ‘desert’ and the distinction between the ‘deserving poor’ and the ‘undeserving poor’, not to mention team spirit — Go, Team Red!, Go Team Blue — are actually driving policy.

  2. Josh Koenig says:

    This is great analysis.

    Just thinking out loud, my own narrative theory of much of this parallels with the “Structural Unemployment” line, but instead of taking the position that there’s something wrong with the workers, I believe there’s just an enormous amount of wasted energy (or non-energy) within most organizations.

    Time and again I’ve seen amazingly talented and energetic human beings ground down to marginal plodders (or less) by sustained exposure organizational disfunction. Management may flatter itself by thinking they’re cutting “dead weight” in terms of non-productive people, but far more often what they’re doing is cutting non-productive positions.

    I saw this inside economically well-insulated organizations (e.g. a large private university with a healthy endowment): financial crisis is an excuse to restructure. It has less to do with individuals who were underperforming, and more to do with making shifts in how operations worked.

    Moral scolding of the long-term unemployed is certainly wrongheaded, but I honestly don’t think a bit more demand will bring unemployment down that much. There’s a massive existential crisis looming for global capitalism as more and more of the world comes online: are there actually 2 billion jobs worth doing? I kind of don’t think so. The story of the 21st century will be about how we deal with this (or not).

  3. Neil in Chicago says:

    It may not be officially available at all, but you have left out a critical variable.
    That is, age distribution.
    If one of the things going on is the replacement of “old”, experienced expensive workers with cheap young workers, then the various curves on your graphs represent demographics more different than they look. Anecdotally, I have no doubt that this is a significant factor in the mean duration of unemployment approaching twice the median duration for U6.
    (I follow a few blogs and BLS’ monthly U6 numbers; I’m no professional.)

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