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Home Publications Blogs CEPR Blog The Beveridge Curve and Structural Unemployment

The Beveridge Curve and Structural Unemployment

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Written by Dean Baker   
Tuesday, 01 January 2013 17:12

There is a whole industry of economists and policy types who are incredibly anxious to find evidence of structural unemployment. The reason is that structural unemployment implies a mismatch of the available jobs and the skills of the unemployed.

This is important because if our unemployment problem is structural then simply using macroeconomic policy to generate more demand won't be of much help. If we want to get people back to work we have to get them the right skills or in the right place (there can be a locational mismatch as well) for the jobs that are available. That is a very difficult and much more complicated process than just spending money.

Recently some proponents of the structural unemployment view of the economy have been highlighting an outward shift in the Beveridge Curve. The Beveridge Curve relates unemployment to the vacancy rate (the number of job openings divided by the number of jobs). In general, higher rates of unemployment are associated with lower vacancy rates. However, in the last couple of years there has been some increase in the vacancy rate without as large a drop in unemployment as would ordinarily be expected. This is taken as evidence that employers are having difficulty finding workers with the necessary skills in spite of the large number of unemployed workers. This is the story of structural unemployment.

A new paper from the Boston Fed by Rand Ghayad and William Dickens looks at this shift in the Beveridge Curve more closely. It finds a very interesting story. If we look at the long-term unemployed (people who have been out of work for more than 26 weeks) we see this shift clearly.

The current vacancy rate of around 2.5 percent used to be associated with rates of long-term unemployment of around 1.0 percent. Now it is associated with rates of long-term unemployment of close to 3.0 percent. That is a substantial outward shift that would be consistent with a large rise in structural unemployment. However if we just look at the short-term unemployed, workers who have been unemployed for fewer than 27 weeks, we don't see the same story. There is no evidence of any shift whatsoever. In fact, a 2.5 percent vacancy rate appears to be assoicated with a slightly lower rate of short-term unemployment than was true before the downturn. This pattern should be troubling for the proponents of the rising structural unemployment view.

Some folks may look at these curves and claim that the long-term unemployed are the misfits, so it should not be surprising that we only see the shift in the Beveridge Curve among this group. There are two problems with this story. First, when we saw shifts in the Beveridge Curve in the past it occurred among both the long-term and short-term unemployed. The other problem is a simple logical one. The long-term unemployed had all previously been short-term unemployed. If this group has a chronic mismatch with the available jobs then it should also have shown up as an outward shift in the Beveridge Curve for the short-term unemployed when they had been unemployed for less than 27 weeks. Clearly this story doesn't work.

There is an explanation having to do with extended unemployment benefits. There are two ways this can work. First, because workers know that they can get benefits for much longer than the normal 26 weeks they are being more choosy about accepting jobs. While there is likely some truth to this, it cannot be too large a factor because this should also affect behavior among workers in their first 26 weeks of unemployment. In other words, if workers willingness to accept a job offer is influenced by the fact that they can get benefits for a longer period of time, then we should also expect to see an outward shift in the Beveridge Curve for the short-term unemployed. Since we don't, this explanation doesn't fit the data.

There is another way in which extended benefits can affect the behavior of workers. In order to qualify for benefits workers must continue to look for work. This could mean that many workers who would have otherwise given up looking for jobs after 40-50 weeks of unemployment keep looking in order to continue to qualify for benefits. Insofar as this is the case, extended benefits are not keeping people from being employed, but rather keeping them from leaving the labor market and therefore raising the unemployment rate.

The findings of Ghayad and Dickens would be consistent with this view. In this case we are not looking at structural unemployment in any meaningful sense. The extended duration of unemployment benefits are not keeping people from working, they are just increasing the number of people counted as unemployed. (Jesse Rothstein has found that the vast majority of people who see their benefits expire leave the labor force; they do not find work.) 

It is also possible that the shift in the Beveridge Curve could be due to a change in employer behavior. If employers see a large pool of unemployed workers and see little urgency in hiring due to weak demand, then it is plausible that they would spend more time choosing among job applicants. It doesn't make sense to be picky if there is little reason to believe that you can find better applicants, however with a large pool of unemployed it is more likely that a better applicant will be available if an employer waits.

This employer behavior story is also not consistent with a structural unemployment explanation for the shift in the Beveridge Curve. While a full explanation for this outward shift will require more research, Ghayad and Dickens' work shows clearly that there is not a simple structural unemployment explanation for the shift.

 

 

Comments (4)Add Comment
long term unemployed data
written by watermelonpunch, January 01, 2013 8:22
What stands out to me the most is the "employer behaviour" about being picky & leaving jobs open for a long time. I've read that this is the case. And that can certainly skew the open jobs data.
I think of the book "Why Good People Can't Get Jobs" by Peter Cappelli
I'm definitely a believer that companies are allowing automated systems to sift through applications in such a way that weeds out the very people who would be qualified, and also that employers have come to expect not to have to train anybody for their jobs.
And I think that some people are considering that "jobs skills mismatch" when in reality it's NOT a job skill mismatch, it's a managerial flaw for some companies.

But my question is... How about long-term unemployment discrimination & its effects on these data sets?

There's ample evidence that the long-term unemployed are disadvantaged. It's no secret that many employers simply won't hire people who have been unemployed for a length of time.
But maybe I'm wrong that it has a great impact on anything...

Still, let's just assume for sake of argument that this is definitely true, that most employers won't hire someone who's been unemployed for more than 27 weeks.

Would that effect these data? And if so, how so?
clarification
written by watermelonpunch, January 01, 2013 8:29
I realize now upon re-reading that this might not be clear:
And I think that some people are considering that "jobs skills mismatch" when in reality it's NOT a job skill mismatch, it's a managerial flaw for some companies.


What I mean is that job mismatch in reality would be something like we need nurses & engineers, and most of the population is trained in carpentry and agriculture.
That's what structural means to me.
I think sometimes what it means to mismanaged companies is that they need people trained in electronics sales, and the all the people that are applying have a background in car sales or machining tools sales. Which obviously to me that doesn't imply a jobs skills mismatch. It's a training / experience mismatch, that can't be cured by getting a 4 year degree in electronics just to get a low paying sales job behind the counter at wireless kiosk at the mall.
Two way deficit?
written by Bob Spencer, January 02, 2013 6:23
It makes sense that the economy is not generating enough jobs and many of the jobs only provide an upgrade from unemployed to underemployment.

At the same time, we have a "structural" problem that existed even during the bubble times. I used to live and work in Virginia, and I happen to know that the high school graduation rates had been near only 50% in most of the state's larger cities. That number appears to have actually improved to better than 60% in the same cities. http://www.doe.virginia.gov/st...able05.pdf

My personal experiences in these cities is that easily 40% of the work force is not prepared to be particularly productive. The drop out rate is only one symptom of a weak labor force.

Now, we obviously have a shortage of jobs and we also have a shortage of a quality workforce.

I don't see much written about the need to develop our workforce because of issues that have existed for generations.
jobs mismatch? or society failure?
written by watermelonpunch, January 03, 2013 3:32
@ Bob Spencer

What you describe doesn't sound like structural unemployment to me. What you describe sounds like a failure of society.

Or are you saying that it's structural because you think a 50% high school graduation rate would be "OKAY" in say, an agrarian society?

And then if the issue is education... why are so many people with not only a high school education, but a higher education, increasingly in jobs that don't require such education?
I could say that my spouse personally knew someone with a phD working at a factory on an assembly line. And there seem to be a lot of people working in jobs for which they have more education than needed.
But the reports generally out there support this too...

So I'm not sure I think even a failure of society to adequately educate 50% or 40% of its citizens is of more weight than just... a shortage of jobs.

After all, if all those college graduates working low wage jobs, were not in jobs requiring no education, there would be more room for the high school drop-outs in the work force.

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