The Bureau of Labor Statistics reports:
BLS: The Beveridge Curve: The... graph plots the JOLTS job openings rate against the CPS unemployment rate. This graphical representation of the relationship between the unemployment rate and the vacancy rate is known as the Beveridge Curve, named after the British economist William Henry Beveridge (1879-1963). The economy’s position on the downward sloping Beveridge Curve reflects the state of the business cycle.
During an expansion, the unemployment rate is low and the vacancy rate is high. During a contraction, the unemployment rate is high and the vacancy rate is low. The position of the curve is determined by the efficiency of the labor market. For example, a greater mismatch between available jobs and the unemployed in terms of skills or location would cause the curve to shift outward.
From the start of the recent recession in December 2007 through the end of 2009, the point on the curve moved lower and further to the right as the job openings rate declined and the unemployment rate rose. In 2010, the point moved up and to the left on the curve as the job openings rate increased and the unemployment rate decreased.
In January 2011, the job openings rate edged down to 2.1 percent and the unemployment rate declined to 9.0 percent.
David Altig wrote last August:
macroblog: Just how curious is that Beveridge curve?: Since the second quarter of last year, the unemployment rate has far exceeded the level that would be predicted by the average correlation between unemployment and job vacancies over the past decade...
And then followed up with:
Since my last post, the U.S. Bureau of Labor Statistics (BLS) published the June edition of its Job Openings and Labor Turnover Survey (JOLTS). Just as not much changed in June relative to May, either with respect to job openings or the unemployment rate, not much changed.... One of the observations made in my previous post was that the apparent shifting of the Beveridge curve—in other words, the observation that given recent experience the number of unemployed individuals seems high relative to the number of available jobs—might be explained by extended unemployment benefits, but only if you are willing to accept estimates of the policy's impact that are on the high end. I referenced a few Federal Reserve papers—here and here—but they only included estimates on the lower end. Several people have asked (in the comments section of my earlier post and in private e-mails) where the higher-end estimates come from. One of these is from an article titled "The Economic Effects of Unemployment Insurance" by Shigeru Fujita, which is forthcoming (but not yet published) in the Philadelphia Fed's Business Review. (Shigeru estimates that extended unemployment benefits raise the unemployment rate by 1.5 percentage points, enough to explain the lion's share of the Beveridge curve shift.)
Tasci and Lindner, in the article mentioned earlier, offer up a few other observations. First, in the last several months labor market statistics have in general been distorted by the entry and exit of significant numbers of temporary Census workers. Second, it does appear to be the case that the current rise in the unemployment relative to job openings is just a standard characteristic of the early phases of a recovery. On this point they provide this chart...
along with this explanation:
One important observation is that a longer-term look at the Beveridge curve shows that the dynamics we have seen recently are not an exception, but are common during the recovery phase of business cycles. As the economy starts improving, it takes time to deplete unemployment, even though job openings are relatively quick to adjust.
Hence, cyclical changes may not necessarily present themselves as... a neat movement along the curve. During and after recessions in the postwar period, the Beveridge curve has generally followed a pattern of shifting to the right during a recovery. One potential reason for this could be that even though some unemployed workers start filling the available job openings, workers who had left the labor force might get encouraged by the recovery and start looking for a job, thereby keeping the unemployment high. While the Census may have skewed the data for this recovery, the path of the curve going forward looks poised to follow in the footsteps of previous recessionary periods...
That still seems to me to be state-of-the-art.
Which makes me wonder what data Narayana Kocherlakota is looking at when he writes:
Kocherlakota: In the past three years, the Beveridge curve has shifted in the United States in a way that suggests that labor market matching efficiency has declined...
Time to go reread Peter Diamond again:
Is there really a widespread difficulty in hiring in some industries or locations? I have not seen such reports. Thus we may be having shifts in the Beveridge Curve and the matching function that do not signal change for the underlying functioning of the economy once a recovery is well-established. That is, the pattern would return to normal after a sufficient rise in aggregate demand, apart from the lingering effects of long-term unemployment....
[W]hatever one’s view on the magnitude of recent slippage in matching efficiency, more education, better education, good retraining all make for a more productive labor force and, done well at a reasonable cost, are policies to pursue. And carefully evaluated experiments in helping the long-term unemployed get and hold jobs seem likely to be worthwhile. Indeed a time of high unemployment is likely to be a time when further education is less socially costly by using time that would otherwise not be so well spent. The policy debate is not about whether to do more on the structural side; it is about what to do on the aggregate demand side, which is particularly an issue now with concern about projected long-run debt levels.
Second, for the current moment, the argument about the aggregate demand side is academic, in the negative sense of the word. Current estimates I have seen of how much of the increase in unemployment from a few years ago is “structural,” rather than due to inadequate aggregate demand, still leaves enough need for aggregate demand stimulation that it is clear what direction is needed for further policies.
Third, I am skeptical of the value of attempting to separate cyclical from structural unemployment over a business cycle.... The tighter the labor market and the more valuable the filling of a vacancy, the more a firm is willing to hire a worker who is a less good match, who may need more training.... [A] worker who might be viewed as structurally unemployed, as facing serious mismatch in the current state of the economy, may be readily employable in a tight labor market. The common practice of thinking about the extent of unemployment as a sum of frictional, structural and cyclical parts misses the point.... [D]irect measures of frictional or structural unemployment... dependent on the tightness of the labor market... have limited relevance for the role of demand stimulation policies. The idea that the US economy is not adaptable and capable of dealing with the need for skills and jobs to adapt to each other is peculiar, given the long history of unemployment going up and down. When the labor market is tight and firms have trouble finding workers, they reach out to places they have not looked before and extend training in order to find workers who can fill their needs. Supporting current stimulus policies as very good for the economy is entirely compatible with taking care to avoid future inflation.
 Dickens, 2010 p. 10, notes: “Figure 3 presents the ratio of vacancies to unemployment in 8 different industries. While it is possible to discern the increase in vacancies over recent months in some industries, the ratio remains substantially depressed in all industries. What we do not see is any industries with high vacancy unemployment ratios. This suggests that it would be hard to make a case for structural mismatch being a major problem today.” In personal correspondence, he reports on ongoing work with Bob Trieste that looked at geographic mismatch indices based on both the JOLTS and the Conference Board's new help wanted on line data. They explored occupational mismatch, geographic mismatch at a much more detailed level than in the original paper, and industry mismatch. None show any evidence of increasing mismatch coincident with the apparent outward shift in the Beveridge Curve. Regis Barnichon, Michael Elsby, Bart Hobijn, and Ayşegűl Şahin (2010) “decompose the recent deviation from the Beveridge curve ... [and] find that most of the current deviation from the Beveridge curve can be attributed to a shortfall in ... hires per vacancy. This shortfall is broad-based across all industries and is particularly pronounced in construction, transportation, trade, and utilities, and leisure and hospitality. Construction alone accounts for more than a third of the Beveridge curve gap.” P 1.