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August 18, 2010
Just how curious is that Beveridge curve?
A few weeks back I made note of the following:
"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."
The focal point of that comment was the so-called Beveridge curve described by the Cleveland Fed's Murat Tasci and John Lindner as follows:
"The Beveridge curve is an empirical relationship between job openings (vacancies) and unemployment. It serves as a simple representation of how efficient labor markets are in terms of matching unemployed workers to available job openings in the aggregate economy."
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 with the Beveridge curve:
(A monthly version of this picture can be found in the JOLTS graphs and highlights published on the BLS Web site.)
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."
"Firm conclusions will only be able to be drawn as more data are generated."
By Dave Altig, senior vice president and research director at the Atlanta Fed
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August 03, 2010
What makes forecasting tough
Bloomberg's Caroline Baum recounts her recent conversation with the Atlanta Fed's own Mike Bryan under the headline For Good Economic Forecasts, Try Flipping a Coin:
"How do economists fare when it comes to real forecasting, to predicting [gross domestic product] GDP growth and inflation one year out? About as good as a coin toss, according to Bryan's research. Less than half the economists did better than the naive forecast, which is based on no understanding of the economy and merely assumes next year's outcome will be the same as this year's. It's what you'd expect if the results were purely random."
A case in point could be found yesterday on Bloomberg, which featured a "chart of the day" that looked something like the one below (though I've updated the data for manufacturing inventories, given today's factory orders report):
The chart was accompanied by this commentary:
"U.S. business inventories are so low relative to demand that any increase may act as a catalyst for larger companies to add workers, according to Nicholas Colas, chief market strategist at BNY ConvergEx Group."
A few days back, in The Wall Street Journal, you could find this:
"Until recently, businesses had helped supercharge economic growth by restocking inventories. Now the oomph from inventories is waning.
"In the second quarter, the change in private inventories added slightly more than one percentage point to the 2.4% increase in gross domestic product from the first quarter, measured at a seasonally adjusted annual rate, the Commerce Department said Friday.
"That is a big change from the first quarter, when inventory-building contributed 2.6 percentage points to GDP growth of 3.7%, and the fourth quarter of last year, when it contributed 2.8 percentage points to GDP growth of 5%....
"But Friday's report suggests companies are nearly done restocking their shelves.
" 'Our sense is current inventories are about where they need to be globally, both in industrial distribution and with the large North American retailers,' John Lundgren, chief executive of Stanley Black & Decker Inc., said in a July 21 call with analysts discussing the tool and hardware maker's second-quarter results."
But, on the same topic, Seeking Alpha opined:
"Inventory increases added 1.05% to second quarter GDP. Based on the annual revision, they added 2.64% to first quarter GDP or 71% of the total increase. Inventories were also responsible for approximately two-thirds of the GDP increase in the fourth quarter of 2009. The entire economic 'recovery' has essentially been an inventory adjustment [emphasis theirs]. This does not bode well for the future."
So one analysis suggests that the latest readings on inventories portend a boost to GDP, one foresees a drag on GDP, and yet another divines that inventories are basically played out as an economic story for the balance of the year.
Again from the Baum piece:
"Bryan said it's not just about getting the number right. 'It's about the narrative.' "
For comparison, it's also useful to take a longer look at what effect inventories have on GDP growth coming out of a recession; see the graph below. It charts the percentage point contributions of various components to real GDP growth in the first four quarters following the end of a recession (the current recession is assumed to have ended in second quarter of 2009). I've shown on the graph the percentage contribution of inventories to the last seven recoveries, beginning with the one in 1971.
Regarding the point made in Seeking Alpha, inventories have contributed around 70 percent to the economic recovery recently, but in the recovery that began in 2002 inventories contributed 75 percent in the first four quarters. So the last two recovery periods stand out for large inventory components. But looking across the data, it's hard to say what an ordinary inventory contribution would be. Regardless of whether inventories are an unusually large part of this recovery, in absolute levels the scale of the recent inventory cycle—the initial liquidation and the subsequent restocking—has been unprecedented.
By Andrew Flowers, senior economic research analyst in the Atlanta Fed's research department
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