The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.

Authors for macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.

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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."

Those sentiments have been echoed more informally by Robert Waldmann, by Andy Harless, and at Free Exchange. And they may prove to be exactly right. But as Tasci and Lindner conclude:

"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

August 18, 2010 in Business Cycles, Labor Markets | Permalink


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oh yes! "the economy starts improving, it takes time to deplete unemployment" however, no one know how much time it will take to overcome that.

Posted by: Crude John | August 18, 2010 at 11:11 PM

Does this have anything to do with structural unemployment?
Or the argument here is this seeming anomaly is entirely related to extended benefits ?
The latter seems a bit optimistic to me

Posted by: C Jones | August 19, 2010 at 09:20 AM

With all due respect your observation is pure BS. The idea that unemployment benefits lead to higher unemployment statistics is searching for an anomaly where none exist.

I've been unemployed for 2 years now, I owned my own business so I receive no unemployment benefits and am not counted in the unemployment surveys. Maybe I'm counted in the U6 numbers but not sure how they would capture my data or categorize me.

In plain English, the unemployment statistics, like most current government statistics, are woefully inadequate to capture the real employment picture in the USA.

Looking for a statistical anomaly in the unemployment data is like checking a sandbag next to the breach in the levee to see if it's adding to the problem.

Posted by: OrganicGeorge | August 19, 2010 at 10:59 AM

Mr. Altig, with all due respect, I am pretty sure all these observations by experts and highly intelectual people are a bit too narrow.

"It serves as a simple representation of how efficient labor markets are..."

Right there is the fallacy. There is no such a thing as "efficient labor markets". I know at least one case of job demand for a wind turbine producer who hasn't been able to cover his needs regarding his workforce because in the area there are no individuals with the right specialized skills. Similarly, I know of another individual who welds special steel pipes for x-ray machines and can't find a job in Miami, even when there are probably no more than 3 others that can do such job in all South Florida. Plenty of work for him in New York, though.

So the point is, jobs are localized in the vast majority of cases and that makes for an inefficient market. It is not like buyers and sellers are all in the same market and have all the information available. The mismatch is compounded now because a large number of jobs lost are of the lower skills type (say retail service) all the while the economy is moving towards a revival of manufacturing with strength in exports. Now, how long will it take to add new specialized skills to the unemployed before we may start to see a match between those have no jobs and those who are offering one?

In the long run, everything becomes efficient by force of nature. But we need to eat today and everyday.

Posted by: Boy Plunger | August 24, 2010 at 01:37 AM

Firms have also pared back on employees over the last 2 years and reorganized for efficiency. Those that are working find themselves doing the work of more than 1 person. Those with hiring authority are in no different a position. Sure, they may have job openings. But, they will only hire those that have done the exact same job recently, so as to add business value quickly. Managers today do not have adequate time to mentor a new employee. Skills that two years ago were close enough are now not enough. This may explain part of the Beveridge curve variation.

Posted by: CD | August 24, 2010 at 01:43 PM

It's hard to accept Economists refuse to tie inflation measurements to population samplings & will not explain how we are to continually grow GDP from a number reached only by years of leveraged gambling.

Posted by: bailey | August 25, 2010 at 10:58 AM

You say:

"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."

This is true and is indeed fairly obvious when one thinks about it. But that doesn't mean that the BC hasn't shifted out more than in past recessions.

One way to measure this is by estimating a Cobb-Douglas matching function and then looking at the Solow residual to get the matching function's "productivity." Stephen Williamson provides a graph of this residual for 2001 - 2010:


He doesn't show earlier recessions, but the shift for the current recession certainly looks much larger than the 2001 recession.

Posted by: Jon | August 29, 2010 at 09:46 PM

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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

August 3, 2010 in Business Cycles, Forecasts | Permalink


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I remember around December 2007, when economists gave something like a 20% chance of recession, there was a Bloomberg poll that showed the public felt we were already in one.

Interestingly, most people would say the recession has never ended, though economists confidently point to the turn to positive GDP one year ago. What if there is another downturn already starting, and the NBER committee decides it is really one large event?

Posted by: Bob_in_MA | August 03, 2010 at 05:14 PM

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.

Posted by: GHD Straighteners | August 04, 2010 at 02:39 AM

I remember around December 2007, when economists gave something like a 20% chance of recession, there was a Bloomberg poll that showed the public felt we were already in one.

Posted by: links of london | August 04, 2010 at 02:40 AM

If we can't forecast, surely this makes the case for analysis of effective design of automatic stabilisers into an interesting question?

Posted by: rjw | August 04, 2010 at 02:55 PM

My predcition for AAA corporate bond yields in 1981 was 15.48%. AAA corporate yields hit 15.49%. I was off by .01%.

It is a scientific fact that economic forecasts are mathematically infallible. All you need is the G.6 debit and deposit turnover release.

Posted by: flow5 | August 05, 2010 at 12:56 AM

The transactions concept of money velocity (Vt) has its roots in Irving Fischer’s equation of exchange (PT = MV), where (1) M equals the volume of means-of-payment money; (2) V, the transactions rate of turnover of this money; (3) T, the volume of transactions units; and (4) P, the average price of all transactions units.

The “econometric” people don’t like the equation because it is impossible to calculate P and T. Presumably therefore the equation lacks validity. Actually the equation is a truism – to sell 100 bushels of wheat (T) at $4 a bushel (P) requires the exchange of $400 (M) once (V), or $200 twice, etc.

The real impact of monetary demand on the prices of goods and serves requires the analysis of “monetary flows”, and the only valid velocity figure in calculating monetary flows is Vt. Income velocity (Vi) is a contrived figure (Vi = Nominal GDP/M).

The product of MVI is obviously nominal GDP. So where does that leave us? In an economic sea without a rudder or an anchor. A rise in nominal GDP can be the result of (1) an increased rate of monetary flows (MVt) (which by definition the Keynesians have excluded from their analysis), (2) an increase in real GDP, (3) an increasing number of housewives selling their labor in the marketplace, etc. The income velocity approach obviously provides no tool by which we can dissect and explain the inflation process.

To the Keynesians, aggregate demand is nominal GDP, the demand for services (human) and final goods. This concept excludes the common sense conclusion that the inflation process begins at the beginning (with raw material prices and processing costs at all stages of production) and continues through to the end.

The Fed first calculated deposit turnover in 1919. It reported weekly until 1941 (like M3, the series was also discontinued, in Sept. 1996). The figure “other banks’’ was used until 1996. Prior to this revision Vt included all banks located in 232 SMSA’s excluding N.Y. City. This was the best that could be done to eliminate the influence on prices of purely financial and speculative transactions. Obviously funds used for short selling do not contribute to a rise in prices.

The Fed calculates these velocity figures by dividing the aggregate volume of debits of these banks against their demand deposits.

We do know that to ignore the aggregate effect of money flows on prices is to ignore the inflation process. And to dismiss the concept of Vt by saying it is meaningless (that people can only spend their income once) is to ignore the fact that Vt is a function of three factors: (1) the number of transactions; (2) the prices of goods and services; (3) the volume of M.
Inflation analysis cannot be limited to the volume of wages and salaries spent.

To do so is to overlook the principal "engine" of inflation - which is of course, the volume of credit (new money) created by the Reserve and the commercial banks, plus the expenditure rate (velocity) of these funds. Also overlooked is the effect of the expenditure of the savings of the non-bank public on prices.

The (MVt) figure encompasses the total effect of all these monetary flows (MVt).

Posted by: flow5 | August 05, 2010 at 01:02 AM

Economist still try to conjure up learned interpretations. Now its the yield curve and its associated long term contractions and expansions of business activity, prices, etc.

“Double-Dippers Are All Wet Ignoring Yield Curve” Caroline Baum - Bloomberg – July 12 2010:

“It’s just that the yield curve, or what it represents, is possibly the best leading indicator of the business cycle”

Everyone on the FED's technical staff that thinks the money supply can be managed by using interest rates should lose their job and their pension.

Posted by: flow5 | August 05, 2010 at 11:43 AM

yes forecasting is tought. But that is why we are willing to pay lots of money for them. Trouble is, we (ie everyone) pays lots of money for those which are wrong.

Posted by: chris | August 11, 2010 at 08:27 AM

People are just people. Sometimes they are right in their forecasts, sometimes not. The most important point is to be able to acknowledge mistakes that we make. Perfection comes with practice.

Posted by: Monklet | August 16, 2010 at 08:09 AM

there are two papers one has to mention when discussing inflation forecasts.
The naive approach was first tested by Atkeson and Ohanian.
Stock and Watson published results of a comprehensive quantitative comparison of existing models.

Atkeson, A., Ohanian, L.E., (2001). “Are Phillips curves useful for forecasting inflation?”, Federal Reserve Bank of Minneapolis Quarterly Review 25, 2-11.
Bureau of Labor Statistics, (2003). “Revisions in the CPS effective January 2003”, http://www.bls.gov/cps/rvcps03.pdf

Stock, J., Watson, M. (2007). Why Has Inflation Become Harder to Forecast? Journal of Money, Credit and Banking, 39(3), 3-33.

Posted by: kio | August 19, 2010 at 02:41 AM

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