The trend is your friend (until it ends)

My previous post advertising Jim Bullard's recent speech seems to have generated a lot of discussion; see Mark Thoma, Scott Sumner, David Beckworth, Tyler Cowen, Noah Smith and, yes, even Princeton Charming himself.

Most commentators are rather negative on Bullard's view that a permanent (persistent) negative wealth shock should be associated with a permanent (persistent) decline in the level of real GDP, leaving it's long-run growth rate largely intact. Some question the logic of Bullard's explanation, but it is not inconsistent with what happens in a standard RBC model where productivity follows a random walk with drift. I'm not sure if that's what Jim had in mind (I will find out in due course), but just thought I'd put it out there. (Alternatively, see Steve Williamson.)

What I would like to talk about here is my own take on the matter, which is I think is subtly different from Jim's. In my previous post, I made the following comment:

I think that Bullard makes a persuasive case that the amount of household wealth evaporated along with the crash in housing prices should likely be viewed as "permanent" (highly persistent) negative wealth shock. Standard theory (and common sense) suggests a corresponding permanent decline in consumer spending (with consumption growing along it's original growth path). The implication is that the so-called "output gap" may be greatly overstated by conventional measures.

I think that the crossed out part above was a mistake in light of the theory I had working in the back of my head when I wrote that paragraph. But otherwise, what I said is fine. As long as you understand the theory; which, of course, I should have explained. Let me do so here.

It is probably fair to say that when most people take a look at a time-series for real GDP, in their mind's eye they decompose the time-series into a linear trend and deviations from linear trend. It is a perfectly natural thing to do. But that doesn't make it correct.

Implicit in any decomposition is a theory. The common decomposition assumes that trend (or potential) GDP follows a smooth upward path. Trend is labeled "supply." Actual GDP (the thing we observe) obviously fluctuates around trend (something we do not observe). And since trend is "supply," it follows that actual GDP must be "demand;" and that cyclical deviations from trend (the output gap) are caused by "demand shocks." A lot of people seem to take all this as self-evident truth. Unfortunately, the "right" data decomposition is not as obvious as people sometimes like to believe.

What is another way to decompose time-series data? Personally, I find Jim Hamilton's regime-switching model an interesting way to interpret the pattern of economic development. The basic idea here is that growth is driven by productivity, and that productivity growth is subject to infrequent, but random and persistent, regime changes. (Regime changes are possible along other dimensions, of course.) Sometimes we are in a high-growth regime, and sometimes we are in a low-growth regime--a view not inconsistent with Schumpeterian growth dynamics. And while these growth shocks are not likely the only reason behind our cyclical ups and downs, this is the type of shock I had in mind when I envisioned the large negative wealth shock mentioned by Bullard.

In particular, as Joseph Zeira has shown (Informational Overshooting, Booms and Crashes, JME 1999), the switch from a high to low growth regime generates equilibrium asset price dynamics that any econometrician is likely to interpret as a price bubble that booms and then crashes. The price crash (and consequent loss of wealth) however, is driven entirely by economic fundamentals (I suspect that one could generate something similar in a model with multiple equilibria and self-fulfilling prophesies). I discuss this possibility in a bit more detail here: The 2005 Real Wage Shock. In this latter post, I raised the question of whether the apparent slowdown in real wage growth may have led property owners to revise downward their estimates of future rental income, precipitating the crash in real estate prices.

Now, maybe all this sounds a little crazy to you and, of course, perhaps it is. But it is interesting to note that some recent evidence on U.S. productivity growth, reported by James Kahn and Robert Rich, seems to corroborate my hypothesis: The Productivity Slowdown Reaffirmed (Liberty Street Economics, Sept. 2011). Here is a snippet from their opening paragraph:

Economists generally agree that productivity is the primary ingredient for sustainable growth in GDP and wages. The August productivity data release provided some clarification regarding trend--or long-run--GDP growth, but the news was not good: Following a resurgence of strong productivity growth in the late 1990s and early 2000s after nearly a quarter-century of slow growth beginning in 1973, the latest reading from a trend tracking model now indicates that slow productivity growth returned in 2004.

OK, so I was off by a year. ;)

I would like to mention some related empirical work by Marco Lippi and Lucrezia Reichlin, Diffusion of Technical Change and the Decomposition of Output into Trend and Cycle (ReStud 1994). The authors argue against modeling productivity growth as a random walk, suggesting that it makes more sense to think of technology diffusing according to an S-shaped dynamic.  Of course, the S-shaped dynamic gives rise to the low/high/low growth regimes I mentioned above. The authors conclude:

Thus we have found what might be called a dynamic tradeoff: either we assume rich dynamics for the cycle and consequently a trivial trend, or else we assume more complicated dynamics for the trend, consequently impoverishing the dynamics of the cycle. All intermediate cases are rejected by the data. 

Interesting, don't you think? At the very least, I think it suggests there is some room for different interpretations of the cycle and that the relative merits of these different interpretations should be the subject of an open and respectful debate (I believe that this was the main motivation for Bullard's speech).

Why is understanding the true nature of the decomposition important for monetary policy? Kahn and Rich provide us with one answer to this question:

It is widely believed that the difficulty of detecting a change in trend growth contributed significantly to the economic instability of the 1970’s, as policymakers were unaware of the slowdown in productivity growth for many years, and only much later were able to date the slowdown at approximately 1973. This resulted in overestimating potential GDP (at least so the conventional wisdom goes) and setting interest rates too low, and double-digit inflation followed not long after.  

It is not surprising to discover that the memory of that event weighs on the mind of some Fed presidents. Now, it happens to be my personal opinion that the inflation threat this time around is overstated (largely because this time there is a huge worldwide demand for USD and US treasury debt that is keeping inflation and interest rates low; see here). But what I, or anyone else, thinks is beside the point I am trying to make here. One of  the Fed's most important jobs is to keep inflation expectations anchored. History shows that inflation expectations can change suddenly and capriciously. Whether one likes it or not, it is the job of Fed presidents to think about this possibility, and to voice concern if they see a danger of repeating past policy mistakes.

If we are indeed entering into 1970s era of relatively slow productivity growth, then current CBO measures of the output gap are likely overstated, and further LSAPs are probably not warranted. This does not mean, however, that there is no output gap, or that there should be no policies directed to those who are having a difficult time in the labor market. As I discuss here, there is considerable variation in regional labor market conditions and it is not at all clear that "looser" monetary policy is the tonic we want to employ (assuming that it will have any effect at all in current conditions). In particular, there may be ample scope for regional fiscal policies, education and retraining programs, or other more direct measures that are outside the realm of monetary policy.

Update: Related Links

Bleak Apologists (The New Arthurian Economics)
The Asset Price Decline IS a Negative Productivity Shock (Canucks Anonymous)
Chucking the Solow Growth Model Cont. (Noahpinion)
The Output Gap: Still Negative (hjeconomics)

What output gap?

James Bullard

In case you haven't seen it, you may be interested in this speech given recently by Jim Bullard, president of the St. Louis Fed: Inflation Targeting in the USA.

This speech is really about how to interpret the recent performance of the U.S. economy. Is the conventional interpretation, that we are far below "potential" GDP owing to "deficient demand," the correct view? Or should we instead be thinking in terms of a large negative shock to "potential" GDP, with unemployment returning slowly to its natural rate, according to its normal dynamic (see here)?

I think that Bullard makes a persuasive case that the amount of household wealth evaporated along with the crash in house prices should likely be viewed as a "permanent" (highly persistent) negative wealth shock. Standard theory (and common sense) suggests a corresponding permanent decline in consumer spending (with consumption growing along it's original growth path. This part is incorrect given the model I have in mind here.) The implication is that the so-called "output gap" (the difference between actual and "trend" GDP) may be greatly overstated by conventional measures.

The view that one takes here is likely to influence what one thinks about monetary policy. The conventional view seems to support the Fed's current policy of keeping its policy rate close to zero far into the future. In his speech, Bullard worries that this may not be the appropriate policy if, in fact, potential GDP has experienced a level shift down (or, what amounts to the same thing, if conventional measures treat the "bubble period" as the economy being at, and not above, potential). Among other things, he says:

But the near-zero rate policy has its own costs.  If we were proposing to remain near-zero for a few quarters, or even a year or two, one might argue that such a policy matches up well with the short-term business cycle dynamics of the U.S. economy.  But a near-zero rate policy stretching over many years can begin to distort fundamental decision-making in the economy in ways that may be destructive to longer-run economic growth.  

Precisely how such a policy "distorts fundamental decision-making" needs to be spelled out more clearly (though he does offer a couple of examples that hinge on a presumed ability on the part of the Fed to influence long-term real interest rates). I am sure that many of you have your own favorite examples.

At any rate, I think this is a nice speech because it challenges us to think about the recent U.S. recovery dynamic in a different way. And if recent history has shown us anything, it's shown that we shouldn't grow complacent over what we think we understand.

Update available here: The trend is your friend (until it ends)

Update: The "terrifying" James Bullard offers a reply to Tim Duy here.

Using Beveridge curve dynamics to identify cyclical and structural shocks

I recently gave a short presentation to the Board of Directors of the Louisville branch of the St. Louis Fed. Following my presentation (which stimulated a lively discussion), I had the opportunity to listen to each member report on local economic conditions from different parts of Kentucky. Two themes stood out. The first was how "an air of uncertainty" along a variety of dimensions had "frozen" investment plans (with the apparent exception of younger entrepreneurs, who probably do not know any better-jk). The second was the unfilled demand for highly skilled, specialized workers (primarily in manufacturing).

I want to focus on the second theme here. In some sense, it is really amazing that firms are struggling to find qualified workers in an era of 8% unemployment. The Financial Times recently ran a piece on the subject: Skills Gap Hobbles US Employers, and I have to say that Mr. Greenblatt below would have fit right in at my BOD meeting:

Drew Greenblatt has been looking for more than a year for three sheet-metal set-up operators to work day, night or weekend shifts. 

The president of Marlin Steel Wire Products, a company in Baltimore with 30 employees, Mr. Greenblatt says his inability to find qualified workers is hampering his business' growth. "If I could fill those positions, I could raise our annual revenues from $5m to $7m," he says.  

He is offering a salary of more than $80,000 with overtime, including health and pension benefits. Yet in spite of extensive advertising,  he has had no qualified applicants. He is trying to train some of his unskilled staff but says none has the ability or the drive to complete the training. 

This quote identifies two problems. The first is what economists call "skills mismatch" caused by a "structural" shock. The second, that some workers are unwilling and/or unable to upgrade their skills is another matter that deserves attention, but is something that I will leave aside here. 

  
Apart from anecdotal evidence, how does one go about measuring "skills mismatch caused by structural shock?" One idea, initially proposed by Abraham and Katz (JPE, 1986), is to use the comovement to in vacancy and unemployment rates to identify "cyclical" and "structural" shocks. 

I put those terms in quotes because there are no set definitions for them. I like to think of a cyclical shock as an event that makes it more or less profitable to find the same kind of worker for the same kind of job. And I like to think of a structural shock as an event that makes it more or less profitable to find a different kind of worker for a different kind of job. 

Anyway, the Abraham and Katz idea is that one would expect cyclical shocks to trace out a stable, negatively-sloped Beveridge curve. That is, one would expect the job-vacancy rate and the unemployment rate to move in opposite directions.  A structural shock, by contrast, is expected to move vacancy and unemployment rates in the same direction. The idea here is that it is now more difficult to find the right kind of worker, so that even greater levels of recruiting intensity is likely to be associated with higher unemployment rates. 

The FT article cited above uses this idea in the diagram to the right (together with the results of a Kaufman poll of entrepreneurs) to suggest that the high U.S. unemployment rate is primarily the consequence of "structural" factors. 

Here is what the U.S. Beveridge curve looks like from May 2005 - November 2011 (The vacancy rate is computed from the Conference Board's help-wanted-online data, which is available from 2005 only).

As the HWOL measure of job vacancies is available at the city level, Constanza Liborio and I thought it might be interesting to see how job availability varies across major U.S. metropolitan areas and how job vacancy rates correlate with regional unemployment rates before and after the beginning of the most recent recession.

Specifically, the exercise we perform is as follows. Consider a major U.S. metropolitan area. Compute the average job vacancy rate and unemployment rate for this metropolitan area over the prerecession period May 2005 – November 2007. Recalculate these averages since the beginning of the last recession, December 2007 – November 2011. Next, compute the change in the vacancy rate and unemployment rate across these periods. Perform this exercise for a set of the largest metropolitan areas in the U.S. 

The results are displayed in the following figure.

Not surprisingly, we see that the unemployment rate in all these metropolitan areas went up since the recession began.  However, the same is not true of job vacancy rates (that is, not all vacancy rates went down, as one might have expected). Specifically, while we observe the typical Beveridge curve dynamic in many jurisdictions (suggesting that cyclical factors are dominant), we also observe vacancy rates remaining relatively stable, or even rising, in several others (suggesting that structural factors are dominant). 

So the tentative conclusion here is that the relative importance of cyclical vs. structural factors appears to vary across regions. To the extent that monetary policy is an effective stabilization tool, it cannot be expected to impact all regions of the country equally. In many regions, localized fiscal policies (education and training subsidies, etc.) may prove to be a more direct and effective tool.
Related story:
More Workers Moving for Out-of-State Jobs

Alien Employers or: How I Learned to Stop Worrying and let the World Run a Current Account Surplus

Meet your new boss.

Back when the Greek crisis was just breaking, I remember having my morning coffee, still half asleep, TV turned on in the background, when I heard a news reporter ask an interesting question. I put my coffee down and turned to the TV. The Parthenon was in the background, communist banners were draped about, and small smokey fires burning here and there. And the reporter, standing excitedly in the middle of all this, rather earnestly asked what I thought was a very good question: Why should Germany even consider bailing out Greece? 

Then, with hardly a pause, he breathlessly began to explain why. His answer went something like this...

"Why?! Let me tell you why, people..." [turns head to the left] "As I look over here, I see and Audi and a BMW..." [turns head to the right] "...and as I look over there, I see a Mercedes and a Volkswagen!" [turns to camera--big light bulb flashing over his head] "Greece is an extremely important export market for Germany!"

Well, as the following diagram shows, this certainly does appear to be the case (source):

So as far as I can gather, what the fellow is trying to tell us is this. The Germans should forgive Greeks their debts because, well, how else will the Greeks continue to afford importing German-made cars? After all, it is the Greek consumer that is selflessly keeping the German autoworker employed. Moreover, it has been a fine recipe for keeping German unemployment low, and growing German wealth. Yes, that's right...wealth in the form of...well, you know...grade A assets, like Greek government bonds.

Now where on earth might a fellow get an idea so bizarre as this? Well, how about here: Germans and Aliens (Paul Krugman):

But the Germans believe that their own experience shows that austerity works: they went through some tough times a decade ago, but they tightened their belts, and all was well in the end. Not that it will do any good, but it's worth emphasizing that Germany's experience can only be generalized if we find some space aliens to trade with, fast. Why? Because the key to German economic affairs this past decade has been a truly massive shift from current account deficit to surplus. 

Now, other countries within Europe could emulate Germany's past if Germany herself were willing to let its current account surplus vanish. But it isn't, of course. So the German demand is that everyone run a current account surplus, just like they do -- something that would only be possible if we can find someone or something else to buy our exports. It remains remarkable to see with how little wisdom the world is governed.

Now, I'm not sure whether any German really has made an explicit demand for all countries to run current account surpluses. But if anyone did, it would clearly be silly. The current accounts of all countries must necessarily sum to zero; at least, in the absence intergalactic trade.

But then, that sort of gave me an idea. Why not a world current account surplus?  What is an account, anyway? It's just a book-entry object. Let's give the account owner a proper name. And what's in a name? May as well call the account holder "Space Alien," with a "local" delivery address, say, the Pacific Ocean.

Next step. Contract some agency to print up Space Alien bonds, rate them AAA, then use them to acquire goods from all over the world, including ocean vessels. That should lower world unemployment. Then load the vessels with the newly purchased cargo, sail them out to their delivery point (the mid Pacific, say), and sink them all. (This last step is absolutely necessary, as sending the goods to any country on earth will mean job-killing imports for that country, jeopardizing their current account surplus).  Alas, the Space Aliens will ultimately have to default on its debt but, you know, who really cares? Just means more work is needed to replenish our lost wealth.

Now, if you think this sounds a little loopy, let me direct you to this: Fake Alien Invasion Would End Economic Slump.

Of course, this is all just a variation of the old Keynesian prescription of employing people to dig up holes and fill them up again. And, contrary to what you may be thinking, the purpose of this post is not to argue against the ability of such a program to increase net employment. What I want to question instead is why running a current account surplus is necessary for all this hocus pocus to work? 

Here's an idea. Instead of exporting vehicles to Greece, why don't German car manufacturers ship their cars to domestic German residents instead? The domestic purchasers could pay for the cars by issuing fake paper, just like their foreign counterparts. And when the time comes to default, well, at least all the BMWs, Audis, Mercedes, and Volkswagens will be residing on German soil. 

The regional dispersion in U.S. vacancy and unemployment rates

Since I happen to have handy some regional data on the help-wanted index (HWI) for the U.S., I thought it might be interesting to see whether U.S. vacancy and unemployment dynamics in a cross-section display any interesting patterns. (I would like to thank Kyle Herkenhoff for suggesting this exercise to me).

The regional HWI data is from the Conference Board. I explain here how the data was corrected for the recent substitution from print to electronic media in job advertising activities. That data was constructed for 36 U.S. cities.  I construct a "vacancy rate" measure by dividing the HWI by the labor force and normalizing to 10  in 1990:1. Here is what the aggregate data looks like:

As one would expect, there is a strong negative correlation between vacancies and unemployment; this is the so-called Beveridge Curve.

Labor economists sometimes like to gauge labor market conditions by constructing a "labor market tightness" variable--the ratio of vacancies to unemployment, or the v/u ratio. The v/u ratio plays a prominent role equilibrium unemployment theory; see Diamond, Mortensen and Pissarides. As the following diagram shows, labor-market-tightness is highly procyclical.

Regional Patterns

The following diagram plots the unemployment rates for 36 metropolitan areas in the U.S. The solid black line is a population-weighted average (it corresponds to the national unemployment rate).

The figure shows that there is significant disparity in regional unemployment rates at all points in the business cycle. As the U.S. economy emerged from the recession in the early 1990s, regional variation in unemployment rates seems to have declined for the rest of that decade. Nothing much changed until the most recent recession, where we see a dramatic increase in both the average unemployment rate and its in its dispersion across regions.

Next, let's take a look at regional "vacancy rates" (the city-based HWI divided by regional labor force).

The dispersion in regional vacancy rates appears to be very, very large (measurement error?). Using my eyeball metric, it appears that the dispersion in vacancy rates is somewhat procyclical. In particular, look at how the dispersion appears to increase throughout the 1990s expansion--at the same time, the dispersion in unemployment rates is declining. This suggests that the dispersion in labor-market-tightness is procyclical; and indeed, the following diagram shows this to be the case.

It would be interesting to know what might be behind these regional differences in labor market tightness, and why this regional dispersion varies over the business cycle.

First, what accounts for the dispersion? In a basic Mortensen-Pissarides labor market search model, extended to incorporate regions, I think that the labor-market-tightness variable is likely to equate across regions (at least, allowing for factor mobility). Regional differences in tax rates, etc., might account for some of the disparity. But the measured disparity is huge.

Second, what accounts for the cyclical properties of the dispersion? Is it simply the case that some regions are populated by industries that are more cyclically sensitive to aggregate shocks? Or is it the case that the shocks themselves are concentrated in certain regions, with the effects propagating to other regions of the country?

If anyone would like to see this data plotted in a different way, or see some statistics reported, feel free to let me know. (Thanks to Constanza Liborio for preparing these graphs.)

The China Factor

The sovereign debt crisis in Europe has garnered most of our attention as of late. But should Europe really be our main concern? For several months now, many economists (including myself) have been casting a nervous eye over to China. Paul Krugman summarizes these concerns nicely in his NYT article today: Will China Break? Mark Gongloff earlier asked the million dollar question here: China's Shadow Banking System: The Next Subprime?  Hmm...

P.S. And what's with these stories I keep hearing about China's missing bosses? (e.g., China's Vanishing Factory Bosses). Sounds ominous, if true. We truly do live in interesting times. 

Beveridge Curves for 36 U.S. Cities (updated)

On October 9, 2010, I posted some regional vacancy-unemployment data for the United States; see: Beveridge Curves for 36 U.S. Cities.

My measure of vacancies was the Conference Board's help-wanted index (HWI).  A colleague of  mine (Silvio Contessi) pointed me to a paper by Regis Barnichon (EL 2010) that identifies a major flaw in this data series. Barnichon summarizes the problem here:

The traditional measure of vacancy posting is the Conference Board Help-Wanted Index (HWI) that measures the number of help-wanted advertisements in 51 major newspapers. However, since the mid-1990s, this “print” measure of vacancy posting has become increasingly unrepresentative as advertising over the internet has become more prevalent. Instead, economists increasingly rely on the Job Openings and Labor Turnover Survey (JOLTS) measure of job openings. However, this measure is only available since December 2000 and cannot be used to contrast current labor market situations with past experiences.

In this paper, I build a vacancy posting index that captures the behavior of total—“print” and “online”—help-wanted advertising, by combining the print HWI with the online Help-Wanted Index published by the Conference Board since 2005. 

Here is how Barnichon's correction looks for the aggregate data.

That is, the secular decline (blue line) in the original HWI series is estimated to be entirely the consequence of a substitution away from print to electronic forms of job advertising.

With this in mind, I asked my tireless research assistant (Constanza Liborio) to recalculate our regional Beveridge curves using Barnichon's correction (for those interested, I can email you a file describing the exact procedure employed).

The regional vacancy data was purchased from the Conference Board (their Help Wanted Online data series), so unfortunately, I cannot make it available to you without their permission. I have permission to display the data, however. Here is what we get.

Addendum: Dec. 13, 2011

As I have stressed in an earlier post, one should be careful in using these raw correlations to identify the source of disturbance; see: Interpreting the Beveridge Curve.

A reader points out that the Monster Employment Index (available since 2004) might be of some use for measuring regional employment opportunities.