Relevant and even prescient commentary on news, politics and the economy.

When S != I

As Brad DeLong has noted, Tim Geithner believes it is time for “the economy has now recovered sufficiently for government to begin to make way for private business investment.”  In short, he expects “the private sector” to do the heavy lifting in these joyous times of economic recovery.

Cynics among us—why, yes, that might well include me—would note that the private sector has had to do much of the heavy lifting for the past several quarters, in the face of what is varyingly described as “a precipitous decline in Aggregate Demand” or “a rise in unemployment.” (You say overextended credit, I say bankrupt.)  And that its performance has been, not to put too fine a point on it, exemplary in the face of the constraints presented.

Yes, I’m praising the efforts of the private sector.  Not just because small businesses especially are trying to sustain current levels of production and services in the face of tightened credit and the aforementioned AD decline, but also because they, as LBJ once observed in another context, have been put into the position of trying to run a race when the shackles are just being removed from their ankles.

I blame the banks.

Now you know it’s me.  The problem is, the evidence is on my side.  Recall that the alleged reason we needed to “save” the banks is that they are Financial Intermediaries, taking a slice out of the matching between Investors (Savers, in most economics models) and Capitalists, who borrow to recombine Capital (K) and Labor (L) into a new product that presents a better return than the old one.

Call it “creative destruction.” Call it “capitalism.” Call it “economic growth.”

Let us ignore—though it Abides, like Earth or a steaming pile of elephant dung—that the “intermediaries” were making somewhere between 30 and 40% of the total profits in the U.S. for the past decade. We can (1) pretend that those were all payday lenders, (2) be a “first-best economist” and claim that is the way things should be, or (3) realize it’s a problem and leave addressing it for another time.*

But let us not ignore that capital supply is essential to growth possibilities. With labor abundantly available, the limitation on creating new product is essentially The Big K, and it’s “Main Street” proxy, money.

As noted above, in most models of economic growth, we treat Savings as being equal to Investment.  This makes sense: even when the Financial Intermediaries were making $3 or $4 of every $10, they were reinvesting in better systems, better technology, better analysis, and better methods.  Low Latency leads to High-Frequency Trading (HFT) which leads to…well, let’s be nice and just say “greater firm profits.”  Even if only 50% of those profits are being directly reinvested, they are being reinvested, while the rest produces at worst greater paper investments and at best a higher velocity of money and/or a multiplier (“trickle-down”) effect from increased spending.**

Put your money in a Mutual Fund, it’s Invested. Buy a stock, it’s invested.  Put it in a Demand Deposit Account (what used to be a “Savings” or “Checking” account), and it’s invested (“swept”) by the Financial Intermediary, who gives you a share of the profits in the form of interest.

Not to sound like a broken record, but Excess Reserves put a spanner in that last one.  Don’t believe me, ask economists Bruce Bartlett or Joe Gagnon.  Or just look at a graphic of M2 and what I’m calling “Intermediary Private Investment” (M2 minus the Excess Reserves maintained by Financial Intermediaries).

 

FinInstPrivInvest

As Excess Reserves are not Seasonally Adjusted, I used the NSA version of M2.  As noted in my previous post, up until September of 2008,  the Fed did not pay interest on Excess Reserves (or Reserves, for that matter), so that excess reserves were essentially a rounding error—funds kept because of the asymmetric risk-reward of a miscalculation, or “precautionary savings.”  They tended to total about $1-2 Billion on average, rather minor in the context of $7-8 Trillion.***

But once you hit September of 2008, the growth in M2 is more than negated by the growth in Excess Reserves. Indeed, the horizontal line on the graphic above is the level of Intermediary Private Investment in August of 2008—nine months into the “Great Recession.”—isn’t exactly reaching for the skies.  But it’s also significantly higher than the current I, as opposed to S.

(Note that the NSA trend is also downward since the alleged beginning-of-recovery months of June-July, 2009. That the performance has been as good as it has been in such a context is amazing.)

When Savings=Investment, there is potential for growth. When savings go into mattresses—for good reason, especially in the pre-FDIC days—intermediaries cannot do their job so efficiently as the models presume.

What are we to call it when Intermediary Private Investment is significantly less than Savings—when not the people, but the intermediaries themselves, are stuffing money into their own, interest-bearing mattress?

I would suggest “bad economics,” but that term seems too applicable to more general conceits.

*I would rather lose what is left of my eyesight and hearing than take the second position; others, from Scott Sumner explicitly to Brad DeLong implicitly, have significantly variant mileages, which is why there’s a horserace for describing economic policies in the past decade or so. They are winning, while I received several decent paychecks over the time.

**It is left as an exercise whether the “trickle-down” effect is positive or significant.

***Another sign of improved technology is that the growth in reserves decelerates—funds are used more efficiently by the intermediaries—after ca. 1990/1991; the trend moves slightly upward in the Oughts, though that is both relatively minor and possibly due to complications related to the expansion of products offered.

ExcResTrends

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Are you better off than you were a year ago? 28 States Say No.

The WSJ Economics Blog, discussing June 2010 unemployment rates by state, uses the headline “Most Regions Show Improvement“*

I suppose we should be encouraged by the headline and not look at the text:

Washington, DC and 16 states recorded jobless rates in excess of 10%. North and South Dakota continued to have the lowest rates in the country, at 3.6% and 4.5%, respectively.

Despite the improvements in the jobless rates, 27 states posted a decline in payroll employment, while 21 notched increases. Montana and Alaska had the highest percentage increase from the previous month, while New Mexico and Nevada reported the largest percentage drops. [emphasis mine]

Less money is being paid in a majority of states. The clearest explanation, then, remains that the “decline” in U-3 reflects people dropping out of the work force, not being employed.

It gets more interesting if you look at the Year-on-Year Change. There, 28 of the 50 states show a U-3 unemployment rate that is higher than or equal to last year’s. (The District of Columbia’s U-3 rate declined by 0.1% over that time, so it is only 10.0% now.)

And the improvements are, lest we forget, from a high plateau. The 14 states with the greatest drop in their unemployment rate year-on-year have an average current rate of 8.4%—and a median rate of 8.95%, the average being skewed by the above-mentioned North Dakota, with it’s 9.3 people per square mile and total population under 650,000, 37% of which are not of working age.

Dropping North Dakota from the “biggest YoY winners” moves the median current unemployment rate to 10.0%, while the average is slightly above 8.75%.

If this is a recovery, then my December 2009 prediction that this will turn out to be a “cursive-zed” recession may turn out to be optimism.

*Also, “Jobless Rates Drop in Most States.”

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The hourless recovery

There was an interesting blog post over at the Macroblog (Atlanta Fed) regarding productivity. John Robertson and Pedro Silos highlight the contributions to GDP growth from various factors, including productivity and employment. One of their findings:

As this chart shows, relatively high labor productivity growth during a recession is not a phenomenon isolated to the 2007–09 and 2001 recessions (for present purposes, the end of the most recent recession is identified with the trough in GDP in the second quarter of 2009). All recessions from WWII through 1970 also featured sizable growth in labor productivity.

The article focuses on the contribution of productivity gains to GDP growth during a recession and the early stages of the recovery. The authors do not comment on, however, a very interesting bit of their story: the “hourless” recovery. Lockhart speaks of this curtly in his speech – the focus of the macroblog article:

Current data on the use of part-time workers suggest that businesses have some scope to increase hours without hiring new full-time employees.

The precipitous drop in hours worked has differentiated this labor downturn from previous cycles (papers here and here). According to the BLS Q1 2010 productivity report, the recovery of the 2007-2009 recession has so far been “hourless”, which is consistent with the previous two cycles.

The chart illustrates the contributions to output growth from hours and productivity for the the first three quarters of recovery spanning the last six recessions. Note: the current recession has not officially been dated as having ended, but June or July 2009 is the “whisper” talk for now. I will simply call Q3 2009 as the onset of the recovery, since GDP grew that quarter.

The “hourless recovery” is underway: a cumulative 3.3% of output has been generated over the last three quarters (using the BLS productivity report) via a 0.9% drop in aggregate hours. I argued last year that adding back hours cannot generate sufficient output growth for sustainable “recovery”; however, productivity growth has been strong enough that the productive hours cycle has not even begun.

It’s likely that the large service sector is the drag that is driving the “hourless” recovery because manufacturing hours are red hot.

(The weekly hours series are indexed to 100 for comparison.)

The chart illustrates average weekly hours of production and nonsupervisory workers in manufacturing and private industry payroll. Manufacturing weekly hours, 41.5 hours per week in May 2010, recovered 5% off the low of 39.4 hours in March 2009. Furthermore, May 2010 set a ten year record, breaking past levels not seen since July 2000 (not shown in chart but you can see it here). In contrast, total private weekly hours remain below pre-recession levels, just 1.5% off of the June 2009 low, 33.0 hours.

The BLS breaks down average weekly hours for all workers by industry since 2006. The service sector is the lion’s share of the private payroll (~85%). Of the service sector payroll, 68% remains short of pre-recession weekly hours worked: trade, transportation, and utilities, professional and business services, and education and health services.

Adding hours still won’t provide a large growth impetus, as I argued here; however, the service industry has yet to see the burst in hours like in manufacturing. As such, I agree with the overall conclusions of the Robertson and Silos article:

Hence, it will probably take awhile to see how President Lockhart’s forecast of continued modest employment growth pans out.

Rebecca Wilder

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Industrial Production and Housing Starts


Industrial production and housing starts were reported today. It has been well covered elsewhere, but I though I would make a couple of comments.

Compared to other cycles this recovery in industrial production continues to be moderate.

It is stronger than in the weak recoveries, but compared to the depth of the downturns the rebound is quite weak. The good point is that in the early stage of a recovery industrial production is driven largely by inventory rebuilding. But we have probably passed that point in the cycle as the economy shifts from the recovery stage to the expansion stage. This means that we are now seeing quite strong industrial production that is driven by changes in final demand rather than by inventory restocking. This implies that good growth in industrial production is likely to continue in contrast to previous expansions when industrial production growth flattened out after inventory restocking ended.

The other point in the report was that capacity utilization was rising. Normally rising capacity utilization is an important driver of business capital spending and is a good omen for continued growth. But that optimistic premise should be tempered by the point that one of the reasons capacity utilization is rising is that industrial capacity is actually contracting.

It is down -1.3% from a year ago, the largest contraction on record.


In contrast to growth in industrial production housing starts actually fell from 659,000 to 593,000. This reflects the major difference between the two economic sectors. Industrial production is being driven by a rebound in final demand while final demand for housing is weak. Moreover, this weakness in housing demand reflects the over a decade of over-production in housing that built excess supply that still has to be worked off.


The fundamental driving force behind housing demand is household formation. In the short run other factors enter the picture. But no matter how many bells and whistles you add to the model, household formation will remain the most important factor. It is not a good determine of month to month fluctuations in the housing market but it is the key factor driving long term demand. Household formation is essentially a function of young people leaving home and setting up independent house keeping. That is one reason it is surprisingly cyclical as in hard times young people either remain or return home. But the long run trend is clear. After the baby boomers leaving home and setting up housekeeping lifted household formation to over 2 million annually in the 1970s and 1980s household formation has fallen to under 1.5 million annually. Moreover, it should remain at that low level unless we have some fantastic rebound in immigration.


This is easy to see if you look at a smoothed series of household formation and housing starts. In the 1970s and 1980s annual housing starts averaged over 2 million. But this was accompanied by household formations of over 2 million annually. So over that period supply and demand were in rough balance and despite the highly cyclical nature of both economic series, significant long term imbalances never developed. But look at what has happened since the late 1990s. Housing starts have significantly outpaced household formation creating a large supply of excess housing that will have to be worked out of the system. But with household formation now expected to remain well below 1.5 million this implies an extended period of housing starts remaining at or near their current low levels rather than the historic pattern of strong rebounds. This cycle the pent-up demand for housing is negative.

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Recovery? or We’re Gonna Need a Bigger Stimulus?

Sometimes, I hate being right. Most of those times are when I take a pessimistic view of data; this has happened a lot recently.

It gets worse when the people who agree with you are none other than The Giant Vampire Squid. As the Wall Street Journal notes:

Zero — First quarter GDP growth, minus the temporary factors of government stimulus and inventories, as estimated by Goldman Sachs.

With the economic recovery already nine months old, it’s easy to forget just how tenuous it remains. Consumers are spending and businesses are investing, but an uncertain amount of that activity depends on temporary lifts, most notably the American Recovery and Reinvestment Act of 2009.

I promise to get enthusiastic about inventory growth when people stop claiming that the drop in sales is based on the Demand side of the equation; that the banks aren’t holding more than $1 Billion in Excess Reserves because they want to, but rather because they can’t find borrowers.

Looking at state budget projections for next year, the reality that inventories cannot grow indefinitely, the unemployment and discouraged-workers levels, and the growth in long-term unemployment, it’s difficult to find engines for growth.

Real GDP recovery is described fairly as, at best, lethargic. And now we know that even the lethargic recovery is stimulus-induced, not real.

But the headline numbers have given an excuse to do nothing, and steroid withdrawal is, I am told, a very painful experience.

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More Detail on Working the Refs

So there are several comments to my previous post. Ignoring the a good one from Dr. DeLong, several people are taking umbrage at my unsubtle suggestion that the effect on employment being suggested is, to be polite about it, rather creative.

kharris begins, “So let me see if I have this right. If anybody tries to figure out what the impact of snow on economic data might be, they are big fat liars? But those who know that the economy is in bad shape, without reference to actual events, is a stand-up kind of hack?”

Following is an expansion of my comment in that thread, with data:

To the second question, well, I may be a hack, but my stand-up days are in the past. But given the choice between believing that the recovery is in full swing and that long-term unemployment is getting worse and jobs are not and will not be created, well, I’ll take the CBO projection as the baseline:

CBO expects the unemployment rate to average a little over 10 percent for the first half of 2010, and it will probably not dip below 9 percent until 2012.

and note that if we’re calling that a recovery, our definitions have become Very Generous. So bold claims of recovery need to be tempered by the prospect of worse headline unemployment (U-3) for the next five months (including February) and no significant recovery for the eighteen after all.

Sorry I’m not doing handstands that GDP might be slightly positive for a few quarters of sub-replacement level employment increases, but I didn’t cheer the “recovery” of 2002 either, so at least I’m a consistent hack.

To the first: Not at all; trying to figure out the effect is fair game and perfectly reasonable. But the declarations so far are all running in one direction: we believe the economy is better than the data will be, so we need to wait if it looks bad. (See Ms. Caldwell as quoted by CR or Catherine Rampell, for example.) Rampell:

That report will probably be very, very ugly. I have seen some forecasters project job losses as high as 100,000.

The main culprit behind the expected jobs plunge is the blizzard, which closed businesses and kept people from going to work or even seeking work for days and sometimes weeks. These work stoppages probably occurred precisely when the government was collecting data for its February jobs report.

So the current estimates are all that (1) demand was down and (2) employment was down.

And (3) deliveries were down: see the ISM data.

Put it all together, and you can tell a story of heavy snow snarling shipments to and from manufacturers, slowing down production growth.

But at least in this case, we have a clear indicator: the increase in backlogged orders.

Finally, (4)savings.

The reasons for the stall are twofold: For one, rebounding wealth since the recession’s depths has helped provide some support for consumer spending. Secondly, weak income growth has left other consumers with little choice but to spend proportionally more of their incomes, particularly in light of [5] still-tight credit conditions.

So demand, supply, savings, credit, and employment are all down. The first and second are aberrations of snow (and equilibrium), the second and third abide.

Which leaves employment, which is discussed in more detail than most sane people would want below the fold.


Now, it is clear that people who are employed did not work in the week. But they are not likely to have reported themselves as “unemployed” or (except in a very literal sense) “out of work.” True, they did not produce—but what they would have produced was not bought, and hence there is a backlog of orders.

But companies that now have backlogs of orders know that this was because they did not have their current workforce. Accept an order to produce, say, 200 units (which takes a month to produce) and lose five to eight business days and you’ll be 50-80 units behind.

But you’re not going to go out and hire a new person to fill the backlog.

Yes, there was an effect on production and sales. But the idea that 100-200K jobs went unfulfilled solely because of weather conditions that were aberrant primarily in the mid-Continent is either (1) rather optimistic or (2) ignoring that the excess snow effect was mostly in the areas that are least underemployed. (See this nice map from Catherine Rampell)

So in the best case scenario, the recovery was muted because things were not delivered or sold—though money (savings) was (were) spent. And the only reason firms didn’t hire was the snowstorm that closed D.C. and delayed Philadelphia. (Though there was no snow in NYC and, as noted, nothing unusual about the fallings in the Midwest.)

The worst case scenario is that demand wasn’t filled solely because supply wasn’t available because existing workers could not produce. Working on the “nine women pregnant for a month don’t produce a baby and you have a real problem eight months thereafter” rule, employers will (generally correctly) view their February backlog as a result of existing labor not working, not as a need to hire new workers.

If you’re balancing the effects of those two—standard Slutsky analysis, as it were—there is a high likelihood that hiring will be dampened going forward by the snowstorm as firms underestimate actual demand. It is less likely that actual hiring was significantly reduced by it.

But that’s not the way the discussion is going. So a bad (negative) number has excuses, a poor number (positive, but less than replacement rate) has excuses and should be seen as “good,” and a good number (replacement rate or better) will mean “all ahead full.”

So I tried looking at ancillary data. Looking at power usage, for instance, indicates a major decline that would correspond to less activity(Table 1.6.b; Commercial usage YOY down 3.6%; Industrial usage YOY down 5.6% with declines in all areas; total usage down 4.3% YOY [Table 1.1])—but that’s only through November.

Maybe the past three months have been part of a miraculous recovery. But it’s not in employment, its not in the available energy usage data, and it doesn’t follow from the ISM data, which indicates slow growth at best.

Those who want to claim the economy is recovered have been, as noted, “working the refs.” So a bad number (by Rampell’s apparent reasoning) will kill health care reform, but not mean that we need a second stimulus—even though the states are hemorrhaging money and, soon, jobs. (Teachers, police and fire–you know, all the nonessential personnel.)

It’s a heads-we-win-tails-we-win-more situation being set up.

If we pretend that all of the argument are true: that the snowstorm was a once-in-a-lifetime event and that it really did produce a major skew though, we might want to look at what happened the last time a “once-in-a-lifetime event” occurred near the end of a recession.

The vertical lines are at September and December of 2001. For a week in September, everyone—and this time I mean everyone, not just the bottom third of the Bos-Wash corridor—stopped shopping for a week. As predicted above, the employment effects abided for at least the next few months. (Recall, after all, that that recession officially ended in November.)

Given the choice between (1) assuming that there will be a one-off decline in employment due to the snow and that everything will return to recovery next month or (2) that there will be a lingering, negative employment effect from the snowstorm and attendant business slowdowns, there appears to be only one way to bet, given the data and the history.

Yet the calls right now—absent evidence—are going the other way.

If we’re working from anecdotal evidence, then certainly there is a recovery. It’s the extant data that doesn’t support any recovery that is not also described as “jobless and uncertain.” That may change on Friday. But it’s not the way to bet, no matter how much the refs are worked.

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Working the Refs

So there was this big snowstorm that hit the East Coast a couple of weeks ago. (Not the one this weekend, that dumped about 2′ of snow on Upstate New York and a little more than a foot here in suburban New Jersey; the one that wiped out D.C. and gave the Party of No an excuse to do nothing.)

Snow in February. What a surprise! Clearly, not something that happens every year.

My high school classmates and others in the Midwest see the notice and say, “Yeah, gosh, sounds like January and February here.”

But This One is Different. Maybe because it gave the U.S. press an excuse to pay no attention to Haiti. Maybe because closing down D.C. meant that all the pundits got to whine and reveal their suffering.

And, just maybe, because it has become the all-purpose excuse for the February Employment Report. Or any other hint that the world is not perfect, and those “green shoots” haven’t been eaten by starving deer who were then shot by Big Bank Hunters.

The Usual Suspects are already out in force.* And the hedging (not in the risk management sense) has begun:

“We will have to wait until March to see if February is an aberration or a fundamental sign that the recovery in sales will be more subdued than hoped,” [Jessica Caldwell, Edmunds’ director of industry analysis said].

So anything that can be marginally interpreted as positive will be The Crest of a Wave, while anything that makes those legendary shoots look as if they were artificial flowers will get the rousing “Wait Until March!” cry.

All we really know is that—thanks to Senator Bunning and a pliant Democratic “leadership”—March, not April, is the Cruelest Month for about 1.2 million normally-working Americans.

But, gosh, the job gains for February might be understated by 5-8% of that total. So let’s not do anything hasty.

*Yes, it’s “pick on Brad DeLong day.” Didn’t you get the memo? (Also, I can’t find discussion of the topic at any of the Other Usual Suspects, though I haven’t checked The Big Picture.)

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Quote of the Day, Economic Recovery Edition II

David Wessel goes to a familiar source:

One big reason is that his efforts have made borrowing easy for big companies, those that can sell bonds, but not for consumers or smaller firms that rely on banks to borrow. “If you’re a large corporation relying on capital markets, the Fed and Treasury saved you,” says Charles Calomiris, a Columbia University economist. “In the other economy, the real engine of job creation, the banks aren’t lending and bank capital is still very scarce.”

Stuffing pension funds with GE Commercial Paper has never been easier. Creating the next GE (a working model this time?): a lot more difficult.

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