Gold’s Cloudy Crystal Ball

Given all the fiscal and monetary stimulus of the last year or two, it’s no wonder that many people are on inflation watch. And whenever that happens, many eyes turn to gold, which is revered in some circles for its power to foretell the future. Is this reputation for prescience deserved?

Not for the last 25 years, it isn’t. Long-time readers may recognize this as a theme of ours: markets generally reflect the present, and rarely divine the future. We’ve made this point concerning oil prices (which reflect, don’t lead supply and demand trends), fed funds futures (which predict next to nothing), and inflation-protected bonds (which reflect current inflation, and don’t anticipate it). And now we can add gold to the list of markets with undeserved reputations as seers.

As the graph below shows, gold did a pretty good job of anticipating moves in the CPI in the late 1970s and early 1980s, but since then the relationship has broken down. For example, the correlation coefficients for the yearly change in the gold price and the CPI during the 1974–84 period improve the further ahead you go—from 0.61 for the same month to 0.68 for a three-month lead on the CPI. They stay in the 0.67–0.68 range for leads of up to about a year (that is, gold anticipates moves in inflation). But if gold were really good at anticipating inflation, you’d expect a steeper gradient of improving correlations than just 0.07 point over the course of three months, followed by a flattening, wouldn’t you?

And after 1984, gold’s powers of prognostication collapse completely. Since 1985, the correlation coefficient for the yearly change in the gold price and the CPI is 0.01 for the same month, 0.00 with gold given a lead of three months, and –0.04 six months out. And the correlations remain slightly negative up to fifteen months out.

In fact, you could do far better in predicting future inflation just by drawing a straight line from current inflation. The correlation coefficient between the yearly inflation rate and the CPI three months out for the graph’s entire history is 0.96. As with gold, the 1974–84 experience pulls up the average; since then, the coefficient is 0.79 (lower, but still a lot better than gold). Six months out, it’s 0.58—not great, but still miles ahead of gold.

Clearly the 1974–84 period is special: a great acceleration in inflation followed by a great disinflation. Maybe we’re in for a rerun—though there are plenty of reasons why the present is very different from that past. One difference is the behavior of productivity and unit labor costs. Another is that the 1970s were the climax of a long wave of rising labor militancy. We’ve got nothing like that now.

That last point is underscored by the graph below, which shows the annual number of major strikes since 1947. Strikes actually do a better job of predicting inflation than gold does. The correlation coefficient between the yearly change in strikes and the next year’s inflation rate since 1985 is 0.18. If the experience of the first nine months of 2009 holds for the rest of the year, we’ll have four—count ‘em, four—work stoppages involving 1,000 workers or more this year. That will be an all-time record low since the BLS started tracking these figures in 1947. From 1947–79, we averaged 303 a year. For 2000–2008, the average was 22 a year. So far this year, we’re down by 90% from the decade average, and more than 99% from the 1947–79 average—and it’s hard to see strike activity picking up anytime soon.

So what is the current strength in gold telling us? That a lot of money has been racing into the metal. While much of that money probably belongs to investors who think we’re going to see a major pickup in inflation—and some of it to investors who want to get ahead of the spread of that perception, regardless of their own convictions—gold’s record as an inflation forecaster isn’t something to bank on.

Bad News from the SF Fed

The last thing we want right now is a study from a regional federal reserve bank with the headline, "Jobless Recovery Redux?" and a subhead, "Reasons for pessimism," but that's what we have from the SF Fed, and it's hard to argue with their logic.

Researchers Mary Daly, Bart Hobjin, and Joyce Kwok consider three labor market indicators--flows in and out of unemployment, involuntary part-time employment, and temporary layoffs--to project how the unemployment rate may behave when the anticipated recovery begins.

They point out that before the 1991 recession, increases in the inflow rate, the speed at which workers move into unemployment, and decreases in the outflow rate, the pace at which they find jobs, were nearly equivalent in relative terms during recessions. The resultant sharp increases in the unemployment rate were followed by rapid recoveries as firms hired back workers in improved conditions.

Increases in the unemployment rate in the 1991 and 2001 recessions, however, were driven by disproportionate declines in the outflow rate, making lack of hiring the primary culprit.  And recoveries diverged from the established pattern as well: outflow rates recovered much more slowly than they had in pre-1990 recoveries.  In fact, the authors cite several studies showing that current business-cycle fluctuations in the unemployment rate are driven primarily by the outflow rate.

The current recession is particularly nasty because the outflow rate is at an historic low and the inflow rate is rising in line with the recessions of the 1970s and 1980s-actually, it's shooting straight up at present-both  contributing to an extremely weak labor market.

The authors evaluate several possibilities for the future. Their benchmark, no change in the outflow/inflow rates, would bring us to 10% unemployment by 2010. The "Blue Chip" consensus included in the paper posits an employment recovery slightly weaker than that of 1983 and a bit stronger than that of 1992, bringing the unemployment rate to 10% in early 2010, from where it would begin to decline.  But if inflow/outflow rates behave as they did in 1992, unemployment would peak around 11% by summer of 2010, and remain above 9% through 2011.

And that's where temporary layoffs and involuntary part-time work come in. In the current recession those working part-time for economic reasons has risen dramatically and to an historical high, from 3.0% in December 2007 to 5.8% in April 2009, with significant reductions in hours across broad sectors. At the same time the share of workers on temporary-as opposed to permanent-layoff is very low. In fact it actually fell from 12.9% in Dec-07 to 11.9% in April-09. (Generally the share of workers on temporary layoffs rises during recessions: it increased from 16.1% to 20.7% between July 1981 and November 1982.)  So with few workers on temporary lay-off waiting in the wings, and a large number working part-time against their wills, it seems logical that employers will expand the hours of partially-idled workers instead of taking on new employees. The authors formulate their forecast for the unemployment rate by adding the linear relationship between part-time employment and the unemployment rate between Dec-07 and April-09 to the Blue Chip consensus. This suggests labor market slack will be higher by the end of the year than at any time since WWII, the outflow rate will be historically low, and the unemployment rate will be sticky. In other words, Jobless Recovery III.

Full report here: 

http://www.frbsf.org/publications/economics/letter/2009/el2009-18.html

Financial Crises: A Close-up

In our issue of May 7, we wrote about the IMF’s  study of 122 recessions in 21 “advanced” countries since 1960. They found that downturns associated with financial crises are far longer and deeper, and recoveries slower and weaker, than those that aren’t financially driven. Here’s a close-up of the behavior of interest rates, stock prices, inflation, and employment in the four years after the onset of the crisis in 15 major financially driven recessions identified by the IMF. (See notes below)

In a nutshell, we found that on average, interest rates and inflation generally decline for the full four years; stock prices rise steadily, though not explosively, after a two-quarter decline; and employment falls for about three years before beginning a weak recovery.

GDP experiences are quite varied, with some countries experiencing sharp, sustained declines; others, brief, sharp declines followed by a strong recovery; and still others, extended periods of stagnation. Those disparate experiences produced a very misleading “average” line, so we are not providing a GDP graph. But despite those contrasting GDP patterns, almost all countries suffered from a very weak job market for several years after the financial system hit a wall.

	GDP	Employment
Australia	-1.7%	-3.8%
Denmark	-8.7
Finland	-20.5	-19.2
France	-1.0	-1.5
Germany	-2.8	-3.1
Greece	-1.6
Italy	-2.2	-8.2
Japan 1	-3.9	-0.4
Japan 2	-3.4	-2.3
New Zealand	-7.6	-6.9
Norway	-7.9	-6.6
Spain	-0.4	-9.0
Sweden	-18.5	-13.1
UK 1	-3.4	-1.2
UK 2	-2.5	-6.2
average	-5.8	-6.3
median	-3.4	-6.2
Total decline in real GDP and total employment in recessions in the IMF sample, from pre-crisis maximum to cycle low

Comparing recent U.S. experience to the average yields the following conclusions. Interest rates, inflation, and stock prices are all down much harder than the “typical” experience. This suggests that interest rates are probably not at risk of rising sharply, but we’re almost certainly past their bottom; stock prices, even with the recent rally, are not acting with outlandish exuberance; and inflation isn’t much of a risk for some time to come. Employment, however, is tracking the average very closely, suggesting that while the worst of the job losses are probably behind us, we’ve got another year and a couple of million to go.

Interest rates: down

Although financial crises typically come with a huge fiscal cost, as revenues sag and bailout expenditures rise, interest rates on long government bonds tend to decline steadily throughout the four year period we studied. Rates fell in 12 of the 15 examples over the first 8 quarters following the crisis, and 13 of 15 over 16 quarters.

Stocks: mostly up

Stock prices do surprisingly well in financial crises, after an initial spill. Actually, prices tend to decline over the year leading up to the crisis (about 4–5% on average); the post-crisis leg down is sharper but shorter than what preceded it (about 12%). But after that decline, stock prices tend to rise, though at far from a barn-burning pace—only around 5% a year.

Inflation: down

Though a lot of market participants expect that the financial bailout will ultimately prove inflationary, the history of financial crises suggests otherwise.

Employment: down hard

Deep, sustained declines in employment are almost universal following financial crises. If these averages hold, we’re about two-thirds of the way through the contraction in numbers, and not quite that far in time.

Notes:

In the four graphs, the line labeled “average” is the mean of the 15 financially driven recessions identified by the IMF, with the quarter of the crisis’ onset set to 100. The line labeled “U.S.” is the recent experience of the United States, with the onset of crisis set to the third quarter of 2007. Horizontal axis represents quarters before and after crisis onset (“C”).

These are the crises the IMF reviewed:

Australia	1990Q2–1991Q2
Denmark	1987Q1–1988Q2
Finland	1990Q2–1993Q2
France	1992Q2–1993Q3
Germany	1980Q2–1980Q4
Greece	1992Q2–1993Q1
Italy	1992Q2–1993Q3
Japan	1993Q2–1993Q4
Japan	1997Q2–1999Q1
New Zealand	1986Q4–1987Q4
Norway	1988Q2–1988Q4
Spain	1978Q3–1979Q1
Sweden	1990Q2–1993Q1
United Kingdom	1973Q3–1974Q1
United Kingdom	1990Q3–1991Q3

When will it ever end, aka, potential subscribers take note.

The market is currently abuzz with news that Robert J. Gordon, longtime member of NBER's Business Cycle Dating Committee, has provided solid evidence supporting a tight link between the peak in initial claims and, dare we say it, the end of recessions.

Back on April 2, we sent this to our subscribers:

Here's a rare note of possible cheer: could the behavior of initial claims be signaling that an end to the labor market contraction is in the offing?

Graphed below is the yearly change in initial claims for unemployment insurance. Note that this measure typically peaks a little before the end of a recession. No surprise, perhaps. But what is a little surprising is how similar current behavior  looks to earlier end-of-recession patterns.

And as the table below shows, the peak in claims growth occurs, on average, four months before the official NBER trough month, though the range is one to seven months. Note too that employment doesn't necessarily turn positive until a few months later, with the trough in yearly job growth typically coming five months after the peak in claims growth, and the trough in the employment level coming eight months after. In 1970s, yearly job growth hadn't picked up even a year after the peak in claims. But even then, the bottom was getting close.

		Months to Trough in Employment			Employment Growth, year-to-year
	peak in claims, yty	cycle	level	growth	claims peak	year later	swing
Dec 69-Nov 70	Apr 70	7	7	7	1.8%	-0.4%	-2.3%
Nov 73-Mar 75	Nov 74	4	5	7	0.4%	-0.7%	-1.2%
Jan 80-Jul 80	May 80	2	2	2	0.7%	1.0%	+0.3%
Jul 81-Nov 82	May 82	6	7	5	-1.3%	-0.5%	+0.8%
Jul 90-Mar 91	Feb 91	1	3	3	-0.6%	-0.4%	+0.2%
Mar 01-Nov 01	Oct 01	1	22	4	-0.7%	-0.7%	+0.0%
average		4	8	5	0.1%	-0.3%	-0.4%

Since there's a good chance that the job market in this cycle will resemble the slow recovery after the 2001 recession, it could be 2011 before employment starts growing again. But if we think of this as a sort of leading indicator of a leading indicator, we could start seeing signs of the recession's end by mid-summer. We hope.

The Fed Evokes Shakespeare

There's no shortage of reasons to worry about the health of the U.S. dollar: a still-huge trade deficit, a huge and swelling budget deficit, pervasive credit troubles, a serious recession that may linger, the threat of capital flight, etc. etc. Should we be worried about a currency crash?

That question is ambiguously phrased. It's quite possible the dollar could crash. But how bad would it be if it did? A surprising answer comes from a recent study by Federal Reserve economist Joseph E. Gagnon. The title lays out a broad hint: Currency Crashes in Industrial Countries: Much Ado About Nothing?. Gagnon's answer is basically, yeah.

Gagnon looks at 19 episodes of sharp currency depreciations-15% or more over four quarters-in 20 industrial countries since 1970. Factors that caused the crashes include inflationary policies, large current account deficits, capital outflows, and rising unemployment rates. Sometimes one factor was enough to cause the slide, sometimes it took several. But his surprising finding is that crashes were followed by poor outcomes-slow GDP growth, rising bond yields, and falling equity prices-only when inflationary policies prevailed. But the currency crash seemed not to contribute to poor outcomes-if anything, they mitigated them. The inflation did the damage, not the currency troubles.

The greatest danger from a currency crash came when the central bank was pegging a specific currency value despite inflationary policies. If the exchange rate is flexible or floating, there's considerably less trouble.

It's important to note that an inflation must be underway, and not merely expected, for a currency crash to be truly damaging. The threshold level of inflationary risk is a rate that's more than two standard deviations above the 20-country average, which works out to 7.2 percentage points.

Gagnon also finds that devaluations can successfully stimulate GDP growth and improve the foreign balance with little effect on inflation. He concludes: "Non-inflationary currency crashes uniformly had good outcomes: GDP growth was average to above average, bond yields fell, and real equity prices rose."

We're not conspiracy theorists, sad to say, but a word on what this paper might mean, aside from its interesting conclusions. There must be talk within the Fed about what would happen should the dollar fall hard-and maybe even if such a devaluation might be a good move for the U.S. Though no central banker or finance minister would ever let on that he or she is thinking this way, you can imagine the temptation. And from all this we'd conclude: avoid betting the farm on dollar strength. But if you lead a dollar-denominated life, you have little to fear from a devaluation. Things might look a little different in Beijing, but that's another story.

The Envelope Please: NBER Study finds ratio between Establishment and Household Surveys to the Cyclical

NBER has just released a working paper, "Exploring Differences in Employment between Household and Establishment Data," that presents research and analysis carried out by the Census Bureau and the BLS concerning the unusually large gap between the two major employment surveys that developed in the late 1990s. By matching individual Unemployment Insurance records with individual respondents in the Household Survey, the authors unearthed characteristics of the workers most likely to show up in one survey yet be missed in the other, and conclude that most of these workers are on the margins of the income and education spectra. For example, poor recent immigrants working under the table and highly educated consultants might both be missed by the Establishment Survey but included in the Household Survey.

But that example should not give Household Survey enthusiasts false hope. The study demonstrates that divergences between the Current Employment Survey (aka the Establishment Survey or Nonfarm Payroll) and the Current Population Survey (aka the Household Survey) are "cyclical phenomenon," with the CES outpacing the CPS during business-cycle expansions, and then falling back during recessions and the early stages of recoveries. The 60-year history of the ratio between the two surveys graphed below shows this clearly. (Take that, Kudlow & Co.) Also note that the ratio failed to rise during the most recent recovery, which seems to underscore the ongoing weakness in terms of employment growth.

Based on characteristics of respondents discovered in their study, the authors contend that tight labor markets create a growing number of marginal jobs that often go unreported in the Household Survey, e.g., establishments hiring short-term workers to cover busy periods, which begins to lift the Establishment Survey. As economic conditions continue to improve, workers tend to drop informal jobs (which would be reported in the CPS but not the CES) for formal jobs (that would be reported in the CES), thus widening the gap between the two surveys. These trends then reverse as economic activity falls off, with establishments laying off workers who then turn to informal employment, moving from the CES to the CPS. The graph of the two series since 1994 directly below illustrates this process.

The unusually large and long-lived gap between the two surveys began in 1998 as the Establishment Survey rose well above the Household Survey, and reversed in 2001, when the Household Survey remained stable as the Establishment Survey fell.  The relative pick-up in the Household Survey that got so much attention in the press was the unwinding of the prior trend and not the beginning of a new one. To put some numbers on it, in comparing UI and CPS data the authors found that jobs counted in the UI but not in the CPS grew by 2.3 million between 1996 and 2001, while jobs counted by the CPS and not by the UI grew by just 600K. Between 2001 and 2003, jobs counted by the CPS but not the UI grew by 800K, while jobs counted in the UI but not the CPS fell by 500K.

 So next time any of us, understandably, seeks solace in the Household Survey’s strength when the Payroll Survey disappoints, we need to remember that NBER researchers, who are responsible for officially calling recessions, have determined that such relative strength is indicative of a weakening economy.

NBER Working Paper No. 14805, issued in March 2009, "Exploring Differences in Employment between Household and Establishment Data," by Katharine G. Abraham, John C. Haltiwanger, Kristin Sandusky and James Spletzer, available here (subscription required): http://www.nber.org/papers/w14805.pdf

Prescient TLR calls on three major economic turns

Dramatic slides in housing prices, auto sales, and oil prices have caused—need we point out?—tremendous turmoil over the past year.

We were out in front on all three (click to enlarge):

Auto Sales
 

Oil Prices
 

Housing Prices

Can you afford *not* to know what we are writing about today? Please call Marni at 877-324-1893 for a trial subscription.

Calculating the Unemployment Rate

Recently several news pieces have made the claim that if the unemployment rate were calculated as it was during the Great Depression, the current rate would be close to double what it is, and creeping toward the formidable rates back in the 1930s.

The first problem with this statement is that there was no official unemployment rate until the 1940s. The ones we use today were reconstructed after the fact. As unemployment ballooned during the Great Depression a number of ad hoc attempts were made to calculate the rate, and the widely divergent results led private researchers and some state and local governments to experiment with various sampling methods. In 1940 the WPA began publishing statistics on those working (the employed), those looking for work (the unemployed), and those doing something else (hiding under the bed perhaps?) and so not in the equation.*

The second problem with the statement is that it's just not true. Although the BLS has refined their surveys and made questions more specific, conceptually the unemployment formulas have not changed, and the BLS's own analysis of test data shows that the impacts of several sets of changes on the overall numbers are minor.

In 1962 high unemployment and two recessions in three years led to the formation of The Presidential Committee to Appraise Employment and Unemployment Statistics, led by Robert Gordon, and tasked with reassessing the concepts used in gathering labor-market data. The Committee gave high marks to the BLS's integrity and suggested some improvements. For several years the BLS tested new survey techniques before instituting a number of changes in 1967.

Among the most important of these were the requirement that workers must have actively sought employment in the last four weeks in order to be classified as unemployed.  A contact at BLS agrees that some discouraged workers were probably counted as unemployed before this change was made, but the effect of this migration is small. As they generally do, the BLS ran the new definitions alongside the old, in this case for 2.5 years, before adopting the new.  Although the test series is not entirely comparable with the new series, the overall unemployment rate in the new series dropped by just one-tenth of a percent and, within that, the rate for adult men was down 3/10th, up 4/10th for adult women, and off a full point for teenagers.  (Maybe they were just being teenagers: the requirement that they give a concrete example of their job search may well have reminded them of their parents and got the blank stare.) The Committee also recognized the need for more detailed data on persons outside the labor force, who are highly sensitive to changes in labor demand, and the BLS began collecting information on those who wanted a job although they were not looking for work in 1967.

In 1976, in order to provide more information on the hidden unemployed (who would presumably be part of the labor force in a full-employment scenario), the BLS first published the original U1 to U7 tables, which break out marginally attached workers.  These tables were revised in the 1994 redesign (becoming U1 to U6) and the controversial requirement that discouraged workers must have sought work in the prior year was added. This change halved the number of discouraged workers, resulting in a complete break in the time series.

But those workers can still be found in the U-6 series, which is the broadest measure of labor underutilization, and it ain't a pretty sight. Up 4.8% over the year, U-6 currently includes an ugly 13.5% of the labor force. Update: In February U-6 unemployment rose to 14.8%. There's no need to fool around with the official unemployment rate (U3) to get an accurate picture of how quickly our labor market has deteriorated: the U1 to U6 tables tell the story.

Update 03/14/2009
In response to a reader's comment:

There are three unemployment series available for the early 1930s: Stanley Lebergott’s, Michael Darby’s reworking of the Lebergott series, and the G.H. Moore series, available through NBER. (Michael Darby is the economist who pointed out that the Lebergott series included those on work-relief as unemployed. His series moves them to employed.) We used Moore’s series, which pretty much splits the difference between the other two. When you combine different series, usually necessary for long-term views, the series breaks themselves produce spikes or dips. Splicing the Darby series to the official BLS data makes it look like the unemployment rate jumped in 1940, which we did not want, and Lebergott’s inclusion of those on work relief as unemployed was in line with 1940 census practice.

Here are the yearly averages for the three series:

	Moore	Lebergott	Darby
1929		3.2%	3.2%
1930		8.7%	8.7%
1931		15.9%	15.3%
1932		23.6%	22.9%
1933	23.4%	24.9%	20.6%
1934	19.1%	21.7%	16.0%
1935	17.6%	20.1%	14.2%
1936	14.2%	16.9%	9.9%
1937	12.2%	14.3%	9.1%
1938	18.4%	19.0%	12.5%
1939	16.3%	17.2%	11.3%
1940		14.6%	9.5%

Basically, if you want to evaluate the effect of government work programs, compare the Lebergott series to the Darby series. If you want a more readable trend line (while avoiding accusations of playing politics) use the Moore series.

For more information and some notes on definitions, please see “Employment and Unemployment in the 1930s,” by Vanderbilt economist Robert A. Margo, available here: http://fraser.stlouisfed.org/docs/MeltzerPDFs/maremp93.pdf

Philippa Dunne and Doug Henwood

*There is currently a bit of a fracas over the reconstructed unemployment rates for the period prior to official series. Stylish Stanley Lebergott, the BLS economist who put together the most widely used series, categorized workers on emergency relief as unemployed. In the 1980s data reclassifying these workers as employed were released, a definition in line with current practice and more widely accepted. In the past month or so, those wishing to show the WPA programs did little to alleviate unemployment have been relying on the unrevised Lebergott series, and those taking the opposite view the revised data. Of course, if you compare the two series it appears that between 1934 and 1941 WPA projects took 2 to 3.5 million workers off the unemployment roles, and shaved the rate by 4 to 7 percentage points.

Why do they do it?

Arguing about performance-based pay is running neck-and-neck with grousing about bonuses, whether they be too big or too small, among popular topics this holiday season. In their upcoming paper, “Give & Take: Incentive Framing in Compensation Contract,” Judi McLean Parks (Washington University in St Louis) and James W. Hesford (Cornell University) test out their hunch that certain compensation packages may be linked to rising fraud, losses from which are currently estimated by the Association of Certified Fraud Examiners to total something like $994 billion annually.

Since compensation packages are considered a central tool in managerial control systems, managerial accounting research has long taken an interest in how compensation packages influence behavior.  A primary foundation of such research is agency theory, a model that assumes agent and principal are self-interested, but in divergent goals, that agents will shirk, “if necessary, [with] guile and deceit,” and that principals will attempt to control agents through monitoring or by aligning the interest of the agents with their own.  In theory, performance-based compensation systems are one way to accomplish the latter.  This may have worked well at GM in the 1980s, when line-workers were put on performance-based pay, so that when GM did well, they did well, but when the agents themselves are reporting the results, such contingency packages may instead encourage financial mismanagement and deceit.

In an effort to supplement empirical studies of performance-based pay, and to include penalty-contingencies, which are actually quite common, McLean Parks and Hesford undertook a controlled study.  Rather than the obvious choice of rats as participants, the authors brought in a random sample of students, paying them for solving anagrams under three compensation packages: flat salary, performance-based bonus, and performance-based penalty.  Each student was given a package with instructions, a “high-quality attractive pen” (keep your eye on these), and self-evaluation forms. Once they turned in the self-scored performance sheets, they threw away their actual work, allowing plenty of opportunity for fraud.

Basic results: those receiving flat salaries were the most honest in their reporting, those on bonus-contingent schedules were less honest, and those on penalty-contingent schedules were the least honest.  Even worse, when no ethics statement was signed, those on penalty-contingent pay were three times as likely as those on salary, and twice as likely as those on bonus-contingent pay, to steal those attractive pens.

The authors unearthed a concern about the use of ethics statements, such as the attestations all CEOs must sign under Sarbanes/Oxley.  Although, overall, 46% of those who did not sign such statements stole their pens, and only 29% of those who did sign statements did not “misappropriate assets,” the details are more complicated.  Those facing performance-based penalties were more likely to misrepresent their performance if they had signed such statements than if they had not. The authors suspect that the existence of the statements themselves suggested to the agents that the principals were weak on apprehending fraud. Why else would they be required to sign such statements?

McLean Parks sums up: “For years we have touted the basic mantra of pay for performance because that's the way you get the best performance. Maybe you get the best performance reported, but what's the underlying performance?"

Not really in the holiday spirit, but you can read the full study, still under review, here:

https://www.business.utah.edu/humis/docs/organization_962_1224879507.pdf

If We Make it to December

Since we have made it to December, that probably should be February or March, but it’s what Merle Haggard wrote. (A shout out to the handsome Hag as he recuperates in Bakersfield.) It’s hard to keep up with the onslaught of staggeringly bad economic news coming in these days. Not only that, we’re facing the fall-out of Secretary Paulson’s bewildering failure to manage the current crisis, or at least to maintain the all-important appearance that he knows what he is doing, and recently revised data indicates that the job market was in even worse shape than previously thought going into this mess. Nevertheless, like the tentatively hopeful recent lay-off in Haggard’s song, we do see some real opportunities for setting our “real” economy on a more fruitful course in the current turmoil.

During the boom there was a good bit of talk about how as a nation we can do without a strong manufacturing sector. The cliché became, “Michigan is irrelevant,” with abuse heaped on the Great Lakes manufacturing states for being beyond repair. Actually, those same states have made real progress in R&D employment, but it has not been enough to offset job losses in the automotive sector. As we re-evaluate our thinking, it’s clear that we need our manufacturing base: time to go crawling back to the Midwest. Current research suggests that design teams are more productive when they work closely with those building the products, which undermines the idea that the best course is to design things here to be made elsewhere, another reason to invest in domestic manufacturing. And the idea that accompanied waving goodbye to “dirty” manufacturing work, that there’s some sort of financial dark matter we’ve got going for us that could prevent a financial big bang, has really got to go.  It’s a shame that the terms our scientists come up with to describe true mysteries get abused like that, so let’s just say that although the current less awesome/more awful “big bang” wasn’t avoided, it’s surely a contender for great moments in creative destruction.

Multiplication

There is no question that public spending will be re-shuffled as we come to terms with the economic consequences of the slow erosion of our infrastructure, our manufacturing sector, and, in the longer term, our scientific research funding.  We’ve put together some stats on some of the economic benefits of shifting more public investment to these areas; there is reason to be hopeful.

Military spending was 3.8% of GDP in 2000, its lowest level since 1940. It rose to 4.7% in 2004, where it stayed until the end of 2006, then rose to 5.1% in the first quarter of 2008, and spiked to 7.4% in the third.  As this graph shows, our economy would look even rockier without this stimulus.

With the federal budget taking on water and the economy in turmoil, military analysts are certain that big spending on big projects, projects made even bigger by cost overruns and delays, will be curtailed.  Of course, none of this will turn on a dime, but a shift away from defense spending and toward other public projects that were left to languish is a shift toward greater stimulus. Military spending has an over-all economic multiplier of 1.61, which means that for every dollar of direct investment, another 61 cents of economic activity is generated. That’s actually pretty low, about equal to spending in the retail sector. For the broad sectors, the big multipliers are in manufacturing, 2.43, and construction, 2.08. Much of the public money we will spend to avoid a deeper recession will be made in subsectors of these two strong sets with even higher multipliers.  It’s important to remember that we are also coming off the bubble in residential construction, which has among the highest sub-sector multipliers, 2.27. So, what might we expect from some of the projects in President-elect Obama’s quiver?

Sub-sector Economic Multipliers
Highest:
Motor-vehicle manufacturing	2.87
Food and tobacco manufacturing	2.61
Farms	2.33
Residential construction (sub-sector)	2.27
Local government enterprises	2.22
Lowest:
Legal services and real estate	1.49
Warehousing and storage	1.43
Fed banks, credit intermediation, related	1.39
Rankings from 2006: Secretary Paulson not responsible for Federal Reserve banks ranking dead last.

Rocks and gravel

At their 2008 Annual Conference, American Society of Civil Engineer President D. Wayne Klotz declared this the Year of the Civilization Engineer. (We had hoped for the year of the Indy Financial Writer, but looks like they beat us to the punch.) He probably has a point, at least in terms of revenue.  As a nation we got a D in infrastructure in 2005, our most recent marking period, and ASCE projects that we need to invest $1.6 trillion to get our infrastructure into “good” condition. (For example the EPA estimates there is currently a $540 billion gap between what communities are spending and should be spending on water infrastructure. Disgusting examples of that include parasites traced to faulty pipes in a Colorado town. ASCE estimates that 27% of our bridges are “structurally deficient.” For that we have a tragic example: the collapse of the Mississippi River I-35W bridge in 2007. Those with strong stomachs can read more here: http://www.asce.org/reportcard/2005/index.cfm.)  President-elect Obama has pledged resources to this sector.  State and local government enterprises are labor-intensive (more on that below), and have an overall economic multiplier of 2.22, so the overall stimulus of spending on infrastructure projects is about twice that of spending on defense, and is basically even with residential construction.

Retrofitting: Make mine green

Obama has also promised to exert major efforts in retrofitting and other public projects aimed at a more fuel-efficient economy.  This is good news for our workers since a larger percentage of project capital is spent on labor in such projects than in new construction, where materials and underlying real estate eat up more money.  Robert Pollin of the Political Economy Research Institute at UMass, Amherst, and Bracken Hendricks of the Center for American Progress have researched the economic benefits of a $100 billion package, to be spent over the next two years, aimed at creating jobs laying the foundations for a low-carbon economy.  (For those with over-taxed memories, the stimulus checks sent to households beginning in April cost about $100 billion.) $50 billion would be allocated to tax credits to help businesses and homeowners finance retrofits and investments in renewable-energy systems, like geo-thermal.  This is important as it encourages private investment that will create jobs now, offset by lower fuel costs in the future. Direct government spending of $46 billion would be devoted to retrofitting, an expansion of freight rail and mass transit, and building smart electrical grids.  Of this, $26 billion would be devoted to retrofitting 20-billion square feet of public buildings, resulting in an estimated energy savings of $5 billion a year. The remaining $4 billion would be set aside for federal loan guarantees to underwrite private credit for investments in renewable energy and building retrofits. Using the Bureau of Economic Analysis’s input-output tables, Pollin computes that every million spent on public infrastructure creates about 17 jobs, and on green investments 16.7 jobs, which compares to 14 jobs for tax cuts for household consumption, and 11 jobs for military spending. Putting it all together he believes at the very least the program he describes would replace the 800,000 construction jobs we have lost in the last two years, and is more likely to create about 2 million jobs, bringing the unemployment rate back into the low-5% range. (More here: http://www.peri.umass.edu/fileadmin/pdf/other_publication_types/peri_report.pdf; Map of some working projects available here: http://apolloalliance.org/apollo-14 )

Michigan, Ohio, Indiana: we can’t make it without them

We have been asked our opinion on the wisdom of advancing bridge loans, in addition to the $25 billion set aside to enable the retooling necessary for producing more fuel-efficient cars, to the Detroit 3. It’s unfortunate that this question is devolving into a battle between Democrats and Republicans; there’s a lot at stake.  Auto-manufacturing has the highest overall economic multiplier of any subsector (2.87) and job multipliers between 5 and 6.5 for each primary assembly job. In a report that received wide attention, the Center for Automotive Research suggested that a failure of any one of the Detroit 3 could set off cascading job losses up to 2.5 million in the first year, as well as heavy hits to state and federal revenues. Some have argued that CAR’s numbers are too high. Well, OK then, let’s say job losses of 1 million; that’s still awfully high. Although it may be true that many of the D3 workers would eventually be picked up by the transplants, throwing the region—MI, OH and IN have a combined population of about 28 million, or 9.3% of the U.S. total—into that kind of turmoil is too risky right now.

Some are suggesting bankruptcy is the better way, but we’d suggest three major risks to that. First, an auto made by a bankrupt company would be a hard sell.  Second, restricting funds for new products that may be truly successful, like the Chevy Volt, is throwing in the towel prematurely. And, third, bankruptcy is a unpredictable process and can quickly move to liquidation, which would likely be the end of our domestic automotive industry. Some think that’s a good idea. We don’t. If we are serious about rebuilding our manufacturing sector, a clear lesson from the current meltdown, we need our domestic auto industry to be whole again.

Looking forward, it’s worth noting that the automotive industry ranks sixth in R&D spending, with annual outlays of about $18 billion.  Recently built shiny R&D centers in the Midwestern manufacturing states may be at odds with the popular stereotype of the Rust Belt, but they’re there, and it’s a smart decision to build on what we have, and develop the synergy between R&D and manufacturing that will support innovation in transportation systems. [More here: http://www.nsf.gov/statistics/seind08/c4/c4s3.htm]

The original plan was to ask for $50 billion, but the request was halved, according to one industry analyst, because the full amount sounded unrealistic.  He added, back in October, that the $50 billion now looked like chump change, and he was referencing Secretary Paulson’s $700 billion bailout, not the $7.4 trillion currently set aside by the Fed for assorted bucket work.  With somewhere between 1 and 3 million good-paying jobs at stake, a relatively modest $25 billion spent heading off yet another crisis sounds pretty good, especially since there is nothing in the TARP legislation that would prohibit this. But we need a real plan from management, and should allow no excuses from anyone. It’s alarming to hear elected officials suggest we can’t make these loans because the auto chiefs will just go back to doing what they have always done. We wouldn’t accept such ineffectual reasoning from our own children, would we?  And we need to allow for the possibility that the importance of product innovation has finally been embraced at the top levels. (http://www.cargroup.org/documents/InnovateorDie_clean.pdf)

Emergent phenomena

Since we’re talking about shuffling funds, we want to make our standard plea for public funding of scientific research at levels adequate to maintain our international leadership. A most galling development in recent years is the assertion that the US would naturally hold the lead, coupled with dwindling public funding of the crucial research behind that leadership.

Here’s one example: Throughout the 20th century, the United States held the undisputed lead in Condensed-matter and materials physics (CMMP). CMMP, the largest physics subfield, comprises both pure and applied research into complex phenomena born of simple things. Although decades often pass between the humble advances in our understanding of those simple things (rocks, ice, snow, water) and the dazzling inventions that rock our world, it is widely accepted within the scientific community that long-ranging CMMP research leads the technological revolution.

Early in the 20th century parent companies invested in their long-term futures by encouraging high-risk long-range research in their industrial labs. GE founded their labs in 1900, Bell in 1925; and IBM’s TJ Watson in 1945. The results were stunning: X-ray tubes, transistors, lasers, the integrated circuit, and the discovery of cosmic micro­wave background radiation matching just what a team of astrophysicists at nearby Princeton had calculated would linger from the Big Bang, were all products of these privately funded labs.

Although private institutions currently provide two-thirds of overall R&D funding, the rush to market pushes them to focus on incremental improvements to already existing products; they often concentrate on the D while neglecting the R, and funding of longer-range research has dropped to just 10% of the industrial investment budget. (The NAS cites the research models in many of the new venture-capital funded start-ups as a big contributor to this mindset.) The federal government remains the largest supporter of CMMP research itself: current funding levels are $600 million a year, roughly flat over the last decade in inflation-adjusted dollars. But the likelihood that a CMMP grant application will National Science Foundation funding has dropped from 38% to 22% in the last five years; new investigators face a bleaker 12% chance, down from 28%. And our CMMP PhD awards have fallen 25% over the same period. At the same time other countries are rapidly increasing funding. In the last decade the number of articles published by U.S. authors in two international scientific journals has just held steady, causing the percentage of articles published by U.S. authors to fall from 31% to 24%.  If part of the plan is to maintain our lead in the international scientific community, as well it should be, we can’t continue to accept a crippling lack of funding. But we can end with some encouraging news.

Bucky paper: That’s what we’re talking about!

In October, an international team at Florida State University announced they have made significant progress in developing manufacturing techniques that may soon make bucky paper competitive with top composite materials currently on the market. We’ll guess that when many web-surfers clicked on the link only to see that the thin sheet of aggregated carbon nanotubes is virtually indistinguishable from a small sheet of origami paper they quickly moved on.

But bucky paper has the requisite characteristics of a true materials break-through:

1. Its development is moving at a snail’s pace; 2. It is an unexpected side product of a different quest. (In 1985 researchers at Rice University set out to create the same conditions that exists in carbon-creating stars. One “extra character” showed up out of left field: the buckyball, AKA the third form of pure carbon we have discovered.  While fooling around with buckyballs, researchers stumbled upon their tendency to stick together and, by filtering them through a fine mesh, produced bucky-paper);  3. Its physical properties are hard to fathom—one tenth as heavy but potentially 500 times stronger than steel, conducts electricity like copper and disperses heat like brass (unlike other composites), and made from carbon molecules 1/50,000 the width of a human hair; and,  4. It’s a true international collaboration. Lockheed Martin Missiles chief technologist Les Kramer suggests bucky paper will be a radical technology for aerospace, others possibly a Holy Grail. (More here: http://www.hpmi.net/)

What’s not to like? Let’s make sure there’s more to come.