DRI-364 for week of 9-23-12: Revisiting the DRI and Related Economic Indices

An Access Advertising EconBrief:

Revisiting the DRI and Related Economic Indices

Periodically this space has revisited Access Advertising’s Driver Recruiting Index (DRI). This index tries to estimate the real-time ex ante demand for commercial drivers. It samples the classified ads placed to recruit drivers in 32 geographically dispersed major-metropolitan newspapers throughout the U.S. Every now and then, we place the DRI alongside other trucking, transport and freight indices and gauge its movements in relation to indices of overall income and employment.

The DRI in the 2nd and 3rd Quarters

Like the overall economy, the DRI got off to a reasonably fast start after a promising end to 2011. But it soon became clear that, like the U.S. economy, the DRI was going to fall short of expectations (let alone hopes) in 2012. The Index pierced the 200 barrier for the only time so far this year on March 25, flirting with a raw score of 500 (an achievement it exceeded 14 times in 2011).

After that, it has been all downhill. Year-over-year comparisons have occasionally fallen over 20% short of 2011; 10% shortfalls have been commonplace. Driver demand has never really caught fire, peaking in late spring and skipping both the normal summer high and the fall upturn.

Second-quarter GDP growth was also disappointing, ending up at a tepid 1.7%, even below the moderate 2% in first quarter. Although unemployment has now declined fractionally to 8.1%, this reflects only the decline in the size of the labor force. The number of new jobs created has continued to languish.

The only good news has been a Wall Street rally engineered largely in response to the latest quantitative easing by Ben Bernanke’s Federal Reserve. This is probably responsible for a recent upsurge in consumer confidence in the economy.

The DRI as Economic Indicator

If the DRI’s disappointing performance has mirrored that of general economic indicators, this very congruence speaks well for the DRI’s performance as an economic indicator. Trucking handles some two-thirds of all freight by volume and about 80% by value; many production inputs and final goods travel the nation’s roads and highways. We expect changes in trucking activity and driving demand to track overall trends in production, income and employment. (Whether the DRI is or should be a leading, coincident or lagging indicator is a complicated question that will be broached later.)

The DRI continues to display other desirable properties as well. One of those is (relative) stability. The very ubiquity and prominence of trucking strongly suggests that we should not expect to find the Index fluctuating widely from week to week. While trucking firms ordinarily experience high rates of turnover, this is a long-term phenomenon, responsive to demographic factors (average age, cultural shifts) and cyclical variables (wage changes, politico-regulatory changes). A particular trucking firm may well experience a sudden, substantial need for drivers, but this will usually represent a geographic shift of demand that is offsetting in the aggregate. Significant increases or decreases, when they occur, are usually persistent, cyclical changes in trend, not random fluctuations.

For a concrete illustration, compare the DRI with TransCore’s DAT North American Freight Index, which compiles data from the company’s load board network in the U.S. and Canada. Neither the DRI nor the NAFI is seasonally adjusted, but the contrast in variability is stark. Earlier in 2012, NADI racked up this record of month-over-month fluctuations: March 2012 – up 40%, April 2012 – up 3.5%, May 2012 – up 1.7%, June 2012 – down 2%, July 2012 – down 20%, August – up 1.1%. Monthly fluctuations of 20% in the DRI would be observed only at a seasonal or cyclical peak or turning point, and a 40% monthly change is unheard of.

The DRI and Comparable Economic Indicators

Given the importance of trucking in the production chain, it is surprising that the DRI is one of few time-tested, reliable trucking indices – and the only one to track driver demand. A rundown of the others reaffirms our understanding of what makes for a good index and confirms the DRI’s recent congruence with its brethren.

The Cass Freight Index compiles data from the expenditures of 350 of the largest freight shippers. Early in the year, the Index flexed its muscles with a 2.5% increase in February 2012. Then, along with the economy at large, it began to lose vitality. Increases diminished to 2.1% in March, 1.9% in April, 1.8% in May and 1.3% in June. In July, the Index turned negative with a 0.1% decrease, followed by a 1.1% fall in August. Sponsors and analysts cited a buildup of inventories, a fall in international trade and recent declines in manufacturing output as recorded by the Institute of Supply Management’s index, which had fallen for three straight months.

The American Trucking Associations are the Establishment of the trucking industry and Chief Economist Bob Costello is the voice of starched, high-collared authority. The ATA Truck Tonnage Index is perhaps the most widely cited trucking index, not only by private-sector analysts but even by the federal government. Although the ATA’s respect for authority imparts a big-government bias to its occasional obiter dicta, its economic data are accorded the utmost respect.

The TTI’s recent numbers paint the same by-now-familiar picture of a stalling, sluggish trucking sector. March saw a 0.2% increase, April improved to 1.1% but May backtracked to 0.9%. June went back up to 1.1% but July was unchanged. Typically, Costello’s public comments wrapped the language of an economist inside the rhetoric of a politician. He depicted “…an economy that has lost some steam but hasn’t stalled.” The ATA’s corporate commentary was more telling, noting that “…the index… has been moving mostly sideways in 2012.”

The Truck Tonnage Index is an important component in the federal government’s Transportation Services Index (TSI), which is published by the Bureau of Labor Statistics (BLS). For most of 2012, this index has alternated back and forth with little net increase to show for the year. In February, the TSI rose 0.5%, but it fell back 0.8% in March. April brought a modest rebound of 0.2% but in May the Index was unchanged. June and July saw offsetting 0.1% changes.

These indices display the bedrock virtues noted above: stability and congruence with general economic activity and with each other. One of the rising economic forecasting stars of recent years was the Ceridian Pulse of Commerce Index (PCI), compiled by respected econometrician Edward Leamer of UCLA. After recording some lackluster increases earlier this year, the Index ceased publishing somewhat mysteriously following its May release. Ceridian has responded to queries by saying that although the Index does not now publish its results, it is contemplating a return on a subscription basis and is soliciting indications of interest among potential customers.

Is the DRI a Leading, Lagging or Coincident Indicator?

Undergraduate students of economics are taught that economic indicators come in three flavors – leading, coincident and lagging. These indicate whether changes in the indicator lead, accompany or lag changes in the general level of economic activity. Since the unknown future preoccupies our attention, leading indicators are especially studied and prized.

There has long been a casual presumption that trucking indices are, or at least should be, leading indicators. Disruptive phenomena like layoffs and unemployment are presumably necessitated by the accumulation of unsold goods. Since trucks carry goods and the inputs necessary to produce them, freight shipments should register the incidence of cutbacks in production and materials. This is the sort of logic that supports the categorization of trucking as a leading indicator.

Early in its life, though, the DRI was observed to be a lagging indicator. We rationalized this as the caution of recruiters, who – unsure and suspicious of the depth and duration of any increases in freight supply after the Great Recession – waited to verify the persistence of demand before incurring the fixed costs of hiring. In fact, similar behavior had been recorded in connection with the Index of Classified Advertising, an economic index that bears a strong family resemblance to the DRI.

Since leading and lagging indicators are at opposite poles, this plants a seed of skepticism about the traditional taxonomy of economic indicators. Further consideration should nourish that thought.

The inherent logic of leading economic indicators says that they can be used to predict the economic future – or at least the turning points of business cycles. And this is simply impossible.

Anybody who can accurately predict the future onset of a recession – or, for that matter, the end date of one – can earn a fortune by so doing. Anybody who can repeat the performance reliably can become fabulously rich. Business forecasters are not fabulously rich. Ergo, they cannot predict the beginning or ends of recessions. Not reliably, anyway.

This must mean that leading economic indicators do not really lead. Maybe they don’t even indicate. In any case, something isn’t quite kosher. The question is: what?

The Theory of the Business Cycle – Such As It Is

Something else that all undergraduate students of economic statistics and econometrics learn is that economic theory and logic form the basis for all empirical work. Without theory, we cannot know what data to collect or what relationships to posit between the variables that make up the data. So an economic model is borrowed or created to embody the relationships upon which data is collected. Only then can the data gathering and testing begin.

But in business forecasting that runs us smack up against a formidable obstacle. There is no generally accepted business-cycle theory. The categories used by the National Bureau of Economic Research to codify episodes of the business cycle – expansion, peak, contraction and trough – were developed by institutional economist Wesley Mitchell in the early 1900s, based on years of observation and study of past recessions. Unfortunately, observation is not theory.

The national income and product accounts used to compile U.S. economic data were developed later, based largely on the economic categories developed by English economist John Maynard Keynes in his influential work The General Theory of Employment Interest and Money. But Keynes explicitly denied that the General Theory contained any theory of the business cycle. He simply declared that capitalist economies suffered from a chronic shortage of aggregate demand – e.g., private spending by households and producers. He never said why the shortage existed. Government should make up for this shortfall, Keynes maintained, by running budget deficits that increased the aggregate total of aggregate demand or spending. Essentially, government should commit to purchasing whatever volume of output is left unbought by households and producers, so as to insure full employment. Keynes didn’t supply a theory to account for the business cycle, only a purported remedy to cure the symptoms.

Without knowing where the shortfall in spending lies, we cannot predict where to look for leading indicators at any stage of the business cycle. There is one school of thought whose business-cycle theory offers general advice on this point. That is, it doesn’t offer a list of specific industries, sectors or indicators as such, but instead provides advice about where to look for them in general cases.

The Austrian theory of the business cycle pinpoints monetary expansion by government – probably supervised by a central bank – as the proximate culprit behind recessions. By driving interest rate below the “natural rate of interest,” the rate that would equate the saving households and producers want to do, the money creation will make interest rates artificially low. This makes long-lived, capital-intensive production processes artificially attractive to producers. In turn, this creates a “bubble,” or artificial excess prosperity, in the sector thus favored. While it lasts, this bubble can seem deliriously prosperous, almost too good to be true. That is because it is too good to be true, as the drawn-out period of housing prosperity in the U.S. proved. But when the bubble bursts – owing either to a rise in interest rates or a rising burden of debt – the artificially-prosperous sectors are the first to crash. They are the leading indicators of the coming recession.

In general, then, leading indicators are those pertaining to the sectors receiving the artificial encouragement. In the U.S. during the 1990s and early 2000s, this would have been the housing sector. But this does not mean, as many have implied or outright insisted, that the housing sector should be the first to recover its balance. And it does not mean that nobody can recover until the housing sector does. Indeed, the reverse is more nearly true – housing should be the last sector to recover fully. It also means that the stubborn attempts to stage-manage recovery in housing by holding interest rates low and artificially raise housing prices through government purchases of mortgages and securities are counterproductive. After all, this is exactly the process that caused the problem in the first place – repeating it merely enlarges the backlog of adjustments that must occur before recovery can take place.

An Austrian Look at Economic Indicators

The effect of this theory on forecasting practice is striking. Housing becomes a leading indicator for the downturn phase because it is a long-lived production process, extremely sensitive to interest rates. But it is a lagging indicator for the upturn; it cannot recover until all of the bad investments made during the bubble phase are liquidated and their resources reallocated.

What about trucking? Well, trucking feeds the housing industry its materials and some of its manpower, so trucking shares this dual forecasting status. Sometimes it will be a leading indicator, sometimes a lagging one. Moreover, trucking feeds other industries as well, so it simply cannot be pigeonholed by a simplistic taxonomy. A sophisticated approach to business cycles requires us to abandon our primitive definitions of economic indicators. First, we must classify industries and sectors according to their status in the production and consumption hierarchy. Second, we must recognize the difference between recession and recovery.

We have still not exhausted the reserves of analysis, since there is still the possibility of inherent cyclical movements in economic activity that are not driven by monetary mistakes made by the authorities. The fact that money substitutes for barter in allowing human beings to trade the product of their labors solves huge problems, but it also creates smaller ones. These subtle problems may well mean that we have to live with an unavoidable element of cyclical instability in our economic life. And this may demand still more adjustments in the terminology of forecasting.

Progress Report on the DRI

The DRI is completing its fourth year of operation. It has passed the standard tests of stability, reliability and usefulness that apply to economic indices. Of course, it has not unlocked the door to wealth and fame available to any economic index that could actually forecast the future – but, as we have seen, that is a chimera. Explaining the past and recognizing the present is tough enough and a worthy goal for any economic index. Many a worthwhile aspirant has fallen short of even this limited objective; Ceridian’s PCI may be the latest addition to this list.

Nearly four years in, the DRI is still trucking.

DRI-420: It’s Official: The Recovery is Receding

Coping with change is famously difficult. The first stage of the adjustment is recognition. It’s hard to adjust to something when you don’t realize – or won’t acknowledge – its reality. That is the problem most people have adjusting to the current state of the economy. They can’t or won’t acknowledge that we are undergoing an unprecedented transformation rather than merely another business cycle.

We periodically review the performance of Access Advertising’s Driver Recruiting Index (DRI) as a tool to gauge the ex ante demand for commercial drivers. We juxtapose it alongside other indices of trucking and transportation to review their performance and assess the state of the economy. Two salient points emerge from our latest review.

First, the economy in general and the transportation (and trucking) sector in particular are caught in a limbo that is neither recession nor expansion. Second, experts who have been slow to recognize this fact are now belatedly doing so.

The DRI’s Spring Plateau

In 2011, the DRI began its annual climb up the ladder in mid-January, then took off sharply in February. It plateaued in April and May, only to accelerate again in June and July. Total upward movement from January to July was dramatic.

This year, after one of the warmest winters on record, the DRI began with its usual vigor in February. But in early March, it reached a plateau from which it seldom deviated through mid-June – a most unusual seasonal performance under any circumstances and even more so now. The index never came within hailing distance of last year’s spring highs and remains mired at least 10% below the values on comparable dates last year.

It is not unusual for the DRI to increase at certain times of the year or in appropriate circumstances, or for it to decrease at other times. But plodding consistency during a season and circumstances in which rapid increase would be expected is unusual. Moreover, this mimics the DRI’s trance-like behavior early last fall, when the increases in trucking activity normally associated with preparation for the end-of-year retail rush did not materialize.

Our recognition of this uncharacteristic lassitude by the DRI and the economy in general is on record. Now, however, we are part of a chorus of mainstream commentators on transportation and the economy.

The ATA Gets on Board

A longtime trucking bellwether is the American Trucking Associations’ (ATA) Monthly Truck Tonnage Index. This seasonally adjusted index of trucking volume backed up its 1.1% decline in April with a 0.7% fall in May.

ATA’s Chief Economist Bob Costello is a reliable go-to guy for a quote on the economy in general and trucking in particular. He is reliably mainstream in his views – which are favorable to big business and big government. He is consistently cautious in his projections – which is to say, not given to dramatics or overstatement.

So when Costello calls the Truck Tonnage Index’s recent dips “reflective of the broader economy, which has slowed,” you need look no further to discern the consensus of the forecasting fraternity. Costello’s lineup of suspected culprits for the slowdown is predictable – Eurozone turmoil and U.S. electoral uncertainty. This double whammy clouds crystal balls and turns corporate planners into chickens who sit clucking atop cash instead of hatching new investments.


The Transportation Services Index (TSI) of the Bureau of Labor Statistics is another familiar index of transportation activity. The Truck Tonnage Index is a component of this broader survey of the overall transportation picture, compiled under the auspices of the Department of Transportation.

Not surprisingly, the federal government moves slower than the world it governs. Consequently, the most recent month available for the TSI is April, during which the freight index rose at the snail’s pace of 0.2%. The DOT summarized recent movements of the index thusly: “Plateauing of the freight TSI since January appears to reflect slowing growth in the general economy.”

The Cass Index

The Cass Index is yet another transportation index of long standing. It compiles separate indices for volume and expenditures. The volume index has increased throughout 2012, but the increases have been steadily decreasing in magnitude – 2.5% in February, 2.3% in March, 1.9% in April and 1.8% in May.

Commenting on this record in the June 5, 2012 posting of Logistics Management, industry analyst Jeff Berman observed “…a dearth of people that truly have real confidence in the economy,” noting that “volumes are still not close to 2007 [e.g., pre-recession] levels.” The economy, he concludes, “remains in teeter-totter mode.”

The Ceridian PCI

The Ceridian Pulse of Commerce Index (PCI) is the brainchild of UCLA econometrician and forecaster Edward Leamer. It captures real-time data on the diesel-fuel consumption of over-the-road trucks at some 7000 locations across the U.S. from the transactions cleared through stored-value card provider Ceridian.

Like most transportation indices, the PCI has registered slowing growth in early 2012 – 0.7% in February, 0.3% in March and 0.1% in April. At first glance, May seemed to reverse this trend with 0.8% growth. But there are reasons to take even this modest piece of good news with a grain of salt.

For one thing, as pointed out by Jeff Berman in Logistics Management on June 7, the May figure still represented a year-over-year decline of 0.6%. Even more telling is the fact that the volume of diesel-fuel purchases reacts strongly to diesel-fuel prices. These, in turn, depend on oil prices and the health of diesel-dependent economies like China and India. Recent downturns in both the above indicators are good news for diesel-fuel consumption specifically, but they are something of a mixed blessing for overall U.S. economic activity.

A decline in oil prices caused by an increased supply of oil is an unambiguous benefit for us. This increases the amount of resources available for production purposes, and the reduction in oil prices translates into lower costs for countless production processes in which oil is an input. But if the decline results from a reduced demand for oil at home and abroad, it is a harbinger of recession. The lower demand will result in less oil being purchased and used in production, leading to less output of derivative goods and services. Moreover, less demand for oil abroad means lower incomes and less demand for U.S. exports, which will ultimately lower our incomes and imports as well.

We are experiencing both effects – the former due to improved recovery methods like fracking and horizontal drilling and sources like shale oil, the latter due to a myriad of influences including Eurozone woes, Chinese recession and our own slogging-through-molasses economic climate. At the moment, the bad tends to outweigh the good. In turn, this tends to mitigate the significance of upturns in the PCI.

Leamer himself is just as lukewarm about our prospects as other transportation forecasters. In Berman’s piece, he characterizes trucking as “soft generally” because “growth in the components of the economy that depend on trucking is not strong.”

Light Dawneth at Last

The current consensus has been slow in forming. In the three years since the official end to the Great Recession in June 2009, mainstream commentators like Bob Costello and Edward Leamer have continually insisted that prosperity was just around the corner. In effect, they have assumed that the United States was living through a typical business cycle, characterized by a downturn that eventually hit bottom, followed by an upturn that picked up steam until it became a full-fledged expansion. Cycles might differ in detail, with respect to trajectory of contraction or expansion and duration of recovery, but not in terms of their general character.

When the rate of GDP growth began to increase somewhat in 2010, Costello confidently asserted that growth would soon accelerate and unemployment would start to fall. After all, he reminded us, unemployment is a lagging indicator and usually is the last symptom of recession to abate once expansion sets in. Late last year, Leamer reacted to a favorable monthly PCI by reading into it the long-awaited resurgence of trucking that would lift the economy off the mud flats and into the whitewater of fast-track growth.

Few economic indicators are as volatile as housing starts, but the slightest upward blip in housing over the last three years has invariably been touted as a neon arrow pointing unerringly at the promised land of full employment. Despite all economic logic to the contrary, the presumption has been that because housing was the most severely affected sector during the Great Recession, it must of necessity lift the general economy up to recovery on its shoulders.

In view of this record, the question isn’t so much how or why we all abruptly find ourselves on the same page. Instead, we should wonder why it took so long.

Revolution and Crisis

The science of macroeconomics (an oxymoronic term that is nonetheless useful) has reached a watershed moment. In his landmark study, The Structure of Scientific Revolutions, Thomas Kuhn decried the conventional view of science. A scientific theory or paradigm is not formulated, tested experimentally and formally accepted or rejected. Instead, it is adopted on the basis of practical usefulness and retained until supplanted by a more useful theory. Replacement is not effected by testing but rather in response to a crisis – the failure of the reigning theory to perform the tasks that made it useful originally.

We are now in the midst of such a crisis.

The reigning theory of macroeconomics was developed by John Maynard Keynes over 75 years ago using a combination of old and new ideas. The principal old idea was that capitalist economies suffered recurrent insufficiencies of spending that gave rise to depressions and unemployment. The principal new idea was that government could and should remedy these shortfalls by spending money and/or inducing citizens to increase spending. Eventually, economists borrowed the term stimulus from behavioral science to characterize these policies. The government spending should be funded by either borrowing or money creation. Induced private spending should be funded by either tax reductions or money creation. Increases in private investment should be induced by artificially lowering interest rates via money creation. Increases in employment should be induced by exploiting “money illusion” of workers – that is, by lowering the purchasing power of wages by money creation, fooling workers into thinking their real incomes had risen while persuading illusion-free businesses to hire more workers at lower real wages.

For over forty years, this theory was subjected to rigorous theoretical and empirical scrutiny and extensive practical application. By roughly 1980, the results were in. The theoretical scrutiny was unfavorable to the theory: no tendency toward underconsumption and unemployment was inherent in the system, government action would be unavailing, unnecessary or even counterproductive; and “money illusion” did not exist. Empirical studies were either unfavorable or equivocal. Practical application of the theory was widespread and remarkably consistent; it failed whenever and wherever tried.

In retrospect, this should not have been surprising. By 1980, the American economy had endured over 30 recessions. It had recovered from all of them without the application of the theory.

Still, the theory was not abandoned.

Macroeconomists claimed that the theory was still useful because government policy would work faster than allowing markets to recover from recession and depression unaided. Why suffer for two or three or four years when we can cure the problem in a few months or a year with the aid of government stimulus?

A Kuhnian explanation would instead find other ways in which a demonstrably wrong theory might nevertheless be useful. Government gradually took on the role of problem solver of first resort, not just in economic policy but in every nook and cranny of society. It actually solved few, if any, problems, but it was required to look as if it were trying to solve them. Trying hard.

Democrats, who had been the first party to advocate tax reductions as economic stimulus, eventually had to repudiate this policy because it supposedly enriched the rich. Republicans could not endorse a policy of government spending for economic- policy purposes because it would enlarge federal-government budget deficits. Both parties desperately needed a way to look busy. By default, they turned to monetary policy; e.g., money creation.

Ironically, Keynesian theory had originally rejected money creation as ineffective, but its practitioners had to abandon that stance for tactical reasons. Now they were backed into the corner of having to rely on it almost exclusively.

The economic theory that had proven utterly bankrupt as economics now became the sole policy tool of both political parties, virtually by default. It had never worked. Nobody in Washington, D.C. really expected it to work. Nobody cared all that much whether it worked or not.

Keynesian economics was in the same position as medicine prior to the eighteenth century. Doctors had few remedies that worked, but they continued to use the ones they had even though they seldom, if ever, cured anybody. If the doctors had admitted the truth, they would have had to stop being doctors. Macroeconomics had established a secure beachhead in the economics profession, with course offerings at every level of instruction, dedicated scholarly journals, major research grants, government positions and a public mission to make the world safe for markets. Admitting the truth about the theory that had midwived all that would have forfeited their gains.

What Time’s the Next Revolution?

So much for politicians, bureaucrats and academic economists. Where does that leave the rest of us? Essentially, it leaves us pacing the streets, looking around nervously, waiting for the next revolution. What we need is the next scientific revolution, and a theory to take the place of the failure being propped up by the Washington, D.C. policy Establishment – a composite version of Frank Morgan in The Wizard of Oz.

Heretofore we have been in denial. We have been telling ourselves that we went through a bad time in 2008, but the worse is over and we’re gradually getting over it now. Only it is now beginning to dawn on mainstream pundits that we’re not really getting over it – that, in fact, we may be getting ready to repeat some of the worst all over again.

We’re starting to realize that hardly a man is now alive who remembers the famous days and years when unemployment wobbled between eight and ten percent for over three years with no sign of relief. Interest rates have never been this low for this long – and what has it accomplished? Amend that slightly – what good has that accomplished? When in peacetime has government debt ever loomed so large? When has regulation bound so tightly? When has freedom seemed so tenuous?

When at last we have mustered the courage to admit the truth, the next stage will be to face the fact that Keynesian economics had no theory of the business cycle as such. Keynesian theory never asked why aggregate demand declined. The question didn’t seem to matter because the answer didn’t affect our course of action, which was to spend ourselves silly until things got better.

Well, we’re silly and they’re not better. Now it’s time to ask what really causes the business cycle. Wisdom begins when we acknowledge that the only time we faced a climate of recurrent limbo such as this one was in the 1930s – after both the Hoover and Roosevelt administration tried every interventionist nostrum under the sun to artificially cure the recession that began in 1929. As Roosevelt’s Treasury Secretary, Henry Morganthau, admitted to his diary, they ended up in 1939 worse off than when they started. Only when FDR himself forsook “Dr. New Deal” for “Dr. Win-the-War” were the chains hobbling American business broken. After World War II, with Roosevelt dead and no sponsor for the New Deal, a Republican Congress and tax cuts ushered in the greatest one-year boom in U.S. economic history.

If we went to the doctor to be treated for a serious illness and he offered us a new drug, how would we react? Would we not ask if it had been tried out? Would we not expect to find a history of successful use? If we found just the reverse – a history of failure – would we not reject the drug? If the only rebuttal argument the doctor could muster was, “Well, we can’t just stand here and do nothing,” wouldn’t we at the very least have the gumption to fire back, “Oh, yeah? Why not?”

This much can be done by any intelligent layman. No Ph.D. in economics is required. Afterward will be the time to grapple with the complexities of intertemporal capital theory and dynamic adjustment, to penetrate the mysteries of the structure of production. You have to learn to crawl before you can walk.