America’s Financial Crisis Is Now


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Three Economic Charts That Will BLOW YOUR MIND,” at RightWing News, offers some tantalizing statistics about the relationship between federal tax receipts and GDP. The bottom line:

The key thing to take away from this is that the amount of revenue the government can bring in via the income tax is, for whatever reason, more inelastic than most people think. That’s yet another reason to put more emphasis on balancing the budget via spending cuts as opposed to trying to fix the problem with tax increases.

Now, if Hauser’s law is as spot-on as it has been in the past … it’s going to be difficult to raise the government’s revenue level much beyond the 20% mark….

I have no quibble with the proposition that the U.S. government has made unaffordable, unilateral “promises” about Social Security, Medicare, and Medicaid benefits. But I must take issue with the focus on the income tax and Hauser’s law, which is

the proposition that, in the United States, federal tax revenues since World War II have always been approximately equal to 19.5% of GDP, regardless of wide fluctuations in the marginal tax rate.

It is necessary to step back from a myopic focus on the federal government and look at all government receipts and expenditures in the United States. The need to do so arises from two facts: (1) State and local spending is substantial, and (2) federal, State, and local finances have become tightly bound together since the advent of revenue sharing and block grants, and with the explosion of federal statutory and regulatory commands to the States.

I begin by looking at the historical record of government income and outgo. That leads me to the future, in which “entitlements” loom unaffordably large . There are three broad paths along which to proceed: cut “entitlements,” borrow considerably more, or tax considerably more. I explain why the second and third options are untenable and economically destructive. The only viable alternative is to cut “entitlements,” and to begin cutting now.


Here is how State and local spending stacks up against federal spending:

Federal vs state and local spending pct GDP
Sources: Derived from U.S. Department of Commerce, Bureau of Economic Analysis (BEA), National Income and Product Accounts (NIPA) Tables: Table 3.2 Federal Government Current Receipts and Expenditures (lines 26 and 40-45) and Table 3.3 State and Local Government Current Receipts and Expenditures (line 33).

State and local spending is not insubstantial, and has risen in recent decades, with a lot of help from the federal government. Federal grants to State and local governments have risen steadily from almost zero in 1929 to upwards of 4 percent of GDP in recent years. (I have excluded those grants from federal spending to avoid double-counting.)

Here is an aggregate picture of federal, State, and local spending and receipts.

Combined government spending and receipts
Source: Derived from NIPA Table 3.1 Government Current Receipts and Expenditures (lines 7, 19, 30, and 33-39).

Despite Hauser’s “law,” government receipts, as a percentage of GDP, rose steadily from 1929 until 2000, peaking at 32 percent. The post-2000 decline can be attributed to slow economic growth (capped by the recession of 2008-2010) and the so-called Bush tax cuts (which Congress approved initially and again in 2010). I have nothing against the tax cuts, except for the fact that they were not matched by spending cuts. The real burden of government is measured by spending, which diverts resources from productive uses to ones that are less-productive (e.g., public education), counter-productive (e.g., regulation), and downright destructive (i.e., growth-retarding and inflationary). The fact that lenders have increasingly borne the monetary cost of the burden of government has not offset its egregious economic effects. And, as I discuss below, without drastic spending cuts (relative to GDP) there will come a day when lenders will shrug off the burden or demand a much higher price for bearing it.

In any event, regardless of generally diminishing receipts in the first decade of the 21st century, government spending rose as a percentage of GDP, for several reasons. First, there was (and is) slower economic growth, due in no small part to the preceding decades of governmental interference in economic affairs. On top of that, there was Obama’s “stimulus package,” which was meant to end the recession of 2008-2010 but did not (because it could not); the recession ended in the normal way, through the recovery of “animal spirits” and consumer confidence. Then there was (and is) a growing population of persons eligible for Social Security, Medicare (supplemented by “free” or “cheap” prescription drugs), and Medicaid — a population made all the more eager to claim its “entitlements,” given the state of the economy. Finally, and almost incidentally, two foreign wars were fought simultaneously (though with varying degrees of intensity) throughout the decade.

To focus only on federal spending, as I say, is myopic because State and local governments have a habit of raising State and local taxes when so-called federal grants are cut back. (I say “so-called” because the money for those grants is provided largely by taxpayers who are, of course, denizens of the States and their political subdivisions.) In addition to the possibility of higher State and local spending in reaction to cuts in federal largesse, taxpayers — not public-sector unions — should be up in arms about the above-market compensation of government employees. A significant portion of that above-market compensation comes in the form of cushy pension plans, which allow “public servants” to receive high fractions of their salary (sometimes as much as 100 percent) for life, and to begin receiving those payments when they are in their 40s and 50s, after having held a government job for 20 years or so. As a result of these obligations and other undisciplined spending habits, State and local governments have liabilities of more than $7 trillion.

Which brings me to the 500-pound gorilla: the federal government.


Perhaps the most interesting lines in the second graph (above) are the three at the bottom. The gap between the cost of social programs (green line) and “contributions” to those programs (gold line) has risen markedly since the late 1990s. By 2010, the size of that gap — 8.5 percent of GDP — accounted for most deficit spending (red line) — 10.6 percent of GDP. And that is but a hint of things to come. The internet abounds with graphs and tables that depict future federal spending and revenues under various assumptions. They all point to the same conclusion: Spending “commitments” must be cut — and cut drastically — in order to avoid (a) economically disabling tax increases and (b) a day of reckoning in credit markets.

The online offerings include these from the Congressional Budget Office (CBO): “Impact of the President’s Proposals on the Budget Outlook” (blog summary), and “Long Term Analysis of a Budget Proposal by Chairman Ryan” (blog summary). The CBO analyses are somewhat dense and must be read in juxtaposition. They are neatly conjoined by the Committee for a Responsible Federal Budget’s “Analyzing the President’s New Budget Framework.” Here is an informative graphic from that analysis:

Debt projections under various fiscal reform plans

Obama’s “framework,” as the report emphasizes, is short on details. It is obviously a slap-dash response to Paul Ryan’s detailed plan (labelled “House Republicans” in the graphic), which is a serious proposal for long-term deficit reduction. To understand the bankruptcy of Obama’s actual budget and current law, which are about the same, one must look beyond 2021.

Drawing on CBO’s work, Cato Institute’s Michael Tanner take the long view in “Bankrupt: Entitlements and the Federal Budget.” Tanner leads off with this:

The U.S. government is about to exceed its statutory debt limit of $14.3 trillion. But that actually underestimates the size of the fiscal time bomb that this country is facing. If one considers the unfunded liabilities of programs such as Medicare and Social Security, the true national debt could run as high as $119.5 trillion.

Moreover, to focus solely on debt is to treat a symptom rather than the underlying disease. We face a debt crisis not because taxes are too low but because government is too big. If there is no change to current policies, by 2050 federal government spending will exceed 42 percent of GDP. Adding in state and local spending, government at all levels will consume nearly 60 percent of everything produced in this country. Whether financed through debt or taxes, government that large would be a crushing burden to our economy and our liberties. (p. 1)

Government spending now consumes almost 40 percent of everything produced in this country. Imagine the lives of your children and their children if and when government spending consumes almost 60 percent of everything produced in this country. But wait — it can get worse. Here, Tanner projects federal spending under current law, through 2080:

Long-term spending projections (Tanner)

Add State and local spending and, by 2080, you have an economy whose entire output is claimed by government entities. Some of that output would be directed to individuals for their sustenance, of course. But the form of that sustenance — along with everything else — would be dictated and allocated by politicians and bureaucrats. They — and their favored intellectuals, artists, and athletes — would live reasonably well (though not nearly as well as they could in a free-market system), while the proles would lead lives of hard work, hard drink, and hard deaths. It would be the USSR all over again. And, as with the USSR, the misdirection of economic activity by politicians and bureaucrats would ensure economic stagnation.

It may not come to that, if there are enough voters who understand the consequences of unbridled government spending, and who put liberty and true prosperity above the illusory promises of security offered by the big-government crowd. But as time goes by and more voters become accustomed to handouts, they will become “European” in their embrace of the welfare state. Slippery slopes and death-spirals lead to the same slough of despond (second definition).

That said, is there a way to have “our” cake and eat it, too? Can the U.S. government raise enough money through borrowing or taxation to fend off the day of reckoning and attain the left’s dream of attaining “Europeanism”?


In fact, financial markets may help to reign in government spending by sending signals that cannot be ignored — if the U.S. government borrows money from willing lenders instead of just printing it. (Economist Karl Smith explains why printing money — deliberate inflation — is an unlikely course of action. He refers to “structured default,” which is explained here.) As government spending rises, and as voters and politicians (in the main) reject significant tax increases, government debt will rise to unprecedented heights. Here, from The Heritage Foundation’s 2011 Budget Chart Book, is a retrospective and prospective look at the size of the federal government’s debt in relation to GDP:

National debt set to skyrocket

Financial markets will reject U.S. government debt — or charge a lot for carrying it — long before it reaches the levels shown above. The events of year ago, when Greece’s financial bind came to a head, gave a hint of the likely reaction of markets to continued fiscal profligacy. Then, earlier this month, there was a sharp, brief stock-market sell off in response to an announcement by Standard & Poor’s about U.S. government debt (“‘AAA/A-1+’ Rating On United States of America Affirmed; Outlook Revised To Negative“):

  • We have affirmed our ‘AAA/A-1+’ sovereign credit ratings on the United States of America.
  • The economy of the U.S. is flexible and highly diversified, the country’s effective monetary policies have supported output growth while containing inflationary pressures, and a consistent global preference for the U.S. dollar over all other currencies gives the country unique external liquidity.
  • Because the U.S. has, relative to its ‘AAA’ peers, what we consider to be very large budget deficits and rising government indebtedness and the path to addressing these is not clear to us, we have revised our outlook on the long-term rating to negative from stable.
  • We believe there is a material risk that U.S. policymakers might not reach an agreement on how to address medium- and long-term budgetary challenges by 2013; if an agreement is not reached and meaningful implementation is not begun by then, this would in our view render the U.S. fiscal profile meaningfully weaker than that of peer ‘AAA’ sovereigns.

If there is no serious effort to control the growth of the U.S. government’s debt by scaling back “entitlements,” two things will happen: Interest rates will rise, thus compounding the problem, and lenders will back away. Megan McArdle outlines a plausible scenario:

Right now, when Treasury goes to sell new bonds, it enters a fairly robust market, with not just the Fed but a bunch of fairly price-inelastic Asian central banks who are willing to take on our bonds at whatever the market offers. If China exits the market, we will either need to borrow less, or attract new lenders by offering higher interest rates. Even a noticeable decrease in volume would force us to pay more for our deficits….

… A lot of people tend to assume that there will be warning signs telling us that we need to get our fiscal house in order: China will slow down its bond purchases, interest rates will gradually rise. But in fact, the lesson of fiscal crises is that the “warning signs” we’re watching for often are the crisis. Unless interest rates increase (or debt buying decrease–which is really the same thing) in a very gradual, orderly fashion, then by the time your interest rates rise, it is already too late to do anything easy; your debt service burden forces you into dramatic fiscal measures, or default.

According to economist Carmen Reinhart, who has made an intensive study of crises, there’s no reason to expect the change to be orderly and gradual. She says the lesson of history is pretty unequivocal: interest rates are not a good predictor of who is about to tip into a crisis. People are willing to lend at decent rates, until suddenly they’re barely willing to lend at all.

When you look at how much of our debt comes due by the end of 2012, it’s easy to see how fast higher interest rates could turn into a real problem for us. To be sure, we’re no Japan–but that’s not necessarily a happy thought, because Japan finances something like 95% of its debt from its pool of thrifty (and nationalistic) savers. Their stock of lenders probably isn’t going anywhere. Ours might.

Lawrence Kotlikoff agrees:

…CBO’s baseline budget updates suggest the date for reaching what Carmen Reinhart, Kenneth Rogoff and other prominent economists believe is a critical insolvency threshold — a 90 percent ratio of federal debt held by the public to gross domestic product — has moved four years closer, in just nine months!…

And if foreigners balk at buying U.S. debt, why would Americans fill the breach? Is there a patriotic duty to finance socialism?

In summary, it seems unlikely that the U.S. can erect a full-blown welfare state on the backs of lenders. Can it be done on backs of taxpayers?


The short answer to the preceding question is “no.” In evidence, I return to Michael Tanner’s “Bankrupt: Entitlements and the Federal Budget“:

Many observers suggest that we can simply tax the rich. For example, the Center for American Progress has recommended, among other things, imposing a 5–7 percent surtax on households with incomes above $500,000 per year, eliminating the cap on Social Security payroll taxes, increasing the estate tax, and raising the top marginal tax rate on capital gains and dividends.60 That would potentially raise the total marginal tax burden on some people to well above 50 percent.

Setting aside the simple immorality of government taking such an enormous portion of anyone’s income, there are many reasons to be skeptical of such an approach, starting with the fact that it may not actually generate any additional revenue….

…[I]ncentives matter. At some point taxes become high enough to discourage economic activity and therefore produce less revenue than would be predicted under a more static analysis….

But even if one assumes that taxes can be raised without having any impact on economic growth, taxing the rich still wouldn’t get us out of our budget hole—because the hole is quite simply bigger than the amount of revenue we could raise from taxing the rich even if there were no disincentives. To put it in admittedly oversimplified perspective: our current obligations, including both implicit and explicit debt, total more than 900 percent of GDP. The combined wealth of everyone in the United States who earns at least $1 million per year equals roughly 100 percent of GDP…. Therefore, you could confiscate the entire wealth of every millionaire in the United States and still barely make a dent in the amount we will owe.

Clearly, therefore, any tax increases would have to extend well beyond “the rich.” In fact, the Congressional Budget Office said in 2008 that in order to pay for all currently scheduled federal spending both the corporate tax rate and top income tax rate would have to be raised from their current 35 percent to 88 percent, the current 25 percent tax rate for middle-income workers to 63 percent, and the 10 percent tax bracket for low-income workers to 25 percent. It is likely, given increased spending since then, that the required tax levels would be even higher today.

Regardless of how one feels about taxing the rich, taxes at those levels would be devastating to future economic growth.

Harvard economist Martin Feldstein points out that the actual loss from tax increases to the private sector is a combination of the confiscated revenue as well as a hidden cost of the actual increase, known as deadweight loss. This hidden cost can be very expensive. Feldstein calculates that “the total cost per incremental dollar of government spending, including the revenue and the deadweight loss, is . . . a very high $2.65. Equivalently, it implies that the marginal excess burden per dollar of revenue is $1.65.” This means that for every 1 percent of GDP needed to be raised in revenue, the equivalent of 2.65 percent of GDP needs to be extracted from the private sector first.

Clearly, tax increases required to finance an increase in spending of more than 40 percent of GDP would place an impossible burden on the private economy. (pp. 13-4, source notation omitted)

One more thing (from Table 1 of the Tax Foundation’s “Fiscal Facts“): For 2008, federal income tax returns with adjusted gross incomes in the top 1 percent accounted for 38 percent of income taxes; the top 5 percent, 59 percent; the top 10 percent, 70 percent; the top 25 percent, 86 percent; and the top 50 percent, 97 percent. Not only that, but the top 10 percent of American taxpayers is taxed more heavily than the top 10 percent in other developed countries, including those “advanced” European countries that American leftists would like to emulate. (See “No Country Leans on Upper-Income Households as Much as U.S.” at the Tax Foundation’s Tax Policy Blog.) And the left has the gall to claim that America’s “rich” aren’t paying enough taxes!


It will not do simply to put an end to the U.S. government’s spending spree; too many State and local governments stand ready to fill the void, and they will do so by raising taxes where they can. As a result, some jurisdictions will fall into California- and Michigan-like death-spirals while jobs and growth migrate to other jurisdictions. Contemporary mercantilists to the contrary, the “winners” are “losers,” too. Even if Congress resists the urge to give aid and comfort to profligate States and municipalities at the expense of the taxpayers of fiscally prudent jurisdictions, the high taxes and anti-business regimes of California- and Michigan-like jurisdictions impose deadweight losses on the whole economy. If you believe otherwise, you believe in the broken-window fallacy, wherein an economically destructive force (natural or governmental) is credited with creating jobs and wealth because it leads to the visible expenditure of effort and resources.

So, the resistance to economically destructive policies cannot end with efforts to reverse the policies of the federal government. But given the vast destructiveness of those policies — “entitlements” in particular — the resistance must begin there. Every conservative and libertarian voice in the land must be raised in reasoned opposition to the perpetuation of the unsustainable “promises” currently embedded in Social Security, Medicare, and Medicaid — and their expansion through Obamacare. To those voices must be added the voices of “moderates” and “liberals” who see through the proclaimed good intentions of “entitlements” to the economic and libertarian disaster that looms if those “entitlements” are not pared down to their original purpose: providing a safety net for the truly needy.

The alternative to successful resistance is stark: more borrowing, higher interest payments, unsustainable debt, higher taxes, and economic stagnation (at best).

Fooled by Non-Randomness

Nassim Nicholas Taleb, in his best-selling Fooled by Randomness, charges human beings with the commission of many perceptual and logical errors. One reviewer captures the point of the book, which is to

explore luck “disguised and perceived as non-luck (that is, skills).” So many of the successful among us, he argues, are successful due to luck rather than reason. This is true in areas beyond business (e.g. Science, Politics), though it is more obvious in business.

Our inability to recognize the randomness and luck that had to do with making successful people successful is a direct result of our search for pattern. Taleb points to the importance of symbolism in our lives as an example of our unwillingness to accept randomness. We cling to biographies of great people in order to learn how to achieve greatness, and we relentlessly interpret the past in hopes of shaping our future.

Only recently has science produced probability theory, which helps embrace randomness. Though the use of probability theory in practice is almost nonexistent.

Taleb says the confusion between luck and skill is our inability to think critically. We enjoy presenting conjectures as truth and are not equipped to handle probabilities, so we attribute our success to skill rather than luck.

Taleb writes in a style found all too often on best-seller lists: pseudo-academic theorizing “supported” by selective (often anecdotal) evidence. I sometimes enjoy such writing, but only for its entertainment value. Fooled by Randomness leaves me unfooled, for several reasons.


The first reason that I am unfooled by Fooled… might be called a meta-reason. Standing back from the book, I am able to perceive its essential defect: According to Taleb, human affairs — especially economic affairs, and particularly the operations of financial markets — are dominated by randomness. But if that is so, only a delusional person can truly claim to understand the conduct of human affairs. Taleb claims to understand the conduct of human affairs. Taleb is therefore either delusional or omniscient.

Given Taleb’s humanity, it is more likely that he is delusional — or simply fooled, but not by randomness. He is fooled because he proceeds from the assumption of randomness instead of exploring the ways and means by which humans are actually capable of shaping events. Taleb gives no more than scant attention to those traits which, in combination, set humans apart from other animals: self-awareness, empathy, forward thinking, imagination, abstraction, intentionality, adaptability, complex communication skills, and sheer brain power. Given those traits (in combination) the world of human affairs cannot be random. Yes, human plans can fail of realization for many reasons, including those attributable to human flaws (conflict, imperfect knowledge, the triumph of hope over experience, etc.). But the failure of human plans is due to those flaws — not to the randomness of human behavior.

What Taleb sees as randomness is something else entirely. The trajectory of human affairs often is unpredictable, but it is not random. For it is possible to find patterns in the conduct of human affairs, as Taleb admits (implicitly) when he discusses such phenomena as survivorship bias, skewness, anchoring, and regression to the mean.


What Is It?

Taleb, having bloviated for dozens of pages about the failure of humans to recognize randomness, finally gets around to (sort of) defining randomness on pages 168 and 169 (of the 2005 paperback edition):

…Professor Karl Pearson … devised the first test of nonrandomness (it was in reality a test of deviation from normality, which for all intents and purposes, was the same thing). He examined millions of runs of [a roulette wheel] during the month of July 1902. He discovered that, with high degree of statistical significance … the runs were not purely random…. Philosophers of statistics call this the reference case problem to explain that there is no true attainable randomness in practice, only in theory….

…Even the fathers of statistical science forgot that a random series of runs need not exhibit a pattern to look random…. A single random run is bound to exhibit some pattern — if one looks hard enough…. [R]eal randomness does not look random.

The quoted passage illustrates nicely the superficiality of Fooled by Randomness, and (I must assume) the muddledness of Taleb’s thinking:

  • He accepts a definition of randomness which describes the observation of outcomes of mechanical processes (e.g., the turning of a roulette wheel, the throwing of dice) that are designed to yield random outcomes. That is, randomness of the kind cited by Taleb is in fact the result of human intentions.
  • If “there is no true attainable randomness,” why has Taleb written a 200-plus page book about randomness?
  • What can he mean when he says “a random series of runs need not exhibit a pattern to look random”? The only sensible interpretation of that bit of nonsense would be this: It is possible for a random series of runs to contain what looks like a pattern. But remember that the random series of runs to which Taleb refers is random only because humans intended its randomness.
  • It is true enough that “A single random run is bound to exhibit some pattern — if one looks hard enough.” Sure it will. But it remains a single random run of a process that is intended to produce randomness, which is utterly unlike such events as transactions in financial markets.

One of the “fathers of statistical science” mentioned by Taleb (deep in the book’s appendix) is Richard von Mises, who in Probability Statistics and Truth defines randomness as follows:

First, the relative frequencies of the attributes [e.g. heads and tails] must possess limiting values [i.e., converge on 0.5, in the case of coin tosses]. Second, these limiting values must remain the same in all partial sequences which may be selected from the original one in an arbitrary way. Of course, only such partial sequences can be taken into consideration as can be extended indefinitely, in the same way as the original sequence itself. Examples of this kind are, for instance, the partial sequences formed by all odd members of the original sequence, or by all members for which the place number in the sequence is the square of an integer, or a prime number, or a number selected according to some other rule, whatever it may be. (pp. 24-25 of the 1981 Dover edition, which is based on the author’s 1951 edition)

Gregory J. Chaitin, writing in Scientific American (“Randomness and Mathematical Proof,” vol. 232, no. 5 (May 1975), pp. 47-52), offers this:

We are now able to describe more precisely the differences between the[se] two series of digits … :


The first could be specified to a computer by a very simple algorithm, such as “Print 01 ten times.” If the series were extended according to the same rule, the algorithm would have to be only slightly larger; it might be made to read, for example, “Print 01 a million times.” The number of bits in such an algorithm is a small fraction of the number of bits in the series it specifies, and as the series grows larger the size of the program increases at a much slower rate.

For the second series of digits there is no corresponding shortcut. The most economical way to express the series is to write it out in full, and the shortest algorithm for introducing the series into a computer would be “Print 01101100110111100010.” If the series were much larger (but still apparently patternless), the algorithm would have to be expanded to the corresponding size. This “incompressibility” is a property of all random numbers; indeed, we can proceed directly to define randomness in terms of incompressibility: A series of numbers is random if the smallest algorithm capable of specifying it to a computer has about the same number of bits of information as the series itself [emphasis added].

This is another way of saying that if you toss a balanced coin 1,000 times the only way to describe the outcome of the tosses is to list the 1,000 outcomes of those tosses. But, again, the thing that is random is the outcome of a process designed for randomness.

Taking Mises and Chaitin’s definitions together, we can define random events as events which are repeatable, convergent on a limiting value, and truly patternless over a large number of repetitions. Evolving economic events (e.g., stock-market trades, economic growth) are not alike (in the way that dice are, for example), they do not converge on limiting values, and they are not patternless, as I will show.

In short, Taleb fails to demonstrate that human affairs in general or financial markets in particular exhibit randomness, properly understood.

Randomness and the Physical World

Nor are we trapped in a random universe. Returning to Mises, I quote from the final chapter of Probability, Statistics and Truth:

We can only sketch here the consequences of these new concepts [e.g., quantum mechanics and Heisenberg’s principle of uncertainty] for our general scientific outlook. First of all, we have no cause to doubt the usefulness of the deterministic theories in large domains of physics. These theories, built on a solid body of experience, lead to results that are well confirmed by observation. By allowing us to predict future physical events, these physical theories have fundamentally changed the conditions of human life. The main part of modern technology, using this word in its broadest sense, is still based on the predictions of classical mechanics and physics. (p. 217)

Even now, almost 60 years on, the field of nanotechnology is beginning to hardness quantum mechanical effects in the service of a long list of useful purposes.

The physical world, in other words, is not dominated by randomness, even though its underlying structures must be described probabilistically rather than deterministically.

Summation and Preview

A bit of unpredictability (or “luck”) here and there does not make for a random universe, random lives, or random markets. If a bit of unpredictability here and there dominated our actions, we wouldn’t be here to talk about randomness — and Taleb wouldn’t have been able to marshal his thoughts into a published, marketed, and well-sold book.

Human beings are not “designed” for randomness. Human endeavors can yield unpredictable results, but those results do not arise from random processes, they derive from skill or the lack therof, knowledge or the lack thereof (including the kinds of self-delusions about which Taleb writes), and conflicting objectives.

An Illustration from Life

To illustrate my position on randomness, I offer the following digression about the game of baseball.

At the professional level, the game’s poorest players seldom rise above the low minor leagues. But even those poorest players are paragons of excellence when compared with the vast majority of American males of about the same age. Did those poorest players get where they were because of luck? Perhaps some of them were in the right place at the right time, and so were signed to minor league contracts. But their luck runs out when they are called upon to perform in more than a few games. What about those players who weren’t in the right place at the right time, and so were overlooked in spite of skills that would have advanced them beyond the rookie leagues? I have no doubt that there have been many such players. But, in the main, professional baseball abounds with the lion’s share of skilled baseball players who are there because they intend to be there, and because baseball clubs intend for them to be there.

Now, most minor leaguers fail to advance to the major leagues, even for the proverbial “cup of coffee” (appearing in few games at the end of the major-league season, when teams are allowed to expand their rosters following the end of the minor-league season). Does “luck” prevent some minor leaguers from advancement to “the show” (the major leagues)? Of course. Does “luck” result in the advancement of some minor leaguers to “the show”? Of course. But “luck,” in this context, means injury, illness, a slump, a “hot” streak, and the other kinds of unpredictable events that ballplayers are subject to. Are the events random? Yes, in the sense that they are unpredictable, but I daresay that most baseball players do not succumb to bad luck or advance very for or for very long because of good luck. In fact, ballplayers who advance to the major leagues, and then stay there for more than a few seasons, do so because they possess (and apply) greater skill than their minor-league counterparts. And make no mistake, each player’s actions are so closely watched and so extensively quantified that it isn’t hard to tell when a player is ready to be replaced.

It is true that a player may experience “luck” for a while during a season, and sometimes for a whole season. But a player will not be consistently “lucky” for several seasons. The length of his career (barring illness, injury, or voluntary retirement), and his accomplishments during that career, will depend mainly on his inherent skills and his assiduousness in applying those skills.

No one believes that Ty Cobb, Babe Ruth, Ted Williams, Christy Matthewson, Warren Spahn, and the dozens of other baseball players who rank among the truly great were lucky. No one believes that the vast majority of the the tens of thousands of minor leaguers who never enjoyed more than the proverbial cup of coffee were unlucky. No one believes that the vast majority of the millions of American males who never made it to the minor leagues were unlucky. Most of them never sought a career in baseball; those who did simply lacked the requisite skills.

In baseball, as in life, “luck” is mainly an excuse and rarely an explanation. We prefer to apply “luck” to outcomes when we don’t like the true explanations for them. In the realm of economic activity and financial markets, one such explanation (to which I will come) is the exogenous imposition of governmental power.


They Cannot Be, Given Competition

Returning to Taleb’s main theme — the randomness of economic and financial events — I quote this key passage (my comments are in brackets and boldface):

…Most of [Bill] Gates'[s] rivals have an obsessive jealousy of his success. They are maddened by the fact that he managed to win so big while many of them are struggling to make their companies survive. [These are unsupported claims that I include only because they set the stage for what follows.]

Such ideas go against classical economic models, in which results either come from a precise reason (there is no account for uncertainty) or the good guy wins (the good guy is the one who is most skilled and has some technical superiority). [The “good guy” theory would come as a great surprise to “classical” economists, who quite well understood imperfect competition based on product differentiation and monopoly based on (among other things) early entry into a market.] Economists discovered path-dependent effects late in their game [There is no “late” in a “game” that had no distinct beginning and has no pre-ordained end.], then tried to publish wholesale on the topic that otherwise be bland and obvious. For instance, Brian Arthur, an economist concerned with nonlinearities at the Santa Fe Institute [What kinds of nonlinearities are found at the Santa Fe Institute?], wrote that chance events coupled with positive feedback other than technological superiority will determine economic superiority — not some abstrusely defined edge in a given area of expertise. [It would come as no surprise to economists — even “classical” ones — that many factors aside from technical superiority determine market outcomes.] While early economic models excluded randomness, Arthur explained how “unexpected orders, chance meetings with lawyers, managerial whims … would help determine which ones acheived early sales and, over time, which firms dominated.”

Regarding the final sentence of the quoted passage, I refer back to the example of baseball. A person or a firm may gain an opportunity to succeed because of the kinds of “luck” cited by Brian Arthur, but “good luck” cannot sustain an incompetent performer for very long.  And when “bad luck” happens to competent individuals and firms they are often (perhaps usually) able to overcome it.

While overplaying the role of luck in human affairs, Taleb underplays the role of competition when he denigrates “classical economic models,” in which competition plays a central role. “Luck” cannot forever outrun competition, unless the game is rigged by governmental intervention, namely, the writing of regulations that tend to favor certain competitors (usually market incumbents) over others (usually would-be entrants). The propensity to regulate at the behest of incumbents (who plead “public interest,” of course) is a proof of the power of competition to shape economic outcomes. It is loathed and feared, and yet it leads us in the direction to which classical economic theory points: greater output and lower prices.

Competition is what ensures that (for the most part) the best ballplayers advance to the major leagues. It’s what keeps “monopolists” like Microsoft hopping (unless they have a government-guaranteed monopoly), because even a monopolist (or oligopolist) can face competition, and eventually lose to it — witness the former “Big Three” auto makers, many formerly thriving chain stores (from Kresge’s to Montgomery Ward’s), and numerous other brand names of days gone by. If Microsoft survives and thrives, it will be because it actually offers consumers more value for their money, either in the way of products similar to those marketed by Microsoft or in entirely new products that supplant those offered by Microsoft.

Monopolists and oligopolists cannot survive without constant innovation and attention to their customers’ needs.Why? Because they must compete with the offerors of all the other goods and services upon which consumers might spend their money. There is nothing — not even water — which cannot be produced or delivered in competitive ways. (For more, see this.)

The names of the particular firms that survive the competitive struggle may be unpredictable, but what is predictable is the tendency of competitive forces toward economic efficiency. In other words, the specific outcomes of economic competition may be unpredictable (which is not a bad thing), but the general result — efficiency — is neither unpredictable nor a manifestation of randomness or “luck.”

Taleb, had he broached the subject of competition would (with his hero George Soros) denigrate it, on the ground that there is no such thing as perfect competition. But the failure of competitive forces to mimic the model of perfect competition does not negate the power of competition, as I have summarized it here. Indeed, the failure of competitive forces to mimic the model of perfect competition is not a failure, for perfect competition is unattainable in practice, and to hold it up as a measure of the effectiveness of market forces is to indulge in the Nirvana fallacy.

In any event, Taleb’s myopia with respect to competition is so complete that he fails to mention it, let alone address its beneficial effects (even when it is less than perfect). And yet Taleb dares to dismiss as a utopist Milton Friedman (p. 272) — the same Milton Friedman who was among the twentieth century’s foremost advocates of the benefits of competition.

Are Financial Markets Random?

Given what I have said thus far, I find it almost incredible that anyone believes in the randomness of financial markets. It is unclear where Taleb stands on the random-walk hypothesis, but it is clear that he believes financial markets to be driven by randomness. Yet, contradictorily, he seems to attack the efficient-markets hypothesis (see pp. 61-62), which is the foundation of the random-walk hypothesis.

What is the random-walk hypothesis? In brief, it is this: Financial markets are so efficient that they instantaneously reflect all information bearing on the prices of financial instruments that is then available to persons buying and selling those instruments. (The qualifier “then available to persons buying and selling those instruments” leaves the door open for [a] insider trading and [b] arbitrage, due to imperfect knowledge on the part of some buyers and/or sellers.) Because information can change rapidly and in unpredictable ways, the prices of financial instruments move randomly. But the random movement is of a very special kind:

If a stock goes up one day, no stock market participant can accurately predict that it will rise again the next. Just as a basketball player with the “hot hand” can miss the next shot, the stock that seems to be on the rise can fall at any time, making it completely random.

And, therefore, changes in stock prices cannot be predicted.

Note, however, the focus on changes. It is that focus which creates the illusion of randomness and unpredictability. It is like hoping to understand the movements of the planets around the sun by looking at the random movements of a particle in a cloud chamber.

When we step back from day-to-day price changes, we are able to see the underlying reality: prices (instead of changes) and price trends (which are the opposite of randomness). This (correct) perspective enables us to see that stock prices (on the whole) are not random, and to identify the factors that influence the broad movements of the stock market.
For one thing, if you look at stock prices correctly, you can see that they vary cyclically. Here is a telling graphic (from “Efficient-market hypothesis” at Wikipedia):

Returns on stocks vs. PE ratioPrice-Earnings ratios as a predictor of twenty-year returns based upon the plot by Robert Shiller (Figure 10.1,[18] source). The horizontal axis shows the real price-earnings ratio of the S&P Composite Stock Price Index as computed in Irrational Exuberance (inflation adjusted price divided by the prior ten-year mean of inflation-adjusted earnings). The vertical axis shows the geometric average real annual return on investing in the S&P Composite Stock Price Index, reinvesting dividends, and selling twenty years later. Data from different twenty-year periods is color-coded as shown in the key. See also ten-year returns. Shiller states that this plot “confirms that long-term investors—investors who commit their money to an investment for ten full years—did do well when prices were low relative to earnings at the beginning of the ten years. Long-term investors would be well advised, individually, to lower their exposure to the stock market when it is high, as it has been recently, and get into the market when it is low.”[18] This correlation between price to earnings ratios and long-term returns is not explained by the efficient-market hypothesis.

Why should stock prices tend to vary cyclically? Because stock prices generally are driven by economic growth (i.e., changes in GDP), and economic growth is strongly cyclical. (See this post.)

More fundamentally, the economic outcomes reflected in stock prices aren’t random, for they depend mainly on intentional behavior along well-rehearsed lines (i.e., the production and consumption of goods and services in ways that evolve over time). Variations in economic behavior, even when they are unpredictable, have explanations; for example:

  • Innovation and capital investment spur the growth of economic output.
  • Natural disasters slow the growth of economic output (at least temporarily) because they absorb resources that could have gone to investment  (as well as consumption).
  • Governmental interventions (taxation and regulation), if not reversed, dampen growth permanently.

There is nothing in those three statements that hasn’t been understood since the days of Adam Smith. Regarding the third statement, the general slowing of America’s economic growth since the advent of the Progressive Era around 1900 is certainly not due to randomness, it is due to the ever-increasing burden of taxation and regulation imposed on the economy — an entirely predictable result, and certainly not a random one.

In fact, the long-term trend of the stock market (as measured by the S&P 500) is strongly correlated with GDP. And broad swings around that trend can be traced to governmental intervention in the economy. The following graph shows how the S&P 500, reconstructed to 1870, parallel constant-dollar GDP:

The next graph shows the relationship more clearly.

090711_Real S&P 500 vs Real GDP

090711_Real S&P 500 vs Real GDP_2

The wild swings around the trend line began in the uncertain aftermath of World War I, which saw the imposition of production and price controls. The swings continued with the onset of the Great Depression (which can be traced to governmental action), the advent of the anti-business New Deal, and the imposition of production and price controls on a grand scale during World War II. The next downswing was occasioned by the culmination the Great Society, the “oil shocks” of the early 1970s, and the raging inflation that was touched off by — you guessed it — government policy. The latest downswing is owed mainly to the financial crisis born of yet more government policy: loose money and easy loans to low-income borrowers.

And so it goes, wildly but predictably enough if you have the faintest sense of history. The moral of the story: Keep your eye on government and a hand on your wallet.


There is randomness in economic affairs, but they are not dominated by randomness. They are dominated by intentions, including especially the intentions of the politicians and bureaucrats who run governments. Yet, Taleb has no space in his book for the influence of their deeds economic activity and financial markets.

Taleb is right to disparage those traders (professional and amateur) who are lucky enough to catch upswings, but are unprepared for downswings. And he is right to scoff at their readiness to believe that the current upswing (uniquely) will not be followed by a downswing (“this time it’s different”).

But Taleb is wrong to suggest that traders are fooled by randomness. They are fooled to some extent by false hope, but more profoundly by their inablity to perceive the economic damage wrought by government. They are not alone of course; most of the rest of humanity shares their perceptual failings.

Taleb, in that respect, is only somewhat different than most of the rest of humanity. He is not fooled by false hope, but he is fooled by non-randomness — the non-randomness of government’s decisive influence on economic activity and financial markets. In overlooking that influence he overlooks the single most powerful explanation for the behavior of markets in the past 90 years.