These experts, armed with the most sophisticated methods available, gave the journalists what they needed. In turn the journalists—armed with what they uncritically accepted as good information—returned with coffee to their keyboards and reported.

Witness:

Mark Zandi, chief economist at Moody’s Analytics, is frequently the go-to guy for both parties when it comes to analysis of various jobs proposals. So, what did he think of President Obama’s speech last night? Here’s the report: “The plan would add 2 percentage points to GDP growth next year, add 1.9 million jobs, and cut the unemployment rate by a percentage point.” [Brad Plummer, “Ezra Klein’s Wonkblog,” Washington Post, September 9.]

And who are the willing consumers of this information? People looking for reasons to be hopeful. People looking for certainty. Who can blame them? Times are tough.

But this sort of reporting is just scientism on display. I’m not alone in thinking this. Economist Russ Roberts, reacting to similar reporting in the Financial Times, wrote at Cafe Hayek (September 13): “Really? That’s what they found? [The journalist] treats it like a discovery of fact. As in ‘[Alan] Blinder and Zandi weren’t sure of the distance between the earth and the sun but when they measured it, they found it was about 93,000,000 miles.’”

Roberts knows economists aren’t capable of auguring such things. Because when it comes to national-level prediction and forecast, economics has all the reliability of a Farmer’s Almanac. And that’s being charitable.

Certainty for Sale

Here’s the problem: People like Mark Zandi belong to a great power nexus that relies on scientism for its very existence. To repeat: People crave certainty. Politicians crave power. So the latter have to provide the former with at least the illusion of certainty to stay in office. But they can’t do it alone.

Economists—especially those who tend to get tapped by the media or by Washington elites—are the ones willing to strut around on the national stage showing their predictive plumage. Journalists, no experts themselves, report what they’re told. (And few try to spot the turkey behind all that peacocking.)

But as readers of this publication know, a nexus of politicians, economists, journalists, special interests, and a desperate lay public can hardly be virtuous. This industry enables peddlers of scientism to hock their wares in a world full of uncertainty. Indeed, a pseudo-certainty creates the circumstances under which great wishes can father great lies.

F. A. Hayek warned us about this, of course, when he said, “It seems to me that this failure of the economists to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences—an attempt which in our field may lead to outright error. It is an approach which has come to be described as the “scientistic” attitude. . . .”

Since Hayek, a growing movement of great minds, across disciplines, warns us to clip our wax wings.

Chaos Rules

In 1961 Edward Lorenz discovered the “butterfly effect.” Ironically, when he figured out that tiny changes in initial conditions could mean seismic shifts in the rest of a system, he was studying weather and climate. I won’t discuss the irony here. Suffice it to say Lorenz is the one who taught us that complex systems—whether the climate, an ecosystem, or an economy—can also be chaotic systems. “I realized,” said Lorenz of his then-obscure finding, “that any physical system that behaved nonperiodically would be unpredictable.”

Although “chaotic” eludes strict definition, the term usually refers to a system that is sensitive to changes in initial conditions, shows order without regularity, and is immune to prediction and forecast.

In his still-vibrant Chaos (1989), James Gleick tells Lorenz’s story—including the latter’s discoveries and the implications of chaos. “Forecasts of economic growth or unemployment were put forward with an implied precision of two or three decimal places,” writes Gleick. “Governments and financial institutions paid for such predictions and acted on them, perhaps out of necessity or for want of anything better. . . . But few realized how fragile was the very process of modeling flows on computers, even when the data [were] recognizably trustworthy and the laws were purely physical, as in weather forecasting.”

Little has changed.

Aggregates, Agents, and Ants

I think the failure of macroeconomics can be boiled down to this: Macroeconomics deals primarily with aggregates, or macro-level trends. But to be truly accurate the macro level would have to be explained in terms of the micro—that is, individual agent behavior. Micro behaviors give rise to macro trends. Another way of putting this is that macro trends are dependent on micro behaviors. The trouble is, individual agents interact with—and react to—one another in diverse, complicated ways.

Similarly, it’s impossible to predict exactly what an ant colony will do when confronted with two picnics at equal distances from the colony. In that famous experiment we might be able to predict a single ant’s behavior if we have lots of local information about its pheromone secretion algorithms and such. But relative to each food source it would be impossible to predict the behavior of the colony as a whole. Such is life at the edge of chaos.

A Blind Spot

Now of course we have processors that can crunch tons of data. We have a new breed of mathematical wizards in the tradition of Paul Samuelson who can write whole tracts with as many equations as words. And we have whole new constituencies of politicians, pundits, and people ready to believe. So are we finally living in a time when macroeconomics can tell us what we need to know about unemployment in a year—as Newtonian mechanics tells us when Halley’s Comet will arrive?

Alas no, says mathematician William Byers. In his excellent The Blind Spot, Byers makes an audacious argument for humility in the sciences—both hard and human: “Human beings have a basic need for certainty. Yet since things are ultimately uncertain, we satisfy this need by creating artificial islands of certainty. We create models of reality and then insist that the models are reality. It is not that science, mathematics, and statistics do not provide useful information about the real world. The problem lies in making excessive claims for the validity of these methods and models and believing them to be absolutely certain.”

Interestingly, Byers also picks up on the idea of selling certainty. Whether he’s talking about the complicated financial instruments that obscured the problems leading to the financial meltdown, or the schematics for all the Keynesian fixes that followed, models are the conduits of pseudo-certainty. “The more complex the package and the more arcane the mathematics, the better,” says Byers. “What was being sold was the faith that the complex, human, world of economics and finance could be made over in the image of science, could be made objective and predictable.”

Byers goes on to explain that there is a kind of quantification bias at work. That is, if you can describe things in mathematics, you are in some sense speaking the language of nature. But limning the world in numbers has its limits—especially since so many of the important aspects of science are subjective. And so many aspects of nature are, well, uncertain. Numbers, argues Byers, are our attempt to create the illusion of objectivity—where objectivity is thought to be the very stuff of certainty. But “science does great damage when it turns into ideology, when it begins to worship certainty.”

The (Other) Freeman

Eminent physicist Freeman Dyson is no libertarian. But his call for humility in science (“Heretical Thoughts about Science and Society,”) extends to economics, too:

The politicians and the public expect science to provide answers to the problems. Scientific experts are paid and encouraged to provide answers. The public does not have much use for a scientist who says, “Sorry, but we don’t know.” The public prefers to listen to scientists who give confident answers to questions and make confident predictions of what will happen as a result of human activities. So it happens that the experts who talk publicly about politically contentious questions tend to speak more clearly than they think. They make confident predictions about the future, and end up believing their own predictions. Their predictions become dogmas which they do not question. The public is led to believe that the fashionable scientific dogmas are true, and it may sometimes happen that they are wrong. That is why heretics who question the dogmas are needed.

So if Dyson is right about the need for heretics, are those skeptical of macroeconomics heretics or “market fundamentalists”?

People who understand markets know they can’t do everything under the sun. Yes, markets can and do work wonders. But most truly liberal thinkers start with a particular kind of skepticism:

• Knowledge is dispersed, not centralized. Planning or tweaking by central authorities is a fool’s errand and results in perverse effects. (Skepticism of grand designs.)
• Centralized power tends to corrupt people. Coalitions of interests, bureaucrats, and moralists form to transfer resources from the masses or from competitors to the pockets of coalition members. (Skepticism of power wielded for the “public good.”)
• Value is not objective but rather subjective. This not only makes market exchanges possible, but makes it difficult for any central authority to claim it is operating in the name of a universal good. (Skepticism of claims to objective value. [See my “The Relentless Subjectivity of Value.”])

I could go on. Suffice it to say that to be a classical liberal is to be a heretic. And for heretics skepticism is a prime virtue. Yes, we tend to admire the market process. But unlike those who prostrate themselves before the golden calf of Aggregate Demand or Government as God, we are skeptics first and foremost.

Soothsayers and Charlatans

When it comes to heresy in economics Arnold Kling comes to mind. Writing in The American, he says: “I think that if the press were aware of the intellectual history and lack of scientific standing of the models, it would cease rounding up these usual suspects. Macroeconometrics stands discredited among mainstream academic economists. Applying macroeconometric models to questions of fiscal policy is the equivalent of using pre-Copernican astronomy to launch a satellite or using bleeding to treat an infection.”

Kling says economists should be more honest about their limitations. He thinks the Congressional Budget Office, with all its scoring, can do little to predict the effects of various policy scenarios, such as taxing and spending: “The CBO adds value to policymakers by ‘scoring’ the impact of policies on the budget. However, the ‘scoring’ of policies in terms of GDP growth or jobs saved is of no value. The CBO should simply refuse to do it, and the consulting firms that purport to provide such estimates should be regarded as the charlatans they are.”

An Uncertain Constituency

Though the methods used by these macroeconomists are no more reliable than “soothsaying or entrail-reading,” they belong to that great nexus of power, which creates incentives for folks to “step right up” for more of the same elixir.

Sadly there is no competing power nexus. And yet people are growing increasingly suspicious of these nostra. Just as Americans have grown weary of intervention in foreign affairs, they’re growing weary of intervention in the economy, too. Call it what you like—stimulus bills, jobs plans, back-to-work schemes, or whatever—fiscal interventionism is not producing the desired effect. And people are getting wise to it. In the old days they ran the charlatans out of town.

More than a year after the original “stimulus,” not only are economists nowhere near consensus about its effects but few if any of the models used to justify it have turned out to be right. Obamanomic adviser Christina Romer, for example, has come under heavy criticism because her team’s plan has performed abysmally. The model behind the plan predicted unemployment would peak at 8.3 percent. It exceeded 10 percent before dropping back slightly. In defending her plan she appealed to counterfactuals—that is, how bad things could have been without it. That her team failed to reach its rosy targets, she says, “prevents people from focusing on the positive impact.” But did Romer ever consider the possibility that her model was just wrong?

When it comes to prediction and explanation, macroeconomic models are often just as bad after the fact as before it. There are just as many debates raging about the effects of the “stimulus” as explanations of the crisis used to justify it. Consensus consistently eludes us. Almost all the arguments presuppose models. There are Keynesian models, “new” Keynesian models, and unbranded models proffered by leading economic lights like Harvard’s Robert Barro. Comparative analyses of these positions offer little except further evidence that, as Stanford’s John Taylor writes, “[T]here is no consensus.”

But why? These people aren’t stupid. I’d like to suggest in nontechnical terms why the problem might be with the models themselves.

“Mainstream macroeconomics is ‘hydraulic,’” writes recovering macroeconomist Arnold Kling at EconLog. “There is something called ‘aggregate demand’ which you adjust by pumping in fiscal and monetary expansion. I wish to reject this whole concept of macroeconomics.” I think he’s right. In fact, as I’ve argued in these pages before, economies are not pumps to be primed, but economic ecosystems. Economists are thus notoriously bad at predicting, much less planning, economies. That’s why next-generation economics must focus on the fundamentals—namely, the rules that give rise to successful entrepreneurship and sustainable growth. Not aggregates. Not models. Rules.

“Institutions form the incentive structure of a society and the political and economic institutions, in consequence, are the underlying determinant of economic performance,” said Douglass North in his Nobel Prize lecture. And he’s not alone in the wilderness. James Buchanan, another Nobel Prize winner, says economists are simply asking the wrong questions:

How do markets work? Standing alone, this is an inappropriate and unanswerable question. It must be replaced by the question: How do markets work under this or that set of constitutional and institutional constraints? Economists’ scientific expertise can be brought to bear on the predicted effects of alternative sets of constraints. The relevant question is not how this or that outcome may be put in place through possible collective or political action. The question becomes instead, how can this or that set of constraints be predicted to operate so as to allow the generation of an order that meets certain criteria of desirability? The difference between the two methodological stances may appear minor, but much ill-advised effort might be avoided if economists would recognize the limits of their own discipline. [“Economists Have No Clothes.”]

Buchanan not only laments the poor framing of economic questions, but also says that even those attempting postmortems of the 2008-09 financial crisis have been “embarrassed by their inability to offer ‘scientific’ explanations.” Those who’ve dared to come forward have offered little more than warmed-over Keynesian nostrums. Just think of folks like Romer, Paul Krugman, and Joseph Stiglitz—all of whom have recommended various versions of doubling down on the failed policy. At the end of their yellow-brick road? A curtain, behind which lies a model, behind which lies an agenda.

So what do all these macroeconomic models have in common?

• They’re rendered either in impenetrable math or with sophisticated computers, requiring a lot of popular (and political) faith.
• Politicians and policy wizards hide behind this impenetrability, both to evade public scrutiny and to secure their status as elites.
• Models vaguely resemble the real-world phenomena they’re meant to explain but often fail to track with reality when the evidence comes in.
• They’re meant to model complex systems, but such systems resist modeling. Complexity makes things inherently hard to predict and forecast.
• They’re used by people who fancy themselves planners—not just predictors or describers—of complex phenomena.

None of this is to argue we should do away with measurement. Temperature, blood pressure, and other indicators are all useful data for telling whether you’re healthy. But using proxy measures to determine an economy’s health is a far cry from using models to reduce dynamic systems to steady-state snapshots.

What does this mean for economics as a discipline? I think it’s time we admit many economists are just soothsayers. They keep their jobs for a host of reasons that have less to do with accuracy and more to do with politics and obscurantism. Indeed, where do you find them but in bureaucracies—those great shelters from reality’s storms? Governments and universities are places where big brains go to be grand and weave speculative webs for the benefit of the few.

And yet “ideas have consequences.” Bureaucracies are power centers. So we have a big job ahead of us. We’ve got to do a seemingly contradictory thing and make the very idea of complex systems simple. How best to say it? Economists aren’t oracles? Soothsaying is not science? Ecosystems can’t be designed?

“The very term ‘model’ is a pretentious borrowing of the architect’s or engineer’s replica, down-to-scale of something physical,” says Barron’s economics editor, Gene Epstein. “These are not models at all, but just equations that link various numbers, maybe occasionally shedding light, but often not.”

Take this as a throwing down of the gauntlet. Macroeconomic wizards owe us more than the circular justifications for cushy jobs.

Likewise, we have to explain that a scientist’s model, while useful in limited circumstances, is little better than a crystal ball for predicting big phenomena like markets and climate. It is an offshoot of what F. A. Hayek called the “pretence of knowledge.” In other words, modeling is a form of scientism, which is “decidedly unscientific in the true sense of the word, since it involves a mechanical and uncritical application of habits of thought to fields different from those in which they have been formed.”   A model is thus a cognitive shortcut for both the wonk and the journalist, the latter of whom wants to peg his story to something authoritative the wonk has to provide. At the receiving end of this wonk-writer alliance are the rest of us—with little besides common sense as a shield. And I don’t mean this as populism. It is rather a defense against scientism launched from the turf of Austrian economics.

Complex phenomena can be counterintuitive. Sometimes they require scrutiny by experts to make sense of them. Notwithstanding their expertise, experts are just as often wrong as right. Can we base policy decisions on what amounts to coin flips? Models are a means of making the most fragile of hypotheses seem strong and substantive. But the only thing we can really predict is that they’ll eventually shatter.

But how can desperately poor people afford it? How can the education market work in countries rife with corruption and institutional barriers to innovation? Why haven’t we heard about this phenomenon before? And if private education can rapidly spread in the developing world, couldn’t it also in the rich West?

In The Beautiful Tree, James Tooley answers those questions. He offers readers a firsthand account of schools all over the developing world. The book isn’t just academic research; it is also a kind of travelogue. We meet the real teachers, students, and parents who constitute the delicate educational ecosystems under constant threat from bureaucrats, do-gooders, and naysayers. Tooley, a former university professor who now works full-time to help start free-market schools, tells their stories as if at our side, coloring straightforward prose with rich stories and quotations from people he has met.

In the end he arrives at what many may think is a highly counterintuitive conclusion: “Private schools for the poor are burgeoning across the developing world. In many urban areas they are serving the majority of schoolchildren. Their quality is higher than that of government schools provided for the poor—perhaps not surprisingly given that they are businesses dependent on fees to survive and hence are directly accountable to parental needs.”

Tooley’s work suggests that the deep yearning parents have to give their children the very best is nearly universal. Unfortunately, it also reminds us just how much education can be fetishized by those who would like it to be removed from the market utterly—which also means removed from the entrepreneurial environment that yields both quality and innovation. Again and again we encounter “experts” who say that education must be under government control and who get in the way of educational entrepreneurs who think otherwise.

A common obstacle faced by private-school entrepreneurs is government regulation used to protect special interests. “We find it possible to meet all of their regulations,” says plaintive Nigerian educator Bawo Sabo Elieu, “but we can’t possibly afford them all.” Elieu is one of many among the world’s private educators who are trying to do something for poor children, despite the encroachment of the regulatory (and in Nigeria, predatory) state.

Rather than dwelling on the well-known reasons why government schools serve students so poorly, Tooley concentrates on the innovations that are possible when the passions and preferences of human hearts to educate the young go unsatisfied. Parents work extra and scrimp to afford the modest fees at makeshift schools. School founders and teachers continually search for ways to do better. Tooley reports that in his visits to these schools, he was usually asked for advice on ways to improve them—when he had come to learn from them! We should take inspiration from the stories of parents, teachers, and kids unwilling to settle for ineffective government schools despite the many obstacles to educational freedom.

Many of Tooley’s third-world stories echo the issues we face here in the United States. Private schools for the poor must compete with “public schools” that charge nothing. Teachers’ unions engage in favor-seeking and protectionism. Government officials and experts argue that schools that charge fees cannot, by definition, be “for the poor.” Regulations make it hard for educational entrepreneurs to challenge the status quo. The politics of guilt and envy are played to the advantage of the educational elites and at the expense of ordinary people who know that government schools handicap their children.

If caring parents and educators can build private schools that work in Kenya, Nigeria, and other poor nations, we can do the same here in the United States. Our circumstances are different, but the desire to have the best for our children is universal. No government can quell that desire.

The Beautiful Tree has a profound and universal message: Freedom works in education. It’s time for Americans to follow the example of the poor people Tooley writes about and invest in private schools, growing that sector enough to hasten a brain drain from “public” to private. The contrast between high-cost, ineffective government schools and low-cost, effective private schools will be too great to ignore. Tooley’s book deserves a thunderous round of applause for showing that the government education empire can be outflanked by determined people.

Nassim Nicholas Taleb is famous for introducing us to black swans. Though these rare creatures have long been used among academic philosophers to explain the shortcomings of reasoning by induction (“Every swan I’ve ever seen has been white, therefore all swans are white.”), Taleb uses the black swan as a stark metaphor for the inevitability of highly improbable events. In other words, black swans are rare, but one will swim by eventually.

As far as Wall Street—particularly the people with a large stake in getting things right—is concerned, this financial crisis involved a confluence of events. Some of these black swans were set in motion by government, like flexible lending standards to extend home ownership, Fannie and Freddie, and a mortgage-friendly tax code. Others were set in motion by willfully ignorant bankers, big shot risk-modelers, and people believing they could live beyond their means. It all came together in a fantastic cascade of failure. The trouble is, no one—neither government nor market actors—can predict such a large-scale event. Black swans happen.

The other important thing to remember is that the economy is a chaotic system. Most of the time chaotic systems achieve a sweet spot between order and chaos, which is a good thing if an economy is to be robust. Chaotic systems, though, change constantly and involve dynamics that are highly sensitive to initial conditions.

An Ecosystem, Not a Machine

Sadly, we’re getting a whole lot of precisely the wrong kind of thinking in response to this crisis. Indeed most of the bad thinking arises from viewing the economy through the lens of a false metaphor: economy as machine. We’ve heard pundits accuse the government or banks of being “asleep at the switch.” But in a complex system, there is no switch. We’ve heard people ask how to “fix it,” “run it,” or “regulate it,” suggesting if just the right sort of genius controlled the rheostats, we’d get just the right sort of economy.

The economy is not like a machine at all. It is rather more like an ecosystem that no one can run, fix, or regulate. The hubristic sort of person who thinks he or anyone can run an economy is the victim of what Hayek called the “fatal conceit.” If given power, the planner will end up making the rest of us the victims of his false metaphor.

It is ironic that Alan Greenspan—once adored by the press but now pilloried by it—is being blamed not only for wielding a laissez-faire ideology that supposedly caused the crisis, but also for failing to predict a black swan. Greenspan was a single, powerful government bureaucrat in charge of gathering enough data to determine the “right” interest rate for a multitrillion-dollar economy. Given the size of that task, he did pretty well for many years. But he was one man. He was housed in a government building. He held an unelected office and made decisions in a bureaucracy that has a monopoly on money and influences the price of credit, at least in the short run. One can hardly call that free-market fundamentalism. Whether Greenspan offered artificially cheap credit or not, interest rates were only one factor among many. To have asked him to predict the best of all possible worlds and adjust interest rates accordingly would have been to ask him to be an oracle channeling the knowledge only God would have. Greenspan is not omniscient. Nor is Bernanke. No one is. But to “run” an economy would require not only omniscience, but omnipotence as well—a power that would bend the actions of millions to its singular will.

Whatever your ideological persuasion, the economy is a complex system that cannot be planned, designed, or have its black swans regulated away. Far from the caricatures sketched in the papers, this is precisely what serious free-market types have been saying for years. That’s why it’s a little more than silly to blame free-market ideology for the current mess, and a little more than mendacious to claim that government fingerprints won’t appear all over the crisis when the postmortem is done.

Hunting Black Swans with Shots in the Dark

The timeless nostra of the politician are to prime the pump (machine metaphor) and to regulate. It seems so simple. But that response is deceptively linear. If you could ask FDR, might he now concede his policies stretched the Depression out for a decade beyond what was necessary? He listened to J.M. Keynes and a coven of interventionists. If we agree that our mixed economy is a complex system, then we also have to agree that the benefits the partly free market confers are an emergent property of that system. If we attempt to regulate away the rare, unforeseen black swan event, the costs of our hubris will be terrible, for we will regulate away untold benefits, too.

In the real world the question may come down to whether we should accept a couple of years of painful market adjustments or decades of recession caused by the blunt instrument of politics. Devastating unintended consequences and unseen effects will follow government attempts to clean up a mess made in great measure by its own hand. Why? Because no one possesses a God’s-eye view of the economy. Government intervenes within the system as part of it, not from outside of it. Nor is the economy an instrument to be manipulated to positive effect—at least not over the long term. That is why Keynes got it so terribly wrong and why the economy must heal itself from within in a distributed, holistic way.

People want government, like God, to come down and fix the unfixable, or explain the inexplicable. That’s why they’re finding it easier to blame greed for our current financial crises. But greed is rather more like gravity: When you fall, you can blame either Newton or the banana peel on the ground.

The profit motive is a good thing when it operates in an environment where bad bets are punished with losses and good investments are rewarded. Only government can distort that healthy profit-and-loss system, giving people incentives to make bad decisions. And it’s in this environment that greed is no good to anyone. It turns out, however, that greed—or better, rational self-interest—can help our economy stabilize faster than government ever could. As the lubricant of our economic system, self-interest will cause a million market actors to recalibrate and to direct resources to projects that create value in our society. We the people will temper our irrational urges and mitigate our risks if government restores the rules that let profit and loss bring discipline. But if government continues to change the rules to bias the market in favor of irrational behavior, rent-seeking, and corporatism, the chaotic aspects of the system will continue to wobble out of equilibrium. Black swans will become commonplace.

The itching question becomes: What do we do? If your answer is “Get the government to do something,” eight world-class economists will give you a failing grade. The economists are Jagdish Bhagwati, Bruno Frey, Justin Yifu Lin, Nancy Stokey, and Nobel laureates Vernon Smith, Douglass North, Robert Fogel, and Thomas Schelling. They comprise the panel assembled by the Copenhagen Consensus Center, headed by Bjørn Lomborg, author of The Skeptical Environmentalist. In 2004 the panel, which operates under the auspices of the Copenhagen Business School, inquired into which of the world’s major problems would be most soluble (measured by bang for the buck) if $50 billion were available for the task. On a list that included diseases, malnutrition, and economic problems, the group ranked global warming dead last. In the language of cost-benefit analysis, government fixes for climate change promise big costs with little to no benefits. (The top-ranked proposal was control of AIDS/HIV. A complete analysis of the rankings is found in Global Crises, Global Solutions, edited by Lomborg. The panel will meet again in 2008.)

But you don’t need Nobel laureates to explain why government solutions to climate change are wrong-headed. Let’s linger on the main solutions offered: cap-and-trade and carbon taxation.

A Kyoto-style cap-and-trade system is one in which a government committee establishes an “acceptable” level of greenhouse-gas emissions for relevant industries. If a plant releases greenhouse gases in excess of the standard, it may go into the “carbon market” and purchase units from other companies that have emitted less than the standards call for and so can sell credits. Thus the process uses quasi-market mechanisms to cut emissions—purportedly minimizing costs to the plants.

Capping might work well to clean up, say, the Chesapeake Bay. But if applied globally the problems are manifold. First, no cap-and-trade system yet conceived has been able to promise a significant reversal in warming trends. (Even a number of Kyoto signatories have admitted this fact.) To bring about an abatement of warming (based on current climate science), cap-and-trade standards would have to be set so high that many industries would be crippled, with unforeseeable ripple effects, potentially leaving millions without work in the developed world. If there are fewer economic resources as a result of the standards, it will be harder to adapt to local global-warming problems.

Second, a truly effective cap-and-trade system would require virtually unanimous agreement from the developing world as well. If developing countries were to opt out, their industries would produce more while industries in the developed world produced less. So emission levels would remain unchanged at best. On the other hand, even if the emerging giants—for example, China, India, Russia —were somehow convinced to agree to a cap-and-trade scheme, their development would be severely retarded, leaving millions destitute.

Third, unanimous international agreement, even if it wouldn’t sound the death knell for the developed economies, would kill the hopes of the poorest nations.

But unanimity is not feasible, given the incentives to defect. And temptations to do so by high-growth industrial newcomers like China would be especially great. Cap-and-trade would thus provide an indirect subsidy to the developing world—with all its dirty, less-sophisticated, carbon-emitting industries. Emitters would subsequently be encouraged to move to defectors’ shores—often to countries with poor political institutions—despite the risks. This outcome would mean little for economic growth in the developed world, force industrial collusion with corrupt governments in the developing world, and do nothing for climate-change abatement. (Indirect subsidies to poor countries may sound great to someone who cares about global redistribution; but it does not bode well for those keen to stop global warming.)

In short, an international cap-and-trade system would seem to offer an unpleasant choice of evils. Ad hoc attempts to lessen such evils after the fact would result in unintended consequences and epicyclical policies.

Carbon Taxes

What about carbon taxes? Overall, similar cost-benefit disparities affecting cap-and-trade apply also to taxes. But at least to some with a market orientation, taxes would have the effect of directly taxing a “bad” (greenhouse-gas emissions) rather than unpredictably taxing a “good” (such as revenues). Thus companies would pay to pollute, and the economic effects would be easier to predict and measure.

The U.S. government largely agrees, and in comparing the two schemes, it comes down largely on the side of taxes. According to the Congressional Budget Office’s issue brief “Limiting Carbon Emissions: Price Versus Caps” (March 15, 2005):

The cost of meeting a given cap on carbon emissions is likely to be difficult to estimate for at least three reasons. First, the cost of meeting a future cap would vary significantly with the amount of growth in carbon emissions in the interim. Those emissions are difficult to predict: they are a function of numerous factors, including population trends, economic growth, and energy prices. Second, policymakers have less information about the cost of controlling emissions than do the firms that create them. Third, the cost of meeting the future cap will depend on the technologies that are developed to reduce carbon dioxide emissions and the economic consequences of adopting those technologies—neither of which can be predicted with certainty.

But in terms of abatement, it’s not clear that taxes could reduce emissions as effectively as caps. In fact, most economists believe that a cap-and-trade system would have a more predictable (and forceful) effect on abatement—notwithstanding its effects on the economy. So, sort of like with Heisenberg’s Principle, it’s all in where you want your uncertainty.

Opting for Taxes

It is predictable that the government would opt for taxes: it likes the revenue. Similarly, “bootlegger and Baptist” coalitions—alliances of privilege-seeking firms and moralistic environmental activists—would benefit more from taxation than capping. Clever companies like Duke Power and Progress Energy have already begun to side with environmental groups to lobby government for carbon taxes instead of caps. Why? So they can benefit from their competitors’ taxation woes. (Progress and Duke have nuclear and natural-gas interests.) Alas, rent-seeking companies would turn right around and burn their natural gas for energy, only to leak methane, which has a 25-times greater greenhouse effect than carbon dioxide. Of course, methane and H2O emitters could be taxed too, but then you’re back to the overall problem of how much of the global economy you have to cripple before the globe cools down.

In any case, the Copenhagen Consensus panel and a number of other economic realists think the best thing we can do for climate change is to make local adjustments. (See “Living with Global Warming” by Indur Goklany, www.ncpa.org/pub/st/st278/.)

If we keep getting richer, we may find technological measures both for mitigating negative effects of climate change as well as for sequestering greenhouse gases. Until then, very few credible economists argue that we should slow growth or hobble the global economy—assuming, that is, the climate change skeptics are wrong. What we are left with, then, is an ironic symmetry between two sets of consensus: one that says man is warming the earth and one that says we’ll do best simply to adapt.

Such is basically the tale of Lafayette, Louisiana, and it reflects what to many is a disturbing trend of municipalities offering broadband as if it were a public utility like water or sewerage. The story, now known as “The Battle of Lafayette,” also reveals the symptoms of “demosclerosis” — Jonathan Rauch’s term for government failure due to rapacious special interest.

We tend to associate what economists call “rent-seeking” with Washington, D.C., where parasites stand to gain by lobbying for either anti-competitive regulation or subsidies. Benefits accrue to only a few groups: those on whose behalf the lobbyists are working, the politicians (in the form of perquisites and happy district constituents), and the lobbyists and lawyers themselves. The costs are spread thinly over the rest of us in the form of higher taxes and/or a dead-weight loss to the economy.

But Washington has no monopoly on rent-seeking. At the municipal level its consequences can be dire. The concentrated benefits and dispersed costs are more difficult to mask when you’re talking about a hundred thousand people versus three hundred million.

Parasites? Isn’t that a little unfair? After all, the people of Lafayette have legitimate concerns. They want to develop—that is, to keep up with the rest of the country technologically lest they be left behind. As they see it (and by “they” I mean the town council, the folks demanding broadband, and the government-controlled public utility), a $135 million investment is an investment in infrastructure—something that should be considered a public good for the people of Lafayette. They had been perfectly willing to let so-called “incumbents” (BellSouth and Cox Communications) come in and provide this good at a reasonable price. But Big Telecom didn’t. Therefore, shouldn’t the people of Lafayette have a right to connect more quickly? Shouldn’t they have broadband too?

The unfortunate aspects of this view are manifold. First, it fails to take into account the wider implications of municipalizing broadband (to which we’ll turn in a moment). Also, some of the best and brightest technologists on earth are behind these efforts, giving folks the impression that brilliant coders know what’s best for the economy simply because they might have worked on protocols for the Internet. But more unfortunate still is that the Lafayette scenario could set a precedent for other municipalities to work under the mistaken notion that government-owned and government-operated broadband is a good idea.

Intellectual honesty check: shouldn’t we wonder why Big Telecom didn’t come to Lafayette? Some say these companies are driven only by their lust for profit. Yes. But the better answer is that it was cost-prohibitive. In other words, no one thought he could do it without operating at a loss. If anyone in Lafayette really thought he could make money providing broadband, why didn’t he seize the entrepreneurial opportunity rather than see broadband as a good that should fall like manna from heaven or from the Lafayette Utility Service?

The Citizen’s Action Committee for Fiber-Optic Broadband (or whatever) knew exactly what Cox and BellSouth knew—that broadband in Lafayette was a losing proposition. Despite however many “market studies” the government and Chamber of Commerce can trump up, the proof is ultimately in the unwillingness of Cox and Bell South to move into the Lafayette market. Thus the only way for the interest group to get what it wanted was simply to take it from other citizens.

Lafayette isn’t walking this road alone. Other towns are doing it. And they’ve got the beginnings of a D.C.-sized interest group forming behind them as I write. In fact, the demand for immediate universal broadband was the dominant theme at the recent Freedom to Connect (F2C) conference in Washington. (Don’t be confused by the name. “Freedom to Connect” is a freedom in the same way that a “right to health care” is a right.) The “monopolists and duopolists”—goes the story—have priced most people out of the market. And the gross disparity between the broadband haves and have-nots is due to the profit-seeking behavior of the usual suspect—Big Telecom. So for adherents of the open-access movement to be “free to connect” amounts to varying degrees and means of broadband socialization. Here are a few of those proposed means:

• Encourage municipalization of broadband, exemplified by the Lafayette case. (In other words, allow local governments to begin entering the market.)

• Change the FCC’s framework from regulating the entire telecom service to focusing on companies’ horizontal layers, for example, content, application, network, or physical infrastructure.

• Use tried-and-true trust-busting in court.

• Appeal to legal precedents like ” nondiscriminatory” rules, such those used against railroads and seaports over a century ago, which forced property owners to lease their services to all comers. (The recent Brand X decision by the Supreme Court protected cable companies from being forced to open their lines to broadband competitors.

Curiously, all these nostrums are suggested in the name of greater competition.

But we should step back and ask: what creates big broadband duopolies? Sometimes it’s simple economies of scale. If you want a big, expensive project done, you need a big, expensive company to do it—of which there are not many. Barriers to market entry for smaller companies often come simply in the fact that the initial capital investment is too big. Even if we overlook other barriers to entry created by the current regulatory regime and costs such as city fees, we still have an expensive venture in building a broadband infrastructure. Entrepreneurs in Lafayette know this. But since the municipality will act with taxpayer money and spread both the risk and the costs over its citizenry, it won’t have to behave according to pesky market laws.

As in many other efforts to save the world by distorting the laws of supply and demand, advocates of “open access” say that within the United States there are a number of “digital divides,” between rich and poor, between urban and rural, and between white people and certain minorities. To bridge this divide, government must take action. To illustrate this, they go on to cite broadband-access rates in other countries to show that U.S. per capita broadband access is lagging. (My own statistics come from the Congressional Budget Office.)

So why aren’t the rates greater in the world’s richest nation? The reasons are numerous , but require only a modicum of common sense. Consider the size and population density of the United States. Now consider the size and population density of the world’s broadband leader, South Korea. The economies of scale for offering broadband to every person in South Korea are considerably different from those in most of the United States.

According to CountryStudies.us , “South Korea was one of the world’s most densely populated countries, with an estimated 425 people per square kilometer in 1989—over sixteen times the average population density of the United States in the late 1980s.” One will find that other, more-densely populated and culturally homogenous counties are “ahead” of the United States in Internet access, since (naturally) it’s cheaper and less risky to invest in broadband infrastructure in densely populated areas.

Even in a large country like Canada (said to rank number 2 in the world behind Korea in broadband adoption), 90 percent of the Canadian population lives within 100 miles of the U.S. border, government broadband subsidies notwithstanding. Again, common sense says that as the technology matures and as the price goes down, access rates will increase—even into the thickets of rural America and the public-housing blocks of Detroit.

Why the Divide?

Great. But why is there a broadband divide between ethnic groups in the United States? Aren’t poorer people priced out of the market by monopolists? Or is it creeping racism? Maybe. But if such were true, wouldn’t people similarly be crying foul about other divides?

With other technologies, divides hardly exist, if they exist at all. Consider mobile phones, which are comparably priced to broadband connections on a monthly basis. What about videogame consoles? Aren’t Xbox and Playstation the products of a duopoly? Television sets, cable, and DVD players? Again, divides here are virtually nonexistent. Why the difference?

The reason may be that people place different values on these things, and those values can be an ethnic and cultural phenomenon. As unfortunate as it may be to middle- and upper-class America, a family in the inner city may place greater value on a Playstation or a cell phone than on broadband. Someone living in a rural area may be more likely to invest in a satellite dish than an Internet connection. We all face opportunity costs.

We can’t assume that a bar graph about broadband access can tell us anything other than what groups of people are more or less likely to value. “Well,” one might say, “they ought to value broadband because it can provide so many more opportunities for them.” Fortunately, markets don’t work by what intellectual elites think people should have.

And what about the satellite dish? Isn’t this another example of a competitive technology that filled the void in the lives of rural people that cable was unable to fill? Given another year or so, analogous technologies will begin to fill any broadband void that might be out there—especially if the U.S. government will let go of more of the spectrum.

The speed of innovation is blinding. Before World War II, Stalin built state-of-the-art factories in Russia. By the time the Soviet Union collapsed in the 1990s, the people of Russia were still using post-World War II factories. The point is that government projects are notoriously bad at keeping up with the pace of technological change.

Have you ever heard of Minitel? If so, probably only as the butt of a techno-geek’s joke. Minitel was the French government’s proto-Internet—a communication device designed for use by every French citizen. Of course, Minitel was soon forced into virtual obsolescence by the Internet and arguably never paid itself off (even by the standards of state utilities). The mantra of the tech market is: Better. Faster. Cheaper. Now say it again fast.

The irony in all this is that for the Louisiana case, poor, hard-working taxpayers will have to shoulder much of the burden to subsidize the more well-to-do people of Lafayette who want broadband. There are some vital questions the city leaders should be asking: Are we making the best possible use of other people’s money? Given a finite set of tax revenues, are there more important things that we could be investing in? Is the water clean? Are the police and firemen adequately equipped? Are we going to hang the town on too risky a venture? If the city is wrong about this broadband bet, Lafayette can kiss sewage treatment and police cruisers goodbye.