Recipe for Failure
Why Copenhagen will be a bust, and other prophecies from the foreign-policy world's leading predictioneer.
Want to know what's going to happen with climate change? Is the world going to come together this December at the Copenhagen summit, or at some future date, and regulate away enough of the greenhouse gases that are heating up the planet to warm Al Gore's heart? I'm no climate scientist, but I've done my own calculations, and I can tell you the answer: probably not.
Want to know what’s going to happen with climate change? Is the world going to come together this December at the Copenhagen summit, or at some future date, and regulate away enough of the greenhouse gases that are heating up the planet to warm Al Gore’s heart? I’m no climate scientist, but I’ve done my own calculations, and I can tell you the answer: probably not.
Despite the hoopla, the U.N. climate change conference in Copenhagen is destined to fail. Here’s what will happen instead: Over the next several decades, world leaders will embrace tougher emissions standards than those proposed — and mostly ignored — in the 1997 Kyoto Protocol. But real support for tougher regulations will fall. By midcentury, the mandatory emissions standards in place will be well below those set at Kyoto, a far cry from the targets for carbon dioxide and other greenhouse gases set to be discussed by world leaders in Copenhagen. And by the time 2100 rolls around, the political will for tougher regulations will have dried up almost completely. The reasons are many, but come down to this: Today’s emerging powerhouses like Brazil, India, and China simply won’t stand for serious curbs on their emissions, and the pro-regulation crowd in the United States and Europe won’t be strong enough to force their hands.
How do I know all this? Because in 1979, I learned that I could predict the future.
Don’t get me wrong — I’m no soothsayer and I have no patience for crystal-ball gazers, astrologers, or even most pundits. In my world, science, not mumbo jumbo, is the way to predict people’s choices and their consequences for altering the future. I use game theory to do just that for the U.S. government, big corporations, and sometimes ordinary folks, too. In fact, I have made hundreds, even thousands, of predictions — a great many of them in print, ready to be scrutinized by any naysayer. For instance, I can tell you right now that bribing Kim Jong Il to mothball, but not eliminate, his nuclear program is the best way to handle North Korea, that the land-for-peace formula in the Middle East won’t succeed, and that it will take approximately $1.5 billion annually in U.S. aid to Pakistan to keep that country’s government fighting the Taliban and al Qaeda.
There is nothing uncanny about my ability to predict. Anyone can learn to use scientific reasoning to do what I do, though I’ve been refining the model I use ever since I accidentally got into the prediction business back in the last days of disco.
The opportunity initially fell into my lap when a U.S. State Department official called to ask me who was likely to be India’s next prime minister. At the time I was a professor of political science at the University of Rochester — where the application of game theory to political questions originated — and I had written my Ph.D. thesis at the University of Michigan about winning and losing strategies among India’s opposition parties. So the State Department official was asking me to use my "expert" knowledge to speculate about the next Indian government.
It happened that I had just designed a mathematical model for a book I was writing about war, as well as a little computer program to make the necessary calculations. The program provided a way to simulate decision-making under stressful circumstances like those that sometimes lead to war. It calculated the probability that actors would get what they wanted if they chose one course of action (say, negotiations) or another (like war), weighting the probabilities by an estimate of how much the decision-makers valued winning, losing, or intermediate compromise outcomes. Of course, it also recognized that they had to work out how others might respond to the choices they made.
The phone call about India got me thinking that maybe war and peace decisions really aren’t that different from everyday political confrontations. Sure, the stakes are higher — people get killed in wars — but then any politician seeking office sees the personal political stakes as pretty darn high. Intrigued, I grabbed a yellow pad and listed everyone I thought would try to influence the selection of India’s next government. For each of those people (political party leaders, members of India’s parliament, and some members of critical state governments), I also estimated how much clout they had, what their preference was between the various plausible candidates for prime minister, and how much they cared about trying to shape that choice. With just one page of my yellow pad filled with numbers, I had all the information the computer needed to predict what would happen, so I plugged it in and awaited the results.
My "expertise" had led me to believe that longtime parliamentary leader Jagjivan Ram would be India’s next prime minister. He was a popular and prominent politician who was better liked than his main rivals for the prime minister’s job. I was confident that he was truly unbeatable. He had paid his political dues and it seemed like his time had come. Many other India watchers thought the same thing. Imagine my surprise then when my computer program, written by me and fed only with my data, predicted an entirely different result. It forecast that Charan Singh would become prime minister, that he would include someone named Y. B. Chavan in his cabinet, and that they would gain support-albeit briefly-from Indira Gandhi, then the recently ousted prime minister. The model also predicted that the new Indian government would be incapable of governing and so would soon fall.
I found myself forced to choose between my personal opinion — that Ram would win — and the logic and data behind my model. In the end, I chose science over punditry. When I relayed my findings to the State Department official, he was taken aback. He noted that no one else was suggesting this result and that it seemed strange at best. When I told him I’d used a computer program based on a model of decision-making that I was designing, he just laughed and urged me not to repeat that to anyone.
A few weeks later, Charan Singh became the prime minister with Y. B. Chavan as his deputy prime minister and support from Indira Gandhi. And a few months after that, Singh’s government unraveled, Gandhi withdrew her backing, and a new election was called, just as the computer model had forecast. This got me pretty excited. But had I just gotten lucky, or was I onto something?
I set out to push my model by testing it against wide-ranging questions about politics and economics. I applied it to prospective leadership changes in the Soviet Union, questions of economic reform in Mexico and Brazil, and budgetary decisions in Italy. The model worked so well that it eventually led to a grant from the Defense Advanced Research Projects Agency, a research arm of the U.S. Defense Department. darpa gave me 17 issues to examine, and as it happened, the model — by then somewhat more sophisticated — got all 17 right. According to a declassified cia assessment, the predictions for which I’ve been responsible over the years have a 90 percent accuracy rate.
This is not a reflection of any great wisdom or insight on my part– I have little enough of both. What I do have is the lesson I learned back in 1979: Politics is predictable. All that is needed is a tool, like my model, that takes basic information, evaluates it by assuming people do what they think is best for them, and produces reliable assessments of what they will do and why they will do it.
However reliable my model has proven, though, it still represents a radical departure from the way most "experts" shape decisions about international affairs. Most diplomats, for example, remain convinced that a country’s name is an important variable that helps explain behavior. That’s why the State Department continues to be organized around country desks, just as the intelligence community is organized around geographic regions. Leaders of multinational corporations take much the same view. When they have a problem in Kazakhstan, they call their guys in Kazakhstan to find out what to do. That seems eminently reasonable. Yet it is terribly inadequate for solving most problems.
Certainly knowing about places and how different they might be is important, but not as important as knowing about people and how similar they are, wherever they are. I have not arrived at this view lightly nor, I hope, in ignorance. After all, the training that led to my Ph.D. molded me into a South Asia specialist. I even studied Urdu for five years and did field research in India, so I certainly respect and value area expertise. But area studies alone are a poor substitute for the marriage of knowledge about places and the deep understanding of applied game theorists about how people decide. Surely we would think it ridiculous if chemists believed that oxygen and hydrogen combine differently in China than they do in the United States, but for some reason we think it entirely sensible to believe that people make choices based on different principles in Timbuktu than in Tipperary.
This is a controversial stance in many of the circles in which I travel, and many in those circles see my views as foolish at best and dangerous at worst. In 1984, when I predicted that Ali Khamenei and Ali Akbar Hashemi Rafsanjani would succeed Ayatollah Ruhollah Khomeini as the leaders of Iran, regional experts denounced me as a charlatan (five years later, when I was proven correct, the most prominent such critic publicly apologized). Foreign Policy‘s own Stephen Walt once dismissed rational choice — the theory of human behavior that underpins much of my work — as a "cult of irrelevance." Still, I do not shy away from the risk of publishing predictions — and by and large, those who disagree with me do not do the same.
So why not tackle perhaps the most controversial and consequential question of our time? What does game theory tells us about how — or if — we humans will solve global warming? The timing is perfect: After years of debate, there now seems to be broad agreement within the scientific community that Earth’s temperature is on the rise. And the political will to do something about it is on the rise, too — or so it seems.
I’ll explain why "seems" is the operative word here, but first, some background. In December 1997, 175 countries, not including the United States, signed the Kyoto Protocol. Kyoto produced a large market in which polluters and nonpolluters could buy and sell "pollution rights." This market has helped rationalize decisions at the level of individual firms, but it has so far failed to result in the magnitude of reductions envisioned by the Kyoto Protocol. Enforcing the 1997 agreement has been virtually impossible.
One consequence of the difficulties encountered since 1997 was a meeting in Bali, Indonesia, in December 2007. The Bali meeting had more modest goals than Kyoto. It was an interim step on the way to Copenhagen, where it is hoped there will be a new international agreement. After considerable resistance, the U.S. representative at Bali agreed to significant concessions at the last minute. This made it possible to set out the "Bali road map" for future climate control. Now the question is: Will these efforts work?
Let’s investigate. To address the prospects for controlling greenhouse gas emissions, especially carbon dioxide, we’ll start with data that reflect the views of the big players on global warming. These are the governments and interest groups with the most at stake. In all likelihood, any agreement that can be reached will be settled primarily among these few stakeholders. They include the European Union, the United States (where opinion is divided between those who favor regulating carbon dioxide and other greenhouse gas emissions, and those opposed), China, and India. It also includes other relatively large economies such as Brazil, Japan, Russia, Canada, and Australia. For good measure, I have also represented environmental nongovernmental organizations, because they had a significant presence at Bali, and multinational corporations. For each stakeholder I have estimated potential influence in negotiations over an agreement to replace the Kyoto Protocol, position on mandatory emission controls, salience (eagerness to weigh in on emission controls), and flexibility-the extent to which the stakeholder is committed to finding an agreement (even if not the one it favors most) or will stick to its guns under political pressure (holding out for the policy it believes in).
I have rated the stakeholders’ positions on a scale from 0 to 100. A position of 50 is equivalent to continuing the greenhouse gas targets that came out of the 1997 Kyoto Protocol. These standards called for rollbacks based on 1990 emission levels. Higher values on the scale reflect tougher standards. For example, 60 is a 10 percent toughening of standards relative to the 1990 benchmark, while 100 is a 50 percent increase in mandatory greenhouse emissions reductions compared with 1990. Likewise, values below 50 reflect a weakening of the terms in the Kyoto agreement. If your position is below 50, as is the case with China and India, that means you’re not on board even with the limited emissions targets set in 1997.
Because so much can happen over the next 125 years of my simulation, I have spiced up the model with random shocks to salience and to each stakeholder’s interest in building consensus or sticking to its guns. By randomly changing 30 percent of the salience values and 30 percent of the flexibility values in each bargaining round, we can look at a range of predicted futures to see whether the global warming simulations reveal strong trends. That will help us sort out how confident we can be about the toughness or weakness of future regulations of greenhouse gas emissions.
In terms of the big picture, the heavy solid black line in the graph shows the most likely emission standard predicted by the game. The two heavy dotted lines depict the range of regulatory values that we can be 95 percent confident includes the true future regulatory environment according to the simulations. That range of values is pretty narrow, encompassing barely five points up or down through about 2050. After that, as we should expect, there is more uncertainty, but even as far into the future as 2130, the range is only about 10 points up or down, so these are probably pretty reliable forecasts.The most likely value — the heavy solid line-reflects our best estimate of what the big players might broadly agree to if the global warming debate continues without any significant discoveries in its favor or against it. It tells us two stories. First, the rhetoric of the next 20 or 30 years endorses tougher standards than the ones put forward in Kyoto in 1997. We know this because the predicted value through 2025 is above 50. That’s the green part of the story. Second, support for tougher regulations falls almost relentlessly as the world closes in on 2050, a crucial date in the global warming debate. When we get to 2050, the mandatory standard being acted on is well below that set at Kyoto. By about 2070 it is down to 30, representing a significant weakening in standards. By 2100 it is closing in on 20 to 25. There’s no regulatory green light left in the story by its end.
The figure shows us that there are some considerably more optimistic scenarios and also some considerably more pessimistic views that fall outside the 95 percent confidence interval. The most optimistic scenario predicts no rollback in emission controls. It never dips below 50. In fact, most of the time in this scenario the predicted level of greenhouse gas reduction hovers around 60, implying a 10 percent or so tougher standard than was agreed to in Kyoto. Only about 10 percent of the scenarios, however, look optimistic enough to anticipate even holding the line at the standard set in the Kyoto Protocol.
In contrast, there are dozens of scenarios in which the standard falls close to 0, indicating abandonment of the effort to regulate greenhouse gases. Typically in these scenarios, some mix of Brazil’s, India’s, and China’s salience rises while the salience of pro-control factions in the United States (mostly liberal Democrats) and the European Union drops well below their opening stance. They just seem to lose interest in greenhouse gas regulations. That decline raises its ugly head especially during global economic slowdowns, so global economic patterns are critical to watch, as they can guide our choice of the scenarios that we should pay the most attention to. Without commitment to change by the European Union and the United States, it becomes much easier for the key developing economies to prevail with the support and encouragement of the anti-control American faction (mostly conservative Republicans).
All of this may be leaving you rather depressed, but perhaps it shouldn’t. As for me, I am most optimistic for the future, despite- – yup, despite — agreements like the ones struck in Bali and Kyoto, or the one to be struck in Copenhagen. These will be forgotten in the twinkling of an eye. They will hardly make a dent in global warming; they could even cause hurt by delaying serious changes. Road maps like the one set out at Bali make us feel good about ourselves because we did something. The trouble is, deals like Bali and Kyoto include just about every country in the world. To get everyone to agree to something potentially costly, the something they actually agree to must be neither very demanding nor very costly. If it is, many will refuse to join because for them the costs are greater than the benefits, or else they will join while free-riding on the costs paid by the few who are willing to bear them.
To get people to sign a universal agreement and not cheat, the deal must not ask them to change their behavior much from whatever they are already doing. It is a race to the bottom, to the lowest common denominator. More demanding agreements weed out prospective members or encourage lies. Kyoto’s demands weeded out the United States, ensuring that it could not succeed. Maybe that is what those who signed on — or at least some of them — were hoping for. They can look good and then not deliver, because after all it wouldn’t be fair for them to cut back when the biggest polluter, the United States, does not. Sacrificing self-interest for the greater good just doesn’t happen very often. Governments don’t throw themselves on hand grenades.
There is a natural division between the rich countries whose prosperity does not depend so much on toasting our planet and the poor countries that really have no affordable alternative (yet) to fossil fuels and carbon emissions. They have an incentive to do whatever it takes to improve the quality of life of the people they govern. The rich have an incentive to encourage the fast-growing poor to be greener, but the fast-growing poor have little incentive to listen as long as they are still poor. As the Indian government is fond of noting, sure, India is growing rapidly in income and in carbon dioxide emissions, but it is still a pale shadow of what rich countries like the United States have emitted over the centuries when going from poor to rich.
But when the fast-growing poor surpass the rich, the tables will turn. China, India, Brazil, and Mexico will then cry out for environmental change because that will protect their future advantaged position, while the relatively poor of one or two or three hundred years from now will resist policies that hinder their efforts to climb to the top. The rich will even fight wars to keep the rising poor from getting so rich that they threaten the old political order. (The rising poor will win those wars, by the way.)
So how might we solve global warming and make the world in 500 years look attractive to our future selves? My short answer: New technologies will solve the problem for us. There is an equilibrium at which enough global warming — a very modest amount more than we may already have, probably enough to be here in 50 to 100 years — will create enough additional sunshine in cold places, enough additional rain in dry places, enough additional wind in still places, and, most importantly, enough additional incentives for humankind that solar panels, hydroelectricity, windmills, and as yet undiscovered technologies will be good and cheap enough to replace fossil fuels. We have already warmed enough for there to be all kinds of interesting research going on, but today such pursuits take more sacrifice than most people seem willing to make. Tomorrow that might not be true, and at that point, I doubt it’ll be too late. And, looking out 500 years, we’ll probably have figured out how to beam ourselves to distant planets where we can start all over, warming our solar system, our galaxy, and beyond with abandon.
Remember, we’re looking out for numero uno.
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