Brian Ferguson at A Canadian Econoview makes an interesting point:
Ever wonder why so many economists are sceptical
about man-made global warming? It's because we've had a lot of humbling
experience with just how quickly large scale computer models can go
very badly wrong. Remember when we had inflation and unemployment under
control through Keynesian fine-tuning?
There are some interesting parallels between the atmospheric sciences (climatology and meteorology) and economics: they study highly complex systems, the available data are non-experimental, and their results have significant policy implications. Not surprisingly, both rely heavily on models as tools for understanding what is going on and why. Of course, models need not be based on a computer simulation, or even mathematics. As Paul Krugman notes, you can put one together using some ordinary household appliances:
Dave Fultz was a meteorological theorist at the University of Chicago, who asked the following question: what factors are essential to generating the complexity of actual weather? Is it a process that depends on the full complexity of the world -- the interaction of ocean currents and the atmosphere, the locations of mountain ranges, the alternation of the seasons, and so on -- or does the basic pattern of weather, for all its complexity, have simple roots?
He was able to show the essential simplicity of the weather's causes with a "model" that consisted of a dish-pan filled with water, placed on a slowly rotating turntable, with an electric heating element bent around the outside of the pan. Aluminum flakes were suspended in the water, so that a camera perched overhead and rotating with the pan could take pictures of the pattern of flow.
The setup was designed to reproduce two features of the global weather pattern: the temperature differential between the poles and the equator, and the Coriolis force that results from the Earth's spin. Everything else -- all the rich detail of the actual planet -- was suppressed. And yet the dish-pan exhibited an unmistakable resemblance to actual weather patterns: a steady flow near the rim evidently corresponding to the trade winds, constantly shifting eddies reminiscent of temperate-zone storm systems, even a rapidly moving ribbon of water that looked like the recently discovered jet stream.
What did one learn from the dish-pan? It was not telling an entirely true story: the Earth is not flat, air is not water, the real world has oceans and mountain ranges and for that matter two hemispheres. The unrealism of Fultz's model world was dictated by what he was able to or could be bothered to build -- in effect, by the limitations of his modeling technique. Nonetheless, the model did convey a powerful insight into why the weather system behaves the way it does.
The important point is that any kind of model of a complex system -- a physical model, a computer simulation, or a pencil-and-paper mathematical representation -- amounts to pretty much the same kind of procedure. You make a set of clearly untrue simplifications to get the system down to something you can handle; those simplifications are dictated partly by guesses about what is important, partly by the modeling techniques available. And the end result, if the model is a good one, is an improved insight into why the vastly more complex real system behaves the way it does.
Popular usage notwithstanding, climatologists have not 'proven' a link between human production of greenhouse gases and global warming. Rather, according to the models that - in their best judgment - best reproduce the main features of the available climate data, the most likely explanation for the increases in the average temperatures we observe is the warming effect of greenhouse gases. That doesn't mean there isn't a more likely explanation - just that no-one has yet been able to think of one.
Although the idea of making important - and possibly very costly - policy decisions based on a modeling exercise doesn't seem to bother many people when atmospheric scientists do it, economists have a harder time getting away with it:
When it comes to physical science, few people have problems with this idea. When we turn to social science, however, the whole issue of modeling begins to raise people's hackles. Suddenly the idea of representing the relevant system through a set of simplifications that are dictated at least in part by the available techniques becomes highly objectionable. Everyone accepts that it was reasonable for Fultz to represent the Earth, at least for a first pass, with a flat dish, because that was what was practical. But what do you think about the decision of most economists between 1820 and 1970 to represent the economy as a set of perfectly competitive markets, because a model of perfect competition was what they knew how to build? It's essentially the same thing, but it raises howls of indignation.
Why is our attitude so different when we come to social science? There are some discreditable reasons: like Victorians offended by the suggestion that they were descended from apes, some humanists imagine that their dignity is threatened when human society is represented as the moral equivalent of a dish on a turntable. Also, the most vociferous critics of economic models are often politically motivated. They have very strong ideas about what they want to believe; their convictions are essentially driven by values rather than analysis, but when an analysis threatens those beliefs they prefer to attack its assumptions rather than examine the basis for their own beliefs...
The problem is that there is no alternative to models. We all think in simplified models, all the time. The sophisticated thing to do is not to pretend to stop, but to be self-conscious -- to be aware that your models are maps rather than reality.
There are many intelligent writers on economics who are able to convince themselves -- and sometimes large numbers of other people as well -- that they have found a way to transcend the narrowing effect of model-building. Invariably they are fooling themselves. If you look at the writing of anyone who claims to be able to write about social issues without stooping to restrictive modeling, you will find that his insights are based essentially on the use of metaphor. And metaphor is, of course, a kind of heuristic modeling technique.
In fact, we are all builders and purveyors of unrealistic simplifications. Some of us are self-aware: we use our models as metaphors. Others, including people who are indisputably brilliant and seemingly sophisticated, are sleepwalkers: they unconsciously use metaphors as models.
This doesn't mean that conclusions based on models are always right; quite the opposite. Models are approximations, and approximations are 'wrong' pretty much by definition. The problem is that it's hard to know if the model is wrong in a way that significantly affects its usefulness for policy analysis. Indeed, many advances in economic thought have occurred because a model-based policy went wrong in an unexpected way. A good economist will always make a clear distinction between a model and reality.
Since I personally know nothing about climatology, I'm willing to defer to the judgment of those who do. But there's always the risk that climatologists - being human - have gotten it wrong. Greenhouse gases may not turn out to be that big of a deal. On the other hand, they may be even more of a problem than even the worst of the model-based scenarios would predict.
When it comes to climate change policy, the most important question may be: Do we feel lucky?
