“Comparative Statics” and Global Warming

A “naive” part of economic science is called “comparative statics”. It is simply a mathematical way to analyze optimums – optimal production through optimal inputs, optimal outputs, and optimal profits. Since we do not yet have the tools to understand and thoroughly take all dynamic parameters to account when making decisions, this branch of economics makes decisions based on reasoning as:

if all parameters and variables are held constant except x_i, then what x_i should we choose to reach the optimum?

As a tool this may very well be useful, simply because all alternatives are utterly useless.

The major shortcoming of comparative statics is that it, as a tool for analysis and decision-making, provides guidance in an inherently dynamic world through inherently static means. It should be obvious that whatever the results of a comparative statics analysis, it is never correct. It does, however, provide a sense of “knowing” what happens and thus it is a basis for believed certainty in the environment, business or government body, where decisions are to be made.

What is important in a world of constant change is to make decisions, and to be as well-informed as possible. Not making a decision can often be more costly than making a decision that is wrong but can be corrected at a later time. Most businesses cannot continue functioning without making decisions, and thus the non-making of a decision generates costs and uncertainty for the time until the decision is finally made. The decision, in other words, is unescapable.

Such unescapable questions may be difficult to imagine, but they are not in any way uncommon. Imagine a business not making decisions such as:

• – What output should we produce?
• – How much output should be produced?
• – How much input should be used?
• – How should the production process be organized?
• – How should our mix of labor and capital in the production process be?

It is quite easy to imagine what would happen to a business (or, for that matter, a government agency) that does not make decisions as to what to produce and how to produce it. It is also clear that not making a decision means whatever fixed costs still need to be covered, while extra costs are generated simply as an effect of the uncertainty caused by the non-decision.

Making a decision is thus beneficial, even if the decision itself is not the optimal decision. A poor decision is better than no decision, and correcting a bad decision may very well be less costly than the state of non-strategy arising from no decision at all. In this situation, comparative statics provides a means to make decisions that are not totally out of the blue. Based on the (faulty) assumption that all but the choice variable(s) can be fixed, one can mathematically calculate the optimum.

Sometimes having something to aim for is more important than knowing the target.

But comparative statics should not be accepted as a tool to discover The Truth. Understanding the limitations and shortcomings of this tool is essential for making the best use of it. Sometimes a business decision based the decision-maker’s hunch, but perhaps taking the results of comparative statics analysis under consideration, is better than the “naked” comparative statics recommendation. The reason for this, as has already been mentioned, is the world being inherently dynamic, a fact that is reasonably a basis of the “hunch”.

Comparative statics is however not only a means used in economic science, it is in essence a tool used by all sciences to draw conclusions of data and make predictions about the future. This kind of analysis offers guidance, but does not deliver the truth about the world and should never be relied upon to 100%. It should rather be a tool used for assistance when other means for understanding the world are unavailable or provide nothing but absurd recommendations.

The problem of static models

Theoretically, a static model could approximate the real world if all important variables are considered and made part of the model. In the study of a well-demarcated business firm, for example, most parameters are already known. We know most of the variables that are important for the decision to be made, and they are all part of the analysis: prices of inputs and outputs, quantities of inputs and outputs, the technology used in the production process, etc.

What we do not know is the market for inputs and outputs, and so we make assumptions that it is always possible to get more inputs and sell more outputs. We also assume it is possible to throw away whatever outputs we do not need, so that making more than the optimum is not a problem in the production model. These assumptions are known to be only partly correct – we know, for instance, that the prices of inputs may go up or down if our demand for them increases, and we know that we might not be able to sell larger quantities of outputs without lowering the price.

But these assumptions, even though they are important and have known shortcomings, do more good than they cause harm to the analysis. There may be costs associated with throwing away outputs produced in excess of the optimum, but such costs may not have a great effect on our decision (after all, we do not want to produce excess goods anyway!).

The situation would be considerably worse if we did not know the landscape in which we are to navigate – if we didn’t know the major variables and parameters in the world of the business firm, we would not be able to make predictions. At all. In such a situation, in a dynamic world that we do not understand, comparative statics would not only be useless – it would be a tool causing nothing but destruction if relied on.

Comparative statics and climate models

The latter situation is in essence what we see in the climate research. Scientists in this field repeatedly assert that the climate system on earth is very advanced and that we do not yet fully understand it. Actually, we do not understand fully the basic mechanisms in the system – we cannot distinguish cause from effect, and we cannot identify which variables are more important. The sad truth is that we simply don’t know. But we are learning.

An obvious conclusion to be drawn about the study of climates is thus that models and tools sharing the characteristics of economics’ “comparative statics” method should prove worthless – potentially generating disinformation. Yet the climate hysteria and the alarmism about global warming and the “greenhouse effect” bases the predictions on such statistical models. The models, in turn, are based on unconfirmed assumptions and lack of understanding the basic mechanisms of the climate system.

This does not, however, mean that the study of climates is impossible in any way whereas economics is not. Climate change takes place in a system that is much more closed than the business firm – the climate system encompasses the Earth and the exogenous variables should be fairly known. Also, the climate system is in no way based on human beings acting, which – compared to economic science – should make climatology much less advanced and much more rule-based. What we study in a climate system are non-living automatic mechanisms, cause and effect nexuses.

The reason the climate system is not yet well-known is simply a result of the age of science. Whereas economics is a science that has literally been researched and pondered since the Ancient Greeks (if not before), the climate system has at best been studied for merely a century. The models predicting the climate system are based on temperature data collected only since the late 19th century – the models, methods, and predictions are therefore bound to include huge errors.

Actually, the climate debate supplies proof that this is so. We might think we know what is going on, but why then did people fear a “new ice age” in the 1970s and 30 years later they fear global warming? The global cooling bound to drag the world into another Ice Age was the scientific predicitons based on state of the art climate system models then, just like the predictions of floodings and a scorged Earth due to increased temperatures is what that very same field of research now claims is “true”.

Of course, we might consider the models now used much better than the models in the 1970s – we must, after all, have learned a lot in the three decades that have passed. And, indeed, we do know a lot more about the climate system today than we did 30 years ago. But the models still include quite a few blind spots. How does, for instance, magnetic radiation from the sun affect the climate system? This is a question not even asked just a few years back. But as anyone should know, the sun has a great effect on the habitability of this planet, the emergence and existence of life, as well as chronobiology.

Yes, the ices of the poles are melting. We know that. But we also know that the glaciers on the planet Mars are melting – and the melting on both planets seems to occur at the same time. That should tell us something.