# Theory construction (model building)

The professional in any science works within a framework of definitions and concepts that becomes second nature to him. As a result, basic methodological points are frequently taken for granted. In appraising a methodological innovation, however, it is useful to re-examine such points. The explanation and evaluation of computer models can be simplified by examining the nature of theory construction (model building) itself.A theory consists of three elements — definitions, assumptions, and conclusions.  The  following  is  a  simple  and  familiar  example  of  a  theory:

### Assumptions

1. Firms attempt to maximize
2. The marginal revenue curves intersect the marginal cost curves from above.
3. The marginal curves are

### Conclusion

A firm will produce that output corresponding to the point of intersection of its marginal revenue and marginal cost curves.

It is obvious that this theory also depends on a set of subject matter (extralogical) definitions — profits, marginal cost, and marginal revenue.

There are a number of relevant points that can be noted from this example. The conclusion is a logical implication of the assumptions. The language in which the conclusion is derived from  the assumptions is a matter of the theoretician’s choice. In general, there are three languages that have been commonly used by economists for drawing a conclusion from a set of assumptions — ordinary prose, pictorial geometry, and formal mathematics. In the specific theory under discussion, it is obvious that the conclusion can be derived using any of the three languages. It would also, of course, be possible to state the assumptions and the conclusions in any of the three languages. Generally it is most convenient to state assumptions and conclusions in prose alone or in a combination of prose and mathematics. The question of which language to use is answered quite nicely in the  following quotation:

If mathematics is no more than a form of logical reasoning, the question may be asked: why use mathematics, which few understand, instead of logic, which is intelligible to all? It is only a  matter of efficiency, as when a  contractor decides to use mechanical earth-moving equipment rather than picks and shovels. It is often simpler to use pick and shovel, and always conceivable that they will do any job; but equally the steam shovel is often the economic proposition. Mathematics is the steam shovel of logical argument; it may or may not be profitable to use it.

Another point to note is that the conclusion is true only in the sense of logically following from the assumptions. The theory must be tested empirically before it can be said that the theory “proves” anything about the world. As has been said a number of times, it is not possible to “prove” by an a priori ‘ argument that a particular proposition is true of the real world. With most economic theories, unfortunately, testing is difficult, as it is with any nonlaboratory science. One important reason for this difficulty in economics is that for the most part we are dealing with static theories, whereas the world in which we must test the theory is dynamic. As a result, it is usually difficult to find satisfactory data for testing purposes. As we shall argue below, we feel that computer models can reduce the difficulties of developing models that can be directly tested, although some new statistical problems may arise.

An additional point that is relevant to the problem of testing should be recognized about the nature of most economic theories. The point has been effectively made by Professor Samuelson:

The general method (of economic theory) involved may be very simply stated. In cases where the equilibrium values of our variables can be regarded as the solutions of an extremum (maximum or minimum) problem, it is often possible, regardless of the number of variables involved, to determine unambiguously the qualitative behavior of our solution values in respect to changes of parameters.

This means that the testing procedure consists in making  numerical measurements to determine whether the direction of change of certain parameters is in  the predicted direction. In general, economic theory seems more successful in yielding propositions about directions of change than propositions about numerical magnitudes of particular variables.

Source: Skyttner Lars (2006), General Systems Theory: Problems, Perspectives, Practice, Wspc, 2nd Edition.