Is the economy complex or merely complicated?
The methodological approach of mainstream economists largely involves seeing an economy as either in a state of equilibrium or in a state of striving to reach an equilibrium. Economists analyse factors and chains of effect that enable an economy to adjust, moving from one equilibrium to the next. Their forecasts are predominantly based on the assumption that the chains of effect they have supposedly identified will continue in the same way.
This methodology is rooted in a scientific tradition, which can be called a so-called “modern view of the world” in the spirit of Max Weber. “This is typified by rationalization, which means … the knowledge or belief that if one but wished one could learn [a rational explanation] at any time [and] … one can, in principle, master all things by calculation” (Weber 1948:139) *). In principle, it is the assumption that there is a rational explanation for everything that was previously unclear and, furthermore, that the previously unclear is calculable. If economic realities do not match the results of a model, it is because the model has not yet succeeded in capturing the complicated economic interdependencies in their entirety. The logical consequence is therefore that the parameters of the model only have to be redefined to more effectively capture the economy. The fundamental validity of the models themselves, however, is not questioned.
This way of thinking, termed “deterministic”, is borrowed from classical physics, which assumed that scientific principles are determined by clear physical laws. Providing that there is complete information about the status of a system at a given point in time, the status of a closed physical system is therefore predictable at any time in the future. According to this view, the quality of statements concerning the future depends largely on how precisely we comprehend the present.
In natural sciences, researchers have understood for a long time that things are not quite as simple in reality, as shown by the development of quantum physics, for example. Beyond this, research work conducted by mathematicians such as Benoît Mandelbrot in past decades has resulted in the so-called “chaos theory”. It has revealed that not only a large number of interrelationships in natural sciences are not linear, but also social interrelationships in particular. It appears that the economy should be seen as a “complex adaptive system“, a term developed a couple of years ago by the Santa Fe Institute, a predominantly interdisciplinary research institute. Complex adaptive systems are made up of several related elements, whose interdependencies can not be clearly determined due to the interactive nature of their relationships. Furthermore, they are adaptive because they can adapt to their environment and they are therefore able to learn from experience. As a result of these two factors – their interactivity and ability to learn – complex adaptive systems produce surprises. And this makes them completely incalculable and very unpopular with researchers.
Even if a researcher has identified the economic interdependencies to date, it does not mean that these will recur in the same way in the future. They can change on an ongoing basis because the economy is “adaptive”. An example of this is the Phillips curve, which was established in the 60s. It described the empirical relationship between inflation and changes in employment. Based on this graph, economic policy could combat unemployment by inflating the economy. Unfortunately, however, this relationship was based on the assumption that trade unions suffered from money illusion and, therefore, failed to identify the negative impact of inflation on real wages. As soon as they had learnt to understand the impact of inflation, they “adapted” by demanding higher nominal wages with expected inflation already factored in. And, as a result, inflating the economy no longer had an impact on employment.
The financial market, in particular, has proved to be a complex adaptive system, which is why the methods of mainstream economists have failed to grasp it time and time again. The actors on the market are very interactive, adapting their actions according to their experience relatively quickly. Behaviour patterns therefore shift permanently and this constantly gives rise to surprises, which have made economic models seem absurd on several occasions.
Classical microeconomics is hardly affected by the paradigm shift from the equilibrium economy to an understanding of the economy as a complex adaptive system. It focuses on interactions that are largely straightforward on markets with a limited number of actors. In complex micro-economic situations, such as oligopolies, game theory provides credible explanations.
The impact on mainstream macroeconomics, on the other hand, is significant. Its foundations have been challenged by the paradigm shift because all of its statements are based on the assumption that interactions between economic aggregates will continue with the same pattern as before. A large number of well paid scientists and economic research institutes are not about to jeopardize their existence by admitting to why economic models have a low success rate. Indeed, the failure to incorporate a sufficient number of parameters is not the only reason, but also the fact that economic models are basically not able to sufficiently capture economic relationships.
To be continued tomorrow.
*) = Weber, Max (1948): Science as a vocation. In: Gerth, H.M.C.W. (ed.), Weber, Max: essays in sociology, Routledge & Kegan Paul. London pp. 129-56.