Background
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What is the research about?

Economic interrelations and connections are extremely complex and complicated. In addition, universal laws do not exist, as they do in natural sciences. Hence, economic forecasts and theories are usually shaped by an ideological position.

A new generation of scientists is trying to decouple ideology and “standard theories” from the analysis of economic systems. Instead, they use computer simulations to model the complex interactions. The advantage of this approach is that they can model the “molecules” (e.g., people, companies, etc.) of the system on a very low level with rules that are more or less commonly accepted (e.g., people who loose their job will look for a new one).

With this approach, they hope to gain “ideology-free” insights into the mechanisms behind economies.

 

How does simulation help?

Simulations can be applied in areas with universal rules (e.g., electric systems) but also in systems with unclear rules (such as an economy). The challenge in the latter is to use an adequate modeling approach that can be fed with the (mostly limited) information available.

Here, the scientists chose to build a model on the basis of the stakeholders. The advantage of that is that these agents act according to simpler rules (e.g., a company with losses will fire people, take out a loan or fail). These rules are less disputed than many of the “grand economic theories”. Hence, it can be argued in favor or against the model without entering the rational of common economical ideologies.

 

What is the outcome?

The model shown is a simplified version of the real model used by the international research consortium. The main reason for this is the model’s complexity: several hundred parameters need to be specified. Such complex systems can be very sensitive to certain changes: they unpredictably loose stability beyond given points. Therefore, such models must be run by scientists with in-depth knowledge on the matter in order to obtain sensible results.

Nevertheless, this simplified, easy-to-be-controlled model, still depicts the results of the original one.