Statistical mechanics of complex economies

TL;DR

This paper models complex economies using statistical mechanics, revealing a phase transition where economies collapse if the number of primary goods or technologies drops below a critical point, highlighting risks of excessive complexity.

Contribution

It introduces a large random economy model within General Equilibrium Theory, showing a phase transition and potential collapse due to increasing complexity.

Findings

Economies undergo a phase transition leading to collapse when complexity exceeds a threshold.

The Industrial Revolution may represent a phase transition in economic complexity.

Overly complex economies risk collapse if too many intermediate goods are added.

Abstract

In the pursuit of ever increasing efficiency and growth, our economies have evolved to remarkable degrees of complexity, with nested production processes feeding each other in order to create products of greater sophistication from less sophisticated ones, down to raw materials. The engine of such an expansion have been competitive markets that, according to General Equilibrium Theory (GET), achieve efficient allocations under specific conditions. We study large random economies within the GET framework, as templates of complex economies, and we find that a non-trivial phase transition occurs: the economy freezes in a state where all production processes collapse when either the number of primary goods or the number of available technologies fall below a critical threshold. As in other examples of phase transitions in large random systems, this is an unintended consequence of the growth in complexity. Our findings suggest that the Industrial Revolution can be regarded as a sharp transition between different phases, but also imply that well developed economies can collapse if too many intermediate goods are introduced.