Multicausality in geometry and economics

Multicausality in dynamic systems theory refers to the fact that emergent outcomes are the product of many interacting forces. Multicausality is sometimes misunderstood as referring to multiple factors. Multiple factors would mean that, e.g., some outcome X is produced by three factors, A, B, and C, with A contributing 20%, B contributing 30%, and C contributing 50% to the final outcome. These are three monocausal processes adding together, not a multicausal process.

An example of multicausality is how the four sides of a square cause the square to exist. Obviously, no individual side of the square causes the square to happen. Nor is it the case that each side contributes 25% to the final square. Instead, the square simply doesn’t exist unless all four sides are present.

Instead of thinking of the square as an event to be caused—as a particular thing that has to be made to happen—it can be thought of as a situation that we recognize. The square situation doesn’t exist without all four sides in place. That’s multicausality.

In economics, the classic example of multicausality is the reciprocal nature of externality. An external is a “neighborhood effect”, like your neighbor throwing loud parties at night while you’re trying to sleep. It might seem like your neighbor is the one making the externality happen, but the noise their parties produce isn’t an externality unless you’re present to be annoyed by it—that’s what it means for externality to be reciprocal. Externality isn’t an event, it’s a situation, and it takes both parties to be present for the situation to exist.

Multicausality is relevant for understanding development, whether of form, behavior, or cognition, because development is a situation, not an event. An adult human is an assembly of parts that we recognize as a grown person, not a caused actuality as such. Such phenomena are inherently multicausal because we only recognize them, or categorize them as such, when many elements are in place.