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To determine if a causal loop is reinforcing or balancing, one can start with an assumption, e.g. "Variable 1 increases" and follow the loop around. The loop is: reinforcing if, after going around the loop, one ends up with the same result as the initial assumption. balancing if the result contradicts the initial assumption.
Fig. 1: Causal loop diagram. In system dynamics this is described by a circles of causality (Fig. 1) as a system consisting of two feedback loops. One is the balancing feedback loop B1 of the corrective action, the second is the reinforcing feedback loop R2 of the unintended consequences. These influence the problem with a delay and therefore ...
Judea Pearl defines a causal model as an ordered triple ,, , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U ...
Causal loop diagram of a model examining the growth or decline of a life insurance company. [15] The figure above is a causal loop diagram of a system dynamics model created to examine forces that may be responsible for the growth or decline of life insurance companies in the United Kingdom. A number of this figure's features are worth mentioning.
A vicious circle (or cycle) is a complex chain of events that reinforces itself through a feedback loop, with detrimental results. [1] It is a system with no tendency toward equilibrium (social, economic, ecological, etc.), at least in the short run.
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.
A system archetype is a pattern of behavior of a system.Systems expressed by circles of causality have therefore similar structure.Identifying a system archetype and finding the leverage enables efficient changes in a system.
A causal diagram consists of a set of nodes which may or may not be interlinked by arrows. Arrows between nodes denote causal relationships with the arrow pointing from the cause to the effect. There exist several forms of causal diagrams including Ishikawa diagrams, directed acyclic graphs, causal loop diagrams, [10] and why-because graphs (WBGs