What is Causality

This concept shows a relationship between two events where one event is affected by the other. Statistically, if one variable, increases or decreases as a result of other variable, then there is causation exists.

It is the method used in time series econometrics where the short run interplays among two or more variables are studied. In a two variable model Granger causality test is run but in a VAR model Wald test is applied to test for causality.

The method that is used to whether an independent variable predicts the dependent variable’s further values or not.

Given a relationship between two or more variables, it looks the relationship between cause and effect or what variables cause what.

The relationship between a cause and an effect.

The association between two events or states such that one generates or brings about the other, where one is the cause and the other its effect.

Causality (also referred to as causation, or cause and effect) is the agency or efficacy that connects one process (the cause) with another process or state (the effect), where the first is understood to be partly responsible for the second, and the second is dependent on the first.

Causality (also referred to as causation, or cause and effect) is the agency or efficacy that connects one process (the cause) with another process or state (the effect), where the first is understood to be partly responsible for the second, and the second is dependent on the first.

To give statistically significant information on a time series values about the future values of another time series.

The relationship that exists between two factors and show a cause and effect; one factor that because it occurs causes a second factor to always occur and can be predictive.

A term to describe cause and effect. Several types of causality are recognized: linear (x causes y and a doubling in x causes a doubling in y), circular (x causes a change in y which in turn causes a change in x), recursive (x is caused by the system that is x – society is made of people that bear children that make up society), nonlinear (as opposed to linear the change in x causes a change in y that follows a power law, for example).

If a time series is said to cause, or lead, another time series in the short run, or vice versa, there exists a causal relationship among the series, meaning that these time series affect each other in the short run.

The causal relationship between two variables.

It is a time series econometric method of testing directions of cause and effect between two or more variables.

In QCA, the influence of condition variable values to define the prescribed outcomes of cases.

Causality is a complex issue within the social sciences, and it is necessary to verify a causal relationship and not just a correlation between two variables.

Causality is the relation between a cause and its effect or between regularly correlated events or phenomena.

The cause-effect connection between X and Y. While X causes Y, if Y doesn't cause X, causality is called one-way causality from X to Y. The situation of causality relationship both from X to Y and from Y to X is expressed as two-way causality. The situation where X does not cause Y and Y does not cause X is expressed as independence.

Refers to the interrelationship of cause and effect indicating a causal relation between two events. In social sciences, the term causality often indicates a causality association or causality assumption as (mono-)causal and quantifiable relations between two events can hardly be identified.

The relationship between two variables that one of them is the reason of the other.

Refers to the relationship between cause and effect, where one event (the cause) leads to another event (the effect).