The notion of causality can refer to the link between a cause and its effect.
Causality is the beginning or origin of something. The concept is used to name the relationship between a cause and its effect , and can be used in the field of physics, statistics and philosophy.
Physics holds that any event is caused by another event before it . Therefore, if you know precisely the current state of something, it is possible to predict its future. This position, known as determinism, was qualified with the advance of science .
Causality in philosophy, statistics and popular wisdom
According to the principle of causality , every effect always has a cause. The principle of uniformity adds that, under identical circumstances, a cause always produces the same effect.
For philosophy , causality is the law by virtue of which effects are generated . Philosophers consider that the fact of any event is caused by a cause and point out three conditions for A to be the cause of an effect B: A must occur before B, whenever A occurs, B must occur, and A and B must be close in time and space.
Statistics , for its part, maintains that causality is a relationship of need for co-occurrence of two variables.
The notion of causality is also present in popular wisdom or informal knowledge. Several proverbs spread this idea, such as “you will reap your sowing” or “he who sows winds reaps storms.” These phrases are not linked to scientific or factual facts, but rather have their value in the belief that people's behavior inevitably has its consequences.
Causality also appears in popular wisdom, as in the case of the expression "You will reap your sowing."
Granger test
Clive WJ Granger, an economist born in 1934 in Great Britain and winner of the Nobel Prize in Economics in 2003, was the author of a statistical hypothesis test whose objective was to determine whether a time series (also called chronological , is a sequence of data) served to predict another.
Generally, statistical regressions ( a phenomenon by which an extreme measurement tends to approach the mean after a second observation), reflect mere correlations, but Granger assured that causality in economics could be shown through some type of test.
It is worth mentioning that, since true causality is a deeply philosophical issue, experts in econometrics (a branch of economics that uses various statistical and mathematical resources to carry out analysis, interpretations and predictions about economic systems) maintain that the Granger test it can only return predictive causal information .
The test, which allows us to find out if a variable can offer useful results to predict the value of another, provided that its character is unidirectional or bidirectional, requires the comparison of the present behavior of a time series to predict the behavior of a time series Y. If the result is positive, it can be said that the result X causes the result Y in the Granger sense, and its behavior is considered unidirectional .
If, on the other hand, everything stated in the previous paragraph takes place, and the fact that result Y allows predicting result X is added, then we are faced with the presence of bidirectional behavior: both results cause each other.
Limitations of this hypothesis to analyze causality
Granger causality has certain limitations , since it is not true causality . For example , if both that is, the opposite). However, manipulating one of them would not show any change in the other.
Simply put, the Granger test was designed to treat pairs of variables, so using three or more can provide confusing results.