Etial principle

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Under Ätialprinzip (from Greek : αἰτία / aitia = Cause) refers to a weak, statistical form of a causal principle , may occur when a cause can not be clearly concluded that an effect, but only to a set of possible effects and an associated probability distribution. The term is mainly used in economics.

Explanation and example

A strict, deterministic form of causality is expressed in the sentence "same cause - same effect" : A cube is let go (cause) - it falls down (effect). In this sense, letting go of the cube is causal for its falling.

If you now consider the connection between letting go of the die and the number of points rolled, one cannot speak of causality in the above sense. However, when letting go of an (ideal) die, one will assume that each of the six possible numbers will occur with equal certainty (i.e. equal probability); if the experiment is repeated frequently, each number will be observed in about a sixth of all cases.

This statistical form of causality is described by the so-called etial principle ; it can be formulated as follows: "same general cause - same set of possible effects with associated probabilities" . The term “general causes” is used here because the lack of clarity of the effect may only be due to a vague description of the cause. Describing exactly how the dice is released could possibly give a clear indication of which number will appear.

Origin and use

The term was introduced by Hartwig (Hartwig, 1956) in 1956. For him, the etial principle is a prerequisite for "probability judgment [e] of objective validity".

Outside of the textbooks of economic statistics and econometrics , the term appears rarely. Since no cause-and-effect relationships can be demonstrated purely through statistical studies (a statistically established connection, for example between wage development and economic growth, says nothing about which size is caused by the other and whether one is caused by the other at all), are in the scientific literature Today other concepts of causality, such as Granger causality , are of far greater importance.

The problem of inferring causal relationships from statistical relationships also exists in medicine when clinical studies are to be evaluated. Correspondingly, in the etiology , the doctrine of the causes of disease, questions similar to those presented here arise; the term “Ätialprinzip” is not in use there.


  • H. Hartwig: Natural and social science statistics . In: Journal for the entire political science , 112, 1956, pp. 252–266, JSTOR 40747797
  • Günter Menges: Outline of the statistics. Part 1: Theory . 2nd edition, Westdeutscher Verlag, Opladen 1972, ISBN 3-531-11070-5