ceteris paribus

Definition of ceteris paribus

Etymology

New Latin cēterīs, the ablative plural of cēterus ("the other"), + pāribus, the ablative plural of pār ("equal"). Literally meaning "with other [things] being equal" or "other things being equal".

Adverb

cēterīs pāribus

1. other things being equal; with all other things or factors remaining the same.

Synonyms

• cet. par.
• c.p.
• all else being equal
• all else the same

Usage notes

• Used when comparing something to something else that is different in some way but required to be the same in all other ways for the comparison to work.

Further reading

Cēterīs paribus is a Latin phrase, literally translated as "with other things the same," or "all other things being equal or held constant." It is commonly rendered in English as "all other things being equal." A prediction, or a statement about causal or logical connections between two states of affairs, is qualified by ceteris paribus in order to acknowledge, and to rule out, the possibility of other factors that could override the relationship between the antecedent and the consequent.[1]

A ceteris paribus assumption is often fundamental to the predictive purpose of scientific inquiry. In order to formulate scientific laws, it is usually necessary to rule out factors which interfere with examining a specific causal relationship. Under scientific experiments, the ceteris paribus assumption is realized when a scientist controls for all of the independent variables other than the one under study, so that the effect of a single independent variable on the dependent variable can be isolated. By holding all the other relevant factors constant, a scientist is able to focus on the unique effects of a given factor in a complex causal situation.

Such assumptions are also relevant to the descriptive purpose of modeling a theory. In such circumstances, analysts such as physicists, economists, and behavioral psychologists apply simplifying assumptions in order to devise or explain an analytical framework that does not necessarily prove cause and effect but is still useful for describing fundamental concepts within a realm of inquiry.

References

1. Schlicht, E. (1985). Isolation and Aggregation in Economics. ISBN 0-387-15254-7.