CORRELATION AND CAUSATION

Correlation analysis helps us in determining the degree of relationship between two or more
variables --- it does not tell us anything about cause and effect relationship. Even a high degree
of correlation does not necessarily mean that a relationship of cause and effect exists between
the variables or, simply stated, correlation does not necessarily imply causation or functional
relationship though the existence of causation always implies correlation. By itself it establishes
only co variation. The explanation of a significant degree of correlation may be any one, or a
combination of the following reasons:

1. The correlation may be due to pure chance, especially in a small sample.

We may get a high degree of correlation between two variables in a sample but in the universe there may not be any relationship between the variables at all. This is especially so in case of small samples. Such a correlation may arise either because of pure random sampling variation or because of the bias of the investigator in selecting the sample. The following example shall illustrate the point:

The above data show a perfect positive relationship between income and weight, i.e., as the
income is increasing the weight is increasing and the rate of change between two variables is
the same.

2. Both the correlated variables may be influenced by one or more other variables.

It is just possible that a high degree of correlation between the variables may be due to the same causes affecting each variables or different causes affecting each with the same effect. For example, a high degree of correlation between the yield per acre of rice and tea may be due to the fact that both are related to the amount of rainfall. But none of the two variables is the cause of the other.

3. Both the variables may be mutually influencing each other so that neither can be designated

as the cause and the other the effect.

There may be a high degree of correlation between the variables but it may be difficult to pinpoint as to which is the cause and which is the effect. This is especially likely to be so in case of economic variables. For example, such variables as demand and supply, price and production, etc., mutually interact. To take a specific case, it is a well known principle of economics that as the price of a commodity increases its demand goes down and so price is the cause and demand the effect. But it is also possible that increased demand of a commodity due to growth of population or other reasons may exercise an upward pressure on price. Now the cause is the increased demand, that effect the price. Thus at times it may become difficult to explain from the two correlated variables which is the cause and which is the effect because both may be reacting on each other.

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