Difference Between Correlation and Causality

In economics, it is of great importance to know what is correlation and what is causality. Also the great difference between them, given that they are two words of the statistical language that are widely used today in the news.

The lack of knowledge or confusion between correlation and causality can lead to a misunderstanding of what they are telling us. Even the media can use these terms with the intention of confusing us. We must remember this phrase, since later it will make sense: correlation does not imply causality.

Conceptual Difference Between Correlation and Causality

We are going to introduce the terms, explain them and differentiate them through two examples:

  • Causality: According to the RAE it means: "Cause, origin, principle". It is a word that is used to establish a relationship between a cause and an effect. That is, it refers to the reasons that originate “something”. For example, if you touch fire, it causes a burn.

There is a causal relationship, since it is something that happens unequivocally and that is proven, touching fire always burns you.

  • Correlation: According to the RAE it means: "Correspondence or reciprocal relationship between two or more things or series of things." In this case, the relationship established is one of simple correspondence or similarity, not of origin. For example, there is a correlation between the number of churches in a city and the number of alcoholics in that city.

It may have even shocked you to read the previous sentence, because it is true! Even if you don't think wrong, I have said that there is a correlation, but at no time have I said that one thing causes the other. In this case, there would be behind a third variable not considered in my sentence that is correlated with the two and that would be the explanatory variable. I'm talking, of course, about the amount of population in that city, the more the population, the more churches and the more population, the more alcoholics. See linear correlation coefficient

Therefore we have seen that they move in the same direction and therefore there is a correlation between the two things, but the fact that there are more churches does not imply that there are more alcoholics.

Through this last example we have been able to clearly see the difference between the two terms and that correlation does not imply causality.

There may be correlation and chance

Correlation may also exist by chance. This is by sheer coincidence. As can be seen in the graph shown. The graph compares sales in millions of dollars of organic food, with the number of people diagnosed with autism. The two increase together, so there is a correlation, but there is no cause that unites them.

The theoretical and practical lesson of this difference teaches us to be careful when learning to interpret the data. Not always that there is correlation, it will mean that one variable causes the other. Thus, it is important to understand very well the difference between correlation and causation. This will help us not to make mistakes when carrying out studies or investigations.