According to research performed by Deirdre McCloskey two important econometric terms, economic significance and statistical significance, have begun to become confused through equivocation. McCloskey calls for the distinction of the two types of significance but never gives a definition for what economic significance is. I show that statistical significance is necessary but not sufficient for economic significance by virtue of the fact that statistical significance does not say anything about the world or the natures of relationships. Furthermore, I found that the currently existing definitions of economic significance was too inconsistent for meaningful discussion. To remedy this problem, I create a definition for economic significance: (1) that something is causally related via counter-factual theory proposed by David Lewis, (2) that it is statistically significant, and (3) that it is malleable. Recognizing that few economic factors qualify by my definition I introduce an intermediary term, economic relevance. For a factor to be economically relevant it qualifies for two of the three conditions listed above. This new definition I provide will provide a platform for meaningful discussion on economic significance, and will also prevent equivocation by clearly outlining what economic significance and statistical significance mean.