Discussion – Mistaken correlations and excluded factors There are many cases whe

Discussion – Mistaken correlations and excluded factors
There are many cases where a correlation is found between two variables, either via a correlation calculation or a simple linear regression, such as we learned in Ch. 12. Sometimes one can find other evidence that supports causation. But, often, the correlation is coincidental. It may be that factors that were not included in the analysis may have affected the results. In most economic regression studies, many variables are included to control for such factors that may affect the correlation between the two main variables of interest. Unfortunately, in this class, we only have time to learn about regression analysis using a single independent variable. Of course, this may not tell the whole story.
The book, Freakonomics, gives a number of examples of seeming causations that don’t hold up when other factors are taken into consideration. You can find several examples by doing a quick search on the Freakonomics website on “causality.” (https://freakonomics.com/?s=causation) Here’s a recent example from an LA Times op-ed (https://www.latimes.com/opinion/story/2019-07-23/guns-state-laws-suicide-rates) that started with an unexpected correlation between suicide rates and taxes. Your assignment for this discussion is to find a report of a causal relationship (maybe even something you’ve found in your own statistical research report, or searching through the Freakonomics site) and consider whether there is actual causation or if this correlation may be affected by other factors. What other factors might those be, and how are they affecting the original correlation finding?

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