It always irks me when I read an article about the supposed effect of a policy change, say a gun ban in the UK or Australia, by looking at the effect on some variable (gun deaths, mass shootings, etc.) after the legislation was passed. The problem is that you can mistakenly conclude a causal relationship between the policy and its impact when none exists. It’s the post hoc ergo propter hoc fallacy, “after this, therefore, because of this.”

As an economics major, I learned that you still need a control and treatment group when dealing with time series, just like you would with cross-sectional data. Other majors, I’m sure, were taught the same thing. We’re familiar with the example of a drug trial, for example, where you find two groups of people that are identical in almost every way and give one group the drug (say, to reduce blood pressure). Ideally, if you see the blood pressure levels drop in the treatment group then you’re confident it’s the result of the drug.