Back in January, I wrote an article on the elections in the US. In this blog post, I analyzed the reasons why ex-president Trump had lost the electoral battle of Pennsylvania (which eventually cost him his presidency). So the question needs to be asked: why did I decide to make such a research in the first place? Well, there were two fundamental reasons behind this decision. 

First, the last year was full of events that had been influencing the mood of American citizens throughout the year. Surely, those events affected their choice in voting too. It was especially interesting to observe the results in the Swing States, where Joe Biden had managed to win. Second, I wanted to find hidden patterns and discover why the eventual outcomes in many states have changed compared to 2016. Are those changes representing a short-term trend? Or are they all related to the massive turmoil in American society?

And finally: why Pennsylvania, though? Well, it’s one of the key states in the USA. In addition, the Secretary of State made publicly available intermediate results and totals, and it turned out that Pennsylvania represents a sort of an “average” state in terms of income and educational level. Therefore, we assumed that the revealed patterns in this state could be applied to the whole country.‍

The Process

Here’s what I and our Akveo team of analysts did. We analyzed the poll results in Pennsylvania as a whole and each county, respectively. Then we studied the difference from 2016. In our research, we considered the following indicators:

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1. The total turnout by the state and for each county (the ratio of voters to the total number of eligible citizens, and the ratio of voters to the number of registered voters).
2. The total number of votes and the percentage of margins for each county's winning candidate compared with 2016.
3. The absolute value of the margin between candidates for each county.