A recent analysis of the 2018 Congressional election found that Medicare for All support hurt Democrats. The model used to show this was simple, including only the 2016 Presidential results, the total funding for each candidate and if there was a Republican incumbent or not, in addition to whether the Democrat supported Medicare for All. If we want to make decisions for what candidates should do in 2020 based on 2018 results we need to be certain that we’ve found a real relationship. Predicting what you should do based on observational data is a tricky business. It becomes even more tricky when you are dealing with strategic actors. We might have a few questions: Who endorsed M4A? What sort of districts were they running in? What sort of media coverage was there on M4A during the race? All of these could affect the relationship between supporting M4A and winning an election.
To test this we collected data on the two-way 2018 returns, the 2016 Presidential two-way vote share, funding for each candidate, spending by outside groups in the district, whether a candidate supported M4A, whether an incumbent was running, and if there were any candidate scandals during the race. In addition, we obtained data on media coverage of M4A in each district from Deck[1]. You can find the code and data for everything here on github. Here, we use the National Nurses Union coding, to replicate the analysis that Abramowitz originally published. However, our analysis of these data suggests that it does not accurately reflect Medicare for All support. Future blogs will discuss our findings there.
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