The 2020 election was unique for a variety of reasons. Chief among them, however, was the false contention from the (losing) Republican camp that they had actually won. In the wake of the election, former president Donald Trump propagated a wave of lies regarding the results and refused to back down on them, making them a centerpiece of his 2022 rhetoric and demanding that GOP nominees echo them.
One question that stuck in the minds of many as a lingering query was just how unpopular election denial actually was, and how much it really mattered. There was little in the way of actual electoral evidence to indicate its salience; neither Glenn Youngkin nor Jack Ciattarelli were aligned with the Trump wing of the party during the 2021 gubernatorial elections in Virginia and New Jersey, respectively, and their overperformances could not be used to discern the salience of the Big Lie in elections.
In the vacuum of actual electoral evidence, people mainly relied on polling. Prominent political scientists circulated surveys pre-election suggesting that large swaths of people did not really care about democracy and preferred to have a “strong leader” unrestricted by an electoral system. But in the wake of the November midterm elections, it is unclear that the hypothesis of “election denialism is electorally acceptable” actually stands up to any level of scrutiny. Across the nation, election deniers appear to have underperformed in salient races.
The first indicator of this is seen in an exercise done by Nate Cohn of the New York Times, where GOP nominees handpicked by Trump underperformed other congressional Republican candidates by 5 points nationally and by 7 points in competitive districts. This is a fairly good proxy on its own for election denial, as the former president often made this position a de-facto requirement for GOP candidates seeking his endorsement, which frequently provided a huge boost in Republican primaries. But it came at a cost in the general election, as Cohn’s data shows.
There is additional evidence that GOP candidates aligned with the Big Lie underperformed, and it can be seen in Secretary of State elections. This office is a statewide one that deals primarily with elections and election handling, and in the wake of 2020, such offices received much more attention, spending, and fundraising given the increased salience of their responsibilities. The results in these elections are broadly consistent with the hypothesis that election denialism is unpopular: examining the results, we see that battleground Secretary of State nominees who denied the outcome of the 2020 election generally underperformed in races regardless of degree of competition.
Split Ticket recently calculated the generic ballot on a statewide level, adjusting for races in which one party lacked a nominee on the ballot. We can use these statewide numbers as a “baseline” to compare Secretary of State performances to. We will categorize the GOP nominees as “election-denying” or “not election-denying” based on FiveThirtyEight’s classification – for the purposes of this analysis, “Refused to Answer”, “Raised Questions”, or “Fully Denied” will be classified as election-denying, on the premise that anything short of openly accepting the results of the 2020 election is tantamount to a denial.
The map below is the partisan overperformance map for the Secretary of State elections. Blue indicates a Democratic overperformance against the generic ballot, while red signifies a Republican overperformance. States with election-denying GOP nominees were marked with the asterisk (*).
The map shows a correlation between election denial and GOP underperformance — 9 out of the 13 election deniers underperformed the congressional ballot. But if we limit our analysis to battleground states (states whose partisan lean was within 10 points of the nation as a whole in 2020), we find something quite telling: Republicans underperformed in every single one of the 5 battleground states with election-denying GOP nominees.
The next question is obvious: Is this correlation, or is it causation? In each battleground state, Democratic nominees fundraised more than Republicans did. But it is not clear that the deltas in spending would cause this degree of underperformance; for instance, 1 million extra in spending typically got you about 1 point in improved congressional margins in 2020, and yet in every single state, the overperformances were far greater than what the spending deltas would suggest. For example, in Arizona, the spending was roughly at parity, but the Republican underperformed the generic ballot by 7 points.
One could possibly point to the gubernatorial nominees being a better baseline for comparison than the congressional nominees, given that this would be a more apples-to-apples comparison between statewide races. Even here, however, our findings hold — the GOP Secretary of State nominees underperformed their party’s gubernatorial nominee in every single case as well. This is especially damning when considering how, in each of those states, FiveThirtyEight’s database shows that the Republican nominee for governor also refused to openly accept the 2020 elections as well. It seems that voters were especially unwilling to entrust control of an election-specific office to candidates who did not accept the basic premise of democratic legitimacy.
It has long been the case that Democrats enjoyed an issue advantage on education and healthcare, whereas Republicans were the more trusted party on economic matters like taxation. But we are hesitant to say that Democrats now have issue ownership on election administration, because in states like Georgia and Ohio, where the Republicans running explicitly accepted the outcome of the elections, the GOP saw massive overperformances in the secretary of state races. Instead, it might just be as simple as this: voters give the issue advantage on election administration to candidates who refuse to undermine the legitimacy of those elections.
I’m a software engineer and a computer scientist (UC Berkeley class of 2019 BA, class of 2020 MS) who has an interest in machine learning, politics, and electoral data. I’m a partner at Split Ticket, handle our Senate races, and make many kinds of electoral models.
CS PhD student and twitter mapmaker. Follow me at @notkavi on twitter.