This post originally appeared on Decision Desk HQ, but the link to the article there is broken so I’m re-posting it here.
One of the strongest forces in state level elections has been the nationalization of the vote. Presidential and senate election outcomes have become increasingly correlated in the last decades. The phenomenon of “straight-ticket voting” has sprouted from this, as voters have grown more likely to choose the candidates of the same party all the way down a general election ballot.
By one analysis, straight-ticket voting in terms of presidential and senatorial vote reached an apex in 2016, with no state splitting their vote for these offices for the first time ever. New Hampshire proved symbolic of this year’s this trend. In the race for president, Hillary Clinton garnered 46.8 percent of the vote to outlast Donald Trump’s 46.5. Two races down the ballot, Maggie Hassan (48 percent) barely edged out Kelly Ayotte (47.9) in one of the most expensive and competitive campaigns of the season. That makes for just a 0.2 percentage point difference in the margins of these two races—a telltale sign of the nationalization of the senate election.
But this trend toward nationalization does not necessarily extend to the other key election sometimes on the ballot—the gubernatorial one. Results in state governorship races are much less linked to presidential voting than those in senatorial races are, and 2016 bore this out very clearly. New Hampshire, in fact, had the smallest gap in presidential-gubernatorial voting in the country in terms of Democratic margin (2.6 points). But in such a close party divide across the entire ballot, that proved enough to flip the outcome: while a Democrat won the presidential vote in the state, a Republican in Chris Sununu won the governorship (49 to 46.7 over Democrat Colin Van Ostern). 7404 fewer people cast votes in the gubernatorial election than in the presidential one, but Sununu was able to collect 8250 more votes from New Hampshire residents than Trump did. That begs the following questions: how did this divergent result come about, where did Sununu run ahead of Trump, and where are the indications of split-ticket voting?
To speak to some of these topics, I collected vote totals for 302 townships and wards that make up larger townships available from the New Hampshire Secretary of State Website. I cut that down to 241 townships, matching the same total that recorded data in the 2012 presidential election. I’ll be examining vote shares and margins from the Republican point of view—for Trump, Ayotte, and Sununu.
Republican Vote across the Ballot
To start things off, below are two graphs comparing how closely the presidential vote was matched up with the senatorial and gubernatorial vote. Points correspond to a township, and size of the points corresponds to number of presidential votes cast in that town. Points that fall above the 45-degree red line indicate where Trump ran behind Ayotte/Sununu, and points below the line show where he ran ahead. If they had the same vote share in each township, all points would fall on this line—the further a town is from the line, the greater discrepancy in vote. Nine and seven town points are omitted for the Sununu and Ayotte comparisons, respectively, because they fall outside the scale range of the graphs. However, their exclusion makes little difference in the visualization.
Of the 241 townships in New Hampshire that recorded votes, Trump won 149 of them, Ayotte won 145 of them, and Sununu won 151 of them. As it relates to the above graphs, Sununu gained a greater share of the vote than Trump in 113 towns (47 percent of them), and Ayotte received higher support than Trump in 123 towns (51 percent). However, township size helps explain why Sununu won fewer towns but still got more of the vote. I’ll go deeper into this later, but as seen with the township sizes (and the five towns with the highest number of votes cast that are labelled), these graphs begin to show that Sununu did better in more populous parts of the state.
While not too different in terms of where each township falls on both graphs, one thing is clear: Trump support is more correlated with Ayotte support (0.85) than it is with Sununu support (0.80). Township points are a bit further off the red line for Trump vs. Sununu. Similarly, Trump and Ayotte’s margins for each township are more correlated (0.90) than Trump and Sununu’s are (0.85). This all begins to show the greater dissimilarity in presidential-gubernatorial, enough of a difference to let Sununu win and Trump lose.
Conflicted Townships
With the senate and presidential races more correlated and both going blue in the Granite State, that leaves the bigger divide between the governor and presidential races as the greater point of interest. To home in on the biggest town discrepancies in the governor and presidential elections, below are two tables, the first showing the 14 towns where Sununu beat out Van Ostern and Trump lost to Clinton, and the second showing the 12 towns where Trump won but Sununu lost. The key columns here are the fifth ones over—how many percentage points Sununu and Trump ran ahead of one another. The “Presidential Votes Cast” column isn’t the same as the number of votes in the gubernatorial election, but still signifies the number of voters in a township.
Given that Dixville only has seven votes, there’s not much to make out of the Sununu-Trump difference there. The biggest difference in support of the two Republicans in Sununu’s favor outside of Dixville comes in the town of Newfields, where Sununu garnered 58 percent of the vote but Trump only gained 41.8 percent of it. Clinton got 53.2 percent of the vote here, so there’s clearly some split-ticket voting going on here.
Outside of Dixville, many of these townships in which Sununu won/Trump lost carry a common theme: they are largely located in the southeastern and southern portion of the Granite State. 12 of the 15 towns in the table are located in either Rockingham or Hillsborough Counties, both of which share a border with Massachusetts. This regional population exhibits much higher educational levels, one of the strongest predictors of voting against Trump among whites across the entire US, and higher income levels relative to the rest of the state. It also contains a smaller population native to the state, with its residents moving from surrounding, more liberal states such as Massachusetts at higher rates. By contrast, as seen in the second table, the towns in which Trump ran ahead of Sununu were located primarily outside of the two aforementioned high-socioeconomic counties with a southern border—such as the townships of Bridgewater, Webster, and Whitefield.
Here’s another perspective on what these tables indicate: for towns where Trump won/Sununu lost, there were 605 total people who voted for Trump but non Sununu. In places where Sununu won/Trump lost, 3047 people refused to vote Trump but still cast their ballot for Sununu. There were split-ticket areas that favored both of these Republicans more than the other, but towns that favored Sununu were greater in population—as seen in the votes cast column—and had residents who likely split their tickets in greater margins against Trump (Sununu % Pts. Ahead in the first table were greater than Trump % Pts. Ahead in the second table). In the end, that helps explain why the presidential victor was blue and the gubernatorial one was red.
Population and Sununu Outperformance
The point regarding population is another key one to understanding the presidential-gubernatorial split in New Hampshire. In townships with more people casting votes—a good proxy for population size of an area—there were indications that Sununu ran ahead of Trump. Non-rural areas with greater populations represented the type of landscape in which Trump suffered the most across the entire country, and a similar trend seems to materialize in New Hampshire as well.
I computed several measures to get a sense of Sununu outperforming Trump, and one of them was called “Sununu Raw Net Votes Ahead.” It sounds a little convoluted, so here’s the formula I used to calculate this metric for each town:
- Sununu Raw Net Votes Ahead = (Sununu total votes – Van Ostern total votes) – (Trump total votes – Clinton total votes)
This quantifies how much Sununu ran ahead of Trump in terms of raw votes and relative to each candidate’s respective opponent. The y-axis of the below graph represents this metric, while the total presidential votes cast—again, getting at how populous a town is—is on the x-axis. Points that fall above the dotted line are towns in which Sununu ran ahead, while points below are places where Trump ran ahead. As the graph notes, towns labelled in red are ones both Trump and Sununu won, blue represents those where both lost, and purple correspond to towns Sununu won but Trump lost.
These two variables are fairly related, with their correlation coefficient at 0.62, and the figure bears the relationship out. Relative to their competitors, Sununu picks up a lot more raw votes than Trump does in several townships with high amounts of voters.
The use of raw votes here—rather than percent shares—is important to illustrate that a big part of Sununu winning and Trump losing in New Hampshire was what happened in more populous towns, and especially Clinton-leaning ones. Sununu lost a lot less ground than Trump did in some blue populous areas—Nashua, Manchester, Dover—in a losing effort, and even won some of these towns that Clinton won at the presidential level—Hampton, Amherst, and Stratham.
The two Granite State towns with the largest overall population swung had a big role in this process: in Nashua, Sununu gained 2202 raw net votes on Trump, and in Manchester, he gained 1205 raw net votes. Notably, both townships still went Democratic in the presidential and gubernatorial races—many Clinton voters still voted Sununu—and both towns are located in Hillsborough County, where residents have relatively higher socioeconomic levels. Two more strong Democratic towns in Portsmouth (+1594 raw net votes for Sununu) and Hanover (+1484) contributed a good amount to Sununu running ahead, as well as one Republican-leaning township in Bedford (+1859). Once again, all three of these places exhibit higher SES levels than in much of the rest of the state.
Ultimately, Sununu capitalized on these vote-rich and higher socioeconomic areas, flipped the town-level vote preference to Republican from Democratic in the presidential race in some cases, and likely split many individual ballots along the way. Trump ran behind Sununu in more populous towns, losing too many raw votes in the process. As a result, a party split in New Hampshire’s presidential and gubernatorial preferences emerged out of Election Day.
Agadjanian Politics 