Even before toss ups are decided, Democrats are primed to pick
up enough seats to control the House (Map courtesy of 270ToWin, make your own here )
By Rachel Bitecofer at the website "270 to Win"
Rachel Bitecofer is assistant director of the Wason Center for
Public Policy at Christopher Newport University where she teaches classes on political
behavior, campaigns & elections, and political analysis. In her position with
the Wason Center she conducts survey research on public policy issues and election
campaigns. She has been featured in many media outlets such as The Washington
Post, USA Today, Huffington Post, NPR, and she is a regular
contributor on CBC Radio. Her book, The Unprecedented 2016 Presidential
Election (Palgrave McMillan) released in October 2017 and is available via Amazon
and via Springer. A
brief synopsis of the book can be found here.
You can follow her at @RachelBitecofer
and @WasonCenter
The signal and the noise. Election analyst Nate Silver used this
phrase when he released his book The
Signal and the Noise: Why So Many Predictions Fail-but Some Don’t after
he successfully predicted the winner in all fifty states in the 2012 presidential
election. The main lesson from Silver’s analysis of the art and science of statistical
predictive modeling is that the signal is the “truth” and the noise is all that
which distracts us from the truth. The signal, or the truth if you prefer, regarding
the upcoming congressional midterms was cast in stone on November 9th 2016. That
was the day on which the 48.2% of America that voted for Hillary Clinton (and the
roughly 3% of “progressives” that cast protest ballots) in the 2016 presidential
election woke up to face their first day in Donald Trump’s America. Clinton’s loss
and Trump’s victory cemented an enthusiasm gap in favor of the Democrats at least
until 2020, and with the retirement of sometime-swing vote Justice Kennedy, the
Supreme Court is sure to issue judicial decisions that are popular among conservatives,
but jarring to liberals for at least the next decade. This enthusiasm gap has already
produced a
net gain of 43 state legislative and congressional seats for the Democrats in
regular state legislative elections in New Jersey and Virginia as well as in a slate
of special state and federal elections across the country. And it’s important to
point out, Democrats are not just winning the competitive elections. Several of
their pickups come from districts in which the Republicans held double digit advantages
such as Pennsylvania House District 18 or more recently Wisconsin’s 1st state senate
district where the Democrat won that open seat despite the fact that Trump carried
that district by nearly 18
pts over Clinton. Perhaps even more notable, the 1st district contains a 2016
“pivot” county: a county that voted for Donald Trump after voting for Barack Obama
in 2012.
The proliferation of political media outlets such as FiveThirtyEight, The Cook Political Report, RealClear Politics, and Sabato’s Crystal Ball
over the past decade, combined with exponential growth in the polling industry,
has dramatically increased both the coverage of elections as well as the amount
of data available to us to study them. In doing so, they have brought once obscure
theories of electoral behavior formerly consigned to academic journals to the mainstream.
Members of the public who approach me after events or lectures are often well-versed
in political phenomena such as the midterm effect and even in more complex concepts
such as partisan gerrymandering. Much of the research put out by data journalists
resembles, at least methodologically, research published by some of the top political
science journals. Major outlets such as The
New York Times can afford the staff and infrastructure needed to publish
election analysis in real time, and without the time constraints imposed by peer
review.
One byproduct of the contemporary environment is that analysis
relies heavily on assumptions and theories of political behavior, much of which
was produced in the pre-polarized era. Most Americans understand that American politics
has become increasingly
tribal and that the two political parties have grown increasingly
acrimonious over the past two decades via negative
partisanship. Indeed, I often find references to the DW-NOMINATE scores (which have evolved into
Alpha-NOMINATE scores) that allow for unbiased estimates of ideology for each member of Congress
which can be used to compare individual members with each other or to demonstrate
the increase in ideological extremism in the House and Senate over time. Less
well understood are the theoretical mechanisms that have led us to this point. Some
pundits
point to the 1994 Republican Revolution that ushered Newt Gingrich into power as
the starting point for the decline of civility in American politics, but the issues
that fuel polarization reach much further back, to the America that was created
after the passage of the Civil Rights
Act of 1964, the Voting
Rights Act of 1965, the women’s liberation movement; which eventually led
to the Supreme Court’s decision in Roe v. Wade, the imposed
secularization of the country by a series
of Court decisions that limited the influence of religion in the public sphere,
the movements for civil rights for other minority groups such as gay Americans,
and liberalized
immigration policy that expanded immigration from non-European countries such
Asia, Africa, and South America. These changes, combined with the emergence of the
modern media environment and then the internet has profound impacts on American
political culture.
One of the most relevant impacts of these changes to American
political behavior is the phenomenon known as “party
sorting,” which refers to the ideological sorting of conservatives into the
Republican Party and liberals into the Democratic Party. Largely gone are the days
of liberal Republicans and despite some hangers-on, largely in the South and Midwest,
conservative Democrats. Party
sorting left each party ideologically homogeneous and that homogeneity has pushed
out the bounds of the ideological spectrum. Today base voters in both parties believe
in corrupt party “Establishments” and an all-powerful “deep state.” Donald Trump’s
presidency has led to the mainstreaming
of conspiracy theorism among Republican rank and file voters.
So why go into all of this background about polarization in a
post that purports to offer predictions for the upcoming midterm elections? I do
so because a central theoretical tenet serving as the basis for my predictions is
that “this ain’t your granddaddy’s electorate” anymore. That is to say, contemporary
elections are largely driven by the aforementioned negative partisanship. Although
partisanship has always been an important driver of electoral behavior the
influence of partisanship on vote choice is immense in the polarized era. What
matters most to the vote decision is party identification. For most voters, in most
places, and in most elections, even judicial elections, this consideration overrides
all others. Despite the rise of self-identified
Independents over the past few decades split-ticket balloting, which refers
to the decision a voter makes to vote for a presidential candidate of one party
and at least one congressional candidate of another, as well as the number of states
where the winning presidential candidate is from the opposite party of the winning
Senate candidate, has collapsed since the mid 20th century. In 2016, 34
out of 34 states chose the same party for president and senate and in 2016 only 35
House districts of the 435 total districts voted for a presidential candidate
of one party and a House candidate of the other.
One need look no further than the nomination of Donald Trump
by the Republican Party in 2016 to understand how high the stakes of partisanship
of the polarized era affects voter behavior. Despite serious considerations of a
brokered convention and the history-making Never Trump movement,
on Election Day 88%
of Republican identifiers cast ballots for Donald Trump despite the fact that
even Republican voters felt he lacked the temperament or behavior to serve as President
of the United States. This is right in-line with other presidential elections where
about 90% of partisans cast ballots for the candidate of their own party. The same
power of partisanship was displayed again in the special senate election in Alabama
to fill Jeff Sessions’ vacant seat. In that race, Republican primary voters selected
for their nominee Roy Moore,
who had twice been removed from the Alabama Supreme Court by fellow conservatives
for conduct unbecoming a justice and more problematically, for whom credible
allegations of sexual abuse of minors emerged. Yet on Election Day, 90%
of self-identified Republicans still cast ballots for this flawed nominee because
he was the Republican. Republican voters interviewed about their support for Moore
either expressed concerns about the allegations but justified their support by citing
aspects of negative partisanship such as the high policy stakes of the seat going
to a Democrat and general acrimony they held towards Democrats, or more common in
the Trump Era, simply
refused to believe the allegations. This type of behavior in Republican politics
presents a sharp departure from the past, when scandal ended political careers.
The normal laws of gravity still applied to Republican politics
as recently as 2012. That cycle, incumbent senator Democrat Claire McCaskill (MO)
was one of the most endangered incumbent Democrats. Yet, McCaskill ended up winning
reelection handily because Republican voters defected in large numbers from their
party’s nominee Todd Akin after he made widely
mocked claims about the capabilities of the female reproductive system in response
to rape. Akin ended up winning just 79% of Republicans
and lost Independents by 12 points, which produced a 16 point trouncing. Yet
in the same state this year Missouri’s Republican governor Eric Greitens had
to be forced out of office by prosecutors via a plea deal after he refused to
resign over sexual abuse allegations. Although many of Greitens’ GOP colleagues
in Missouri failed to rally behind him, Republican voters in the state largely stood
by their man. At the height of the scandal Greitens
still maintained a 63% approval rating among Republicans largely by relying
on what has become a go-to tactic for the modern, scandal-ridden politician: cast
aspersions on the investigation to get your own party’s voters to question the legitimacy
of the claims against you. So a lot has changed in the last 5 years in terms of
what the electorate is willing to tolerate and that is being driven in part by increasing
hyperpartisanship and polarization in the public, particularly the part of it that
votes, which in recent midterm elections constitutes between 35%
and 40% of eligible voters and in presidential elections, about 55%.
The way we understand the electorate needs to be reexamined for
the polarized era. The traditional view sees the electorate as an ocean that flows
from left to right depending on the movement of Independent voters from Republican
to Democratic party candidates, which is largely predicated on major factors such
as how the economy is performing and whether there are any large, salient issues
moving voters toward one party or the other. Take the aforementioned midterm
effect, for example. The midterm effect is the longstanding tradition of the
president’s party losing seats in the subsequent congressional elections two years
later, midway through the president’s term. The midterm effect is really a referendum
effect and it supposedly measures the amount of “buyer’s remorse” the electorate,
particularly Independents, have after the preceding cycle’s presidential election.
This may well have been the case in earlier decades, when partisans were more ideologically
heterogeneous, Independents fewer in number, and “Reagan Democrats” still roamed
the Earth. But my preliminary analysis of voter files indicates that the modern
midterm effect may be misunderstood. The data suggests that the rise and fall of
the incumbent party’s fortunes may not be driven by the movement of Independent
voters from one party to the other, but instead, by the entrance (and exit) of partisan
voters who are activated or deactivated by negative partisanship. Keep in mind,
midterm elections are low turnout elections. The
2014 midterms produced the worst turnout rates in the modern era, only 36.4%
of eligible voters cast ballots that cycle. And what drives turnout at the margins
in off year and midterm elections is negative
partisanship fueled by being locked out of power in Washington, particularly the
big, white house at 1600 Pennsylvania Avenue.
I’ll come back to this shortly but first I want to explain a
very important, but largely ignored, fact about the American electorate. In many
elections, even competitive ones, Independents are not always the decisive factor
determining who wins and who loses an election. You are likely scoffing at this
claim because it contradicts the way we understand elections but consider the evidence.
Although Barack Obama won the majority
of Independents in his 2008 presidential race (primarily because the economy
was quite literally collapsing on Election Day) he did not
win the majority of Independents in his 2012 reelection bid. Given the conventional
wisdom of elections, such a thing should not be possible. And it’s not just that
he failed to carry Independents nationally, he failed to carry Independents in critical
swing states such as Ohio that he still won. In fact, Obama lost Independents in
that decisive swing state by a staggering
10 points, but he still won the state because the impressive turnout operation
established by the Obama campaign managed to produce an electorate that was 38% Democrat.
And as I show in my unfortunately titled book The Unprecedented 2016
Presidential Election, Democrats lose Independents quite often, and in elections
they win and they lose because they have a population advantage in many places and
when their partisans turn out in high numbers, it trumps the combined loss of Republicans
and Independents, assuming they don’t lose the latter group by wide margins.
The fortunes of the Republican and Democratic parties seems to
rock back and forth every few cycles, creating the appearance of neurotic electorate
that can’t quite figure out what it wants. But what we are really seeing, especially
in the first midterm under a new president, is backlash from negative partisanship
from voters of the party that lost the presidency looking for electoral revenge
coupled with complacency from voters of the ruling party. Out of power partisans
vote because fear is an excellent motivator. Especially the kind of fear that comes
from seeing the opposition party enacting policies you don’t support and stacking
the federal courts with judges with the “wrong” ideology.
Think about it. When we look at the impressive gains made by
Republicans in the 2010 and 2014 congressional midterms, as well as the 1000+ state
legislative seats they gained over the course of the Obama presidency, partisan
gerrymandering only accounts for part of their electoral success. And in the case
of the 2010 midterms, the current district lines that strongly
advantage Republicans in many states are the product of the big gains Republicans
made in state and federal elections, not the cause of it. So the electoral success
of Republicans is more than a story of partisan gerrymandering, which didn’t take
effect until the 2012 election. Instead, much of their electoral prowess over the
past 8 years was largely driven by backlash to Obama and Republican strategists’
success at tapping into this “fear factor” by nationalizing elections. For Republicans,
elections in the Obama era, both big and small, were framed as a referendum on Barack
Obama and Nancy Pelosi. This brilliant messaging, combined with a complacent Democratic
electorate, allowed Republicans to over
perform their share of the electorate by 5 points in the 2010 midterms and 10 points
in 2014 in midterms. It is negative partisanship among opposition party voters
that drives the midterm effect, not movement of independent voters back and forth
between the parties.
This updated theory of electoral behavior led to my successful prediction of the
Blue Wave in the 2017 elections in Virginia (at the 20 minute and 32 minute
marks). All told, we ran 5 surveys on the gubernatorial race between Democrat Ralph
Northam and Republican Ed Gillespie over the course of the general election and
they were remarkably stable, predicting that Northam would win the election handily.
This worried my colleague, who had spent the past decade making a close study of
the Virginia electorate because the elections in 2013 and 2014 had turned out to
be far more competitive than expected. Indeed, this was a reason
the national punditry herded around a close and competitive election the final
week heading into Election Day. But by applying my theory of negative partisanship’s
electoral effects in the polarized era, I
suspected that Ralph Northam’s victory was cemented on November 9th, 2016 when Donald
Trump won the presidency. Trump’s victory created a different Virginia electorate
from the electorates of 2010, 2013, and 2014. Because Democrats lost the 2016 presidential
election, especially considering the way they lost it and to whom, I expected
a turnout surge among the Democratic portion of the electorate and this is exactly
what happened. Despite predictions of a close race by other pundits, Northam ended
up winning by 9%. And he did it by a surge in Democratic Party participation, not
by winning over Virginia’s right-leaning Independents. In 2013,
37% of the electorate were Democrats and in 2017 that percent increased
to 41%, which is enough to turn a average 2-3 point advantage for statewide
Democrats into a 9 point route that also allowed Democrats
to flip 15 House of Delegate seats when even the most ambitious predictions,
including my own, predicted a gain of just 7 or 8 seats due to gerrymandering. The
point I want to hammer home is that the determinate factor driving voter behavior
in this election was negative partisanship because had Hillary Clinton won in 2016,
Virginia may well be currently governed by the Gillespie Administration despite
the growing demographic advantage Democrats hold among the overall population of
the state and the increasing influence of Northern Virginia on statewide election
outcomes.
So let me come back to Silver’s concept of the signal and the
noise. Because of negative partisanship Democrats will have a significant enthusiasm
advantage in turnout in elections so long as Donald Trump sits in the White House.
In places where there are large pools of untapped Democratic voters, the party is
going to win marginal seats as well as some seats that have not been competitive
since at least 2006. Case in point, the special election in Pennsylvania CD 18.
Although the narrative of Connor Lamb’s unexpected victory points to a well-run,
highly funded campaign (it was) and Lamb’s centrist platform attracting Independents
(it did) Lamb’s narrow 1 point victory would not have possible without massive Democratic
turnout. In a largely rural district with an 11 point Republican Party advantage
(PVI)
that Trump carried by 19 points Democrats managed to make up a plurality of the
the electorate, 46%
compared to just 41% for Republicans. And that was driven by large turnout among
Democratic voters in the Pittsburgh suburbs motivated to the polls by negative partisanship
and backlash to Trump.
My analysis of special elections since Trump was elected reveals
that Democratic Party candidates are over-performing Hillary Clinton’s share of
the two-party vote by an average of 7.36 points while Republican Party candidates
have under performed Trump’s vote share by an average of -3.47 for a net improvement
advantage for Democrats of 10.83 points. This advantage is especially pronounced
in two regions of the country: the Midwest (D+ 19.27) and the South (D+13). And
while it is true that low turnout elections such as special elections benefited Republicans over the Obama years, since
the election of Trump, Democrats have flipped 27 seats in special elections and
in these elections the Democrats improved their share of the two-party vote over
Clinton’s share by an average of 13 points, including 45 points in a special election
in Kentucky.
Although statistical analysis informs the predictions I offer
here, it is important to draw a distinction between what I am doing, and the predictions
that are derived from forecasting models. Contemporary midterm forecasting models
do what they do quite well: estimate a range of potential seat gains/losses for
each party by utilizing the highly predictive indicators of generic ballot advantage
and presidential approval to run thousands of election simulations which are updated
constantly with new data to produce a real-time forecast for a range of outcomes
for control of the chamber and overall seat share. New forecasters such as G. Elliott Morris
have built on earlier predictive models by refining their polling aggregators and
introducing some district-specific factors. The predictions offered here does not
endeavor to “reinvent the cart” or even to replicate it. These parsimonious models
have established a long track record of efficiency and accuracy and I expect that
the actual performance of the Democrats on Election Day will closely mirror their
predictions, especially because the models are updated continuously. The future
becomes clearer when it is only a week or a day away. Right now, the advantage for
Democrats on the generic ballot hovers on average around 7 points and produces a
seat gain for Democrats anticipated to be somewhere between 12 and 33 seats, depending
on the forecaster. As Election Day approaches that “cone of uncertainty”will narrow
and I expect the aggregate models will be producing seat gain forecasts closer to
the predictions I offer here.
To arrive at my predictions, I undertook a deep study of the
demographic composition of each congressional district, Democratic Party electoral
performance in elections since Trump’s election, polling I conducted on 4 congressional
districts here in Virginia in March as well as national polls from other outlets,
analysis of the electorate in the 2006, 2010, 2014, 2017, and 2018 elections including
data on primary turnout, and analysis to isolate district-level/state-level predictive
factors affecting outcomes in elections since the election of Donald Trump. My analysis
currently predicts Democrats will pick up 42 House seats as well as holding onto
Senate seats in Florida, West Virginia, Montana, Indiana, and Missouri. My analysis
also predicts that the Democrats will likely pick up the Nevada senate seat, while
Arizona and Texas, (yes Texas) are currently toss ups. The senate seat I predict
is most vulnerable for the Democrats is Heidi Heitkamp’s seat in North Dakota, and
even with
the support she is receiving from the Koch Brothers, this race is currently
coded as Lean Republican. Although many pundits code Tennessee as a tossup, given
the strength of the Republican nominee, the lack of the factors most likely to produce
a surge of Democratic voters, and the lack of any competitive House races, Tennessee
is currently Lean Republican.
I can use the Senate map to further illustrate my point about
the polarized electorate because if Hillary Clinton was currently president the
Democrats would likely lose every one of these races with the exceptions of West
Virginia, where split ticket balloting is still common due to the issue of coal,
and Florida, which would have been extremely tight with two well-known, well-financed
statewide incumbents facing off. With a Clinton Administration the edge in that
race would go to Rick Scott, because Democratic turnout would be lackluster while
Republicans would be galvanized after Trump’s loss and hatred of Clinton. Despite Scott’s considerable assets, flipping
Nelson’s seat this cycle will be an uphill battle because the electorate made him
a two term governor has been replaced by an electorate that will favor Democrats
while Trump is in office. Unfortunately for the Democrats the timing of this wave
falls on the Class 1 map, which structurally restrains Democrats significantly,
even under scenarios where they win the national popular vote by a wide margin.
In terms of the House I am able to identify 12 specific seats
that will flip to the Democrats, most of which are coded as toss up races
by other forecasters. My analysis also produces an additional 12 seats that are
highly likely to flip. Although many of these districts are Clinton districts, not
all are. I include in the list of likely pickups districts like Virginia’s 7th district
and California’s 21st, which aren’t even considered toss ups by other outlets. At
least not yet.
Like with Virginia in 2017, I expect these predictions to be
met with skepticism at this point in the cycle. But when you look at the data, Democratic
Party vote share collapsed between 2006 and 2010 and 2014. Where did all of those
Democratic voters go? Complacency depressed their turnout while Republicans were
highly motivated due to negative partisanship. I predict the 2018 electorate will
look more like the 2006
electorate than the 2010 and 2014 electorates in terms of its partisan composition.
A few percentage point increase in Democratic turnout has a large effect on Democratic
candidates two party vote share. In Virginia Democrats improved their share of the
electorate by 3 points and in doing so transformed a modest demographic advantage
into a wave.
We can learn a lot regarding the potential gains for Democrats
in 2018 by looking back at how Republicans performed in the 2010 midterm. In that
cycle, Republicans not only won 29 of the 40 toss up races, they also won 5 of the
25 districts classified as “Lean Democrat” and even won 2 of the 13 races classified
as “Likely Democrat.” All told the Republicans netted 63 House seats, the difference
coming from a host of districts whose PVIs advantaged Democrats enough that they
were largely left out of consideration as competitive races by forecasters until
the final weeks of the cycle (the
strong performance of my friends over at Crystal Ball in their final forecast
issued on election eve should be noted). Like in 2018 the beginning of the 2010
cycle was marked by a high number of retirements, 37 in the House. But unlike 2018,
retirements in 2010 were fairly evenly split
between the parties: 17 Democrats to 20 Republicans.
Members of Congress are good at anticipating tough electoral environments and Republicans
clearly recognized that 2018 would favor Democrats because of the 65 retirements
this cycle, 46 of them are Republicans. A handful of these retirements are due to
appointments in the Trump administration but 17 of them are either from scandal
or strategic retirements to avoid a loss. Republicans might have learned from watching
the Democrats who stayed in 2010 get shellacked. 52 Democrat incumbents lost election
in 2010 and 14 open seats held by Democrats switched to Republicans while just 1
seat switched to the Democrats. Potential challengers certainly smell blood in the
water. The 2018 cycle brought out an unprecedented number of House candidates powered
by a
record number of female candidates.
Of course, there are key differences between 2018 and 2010. Part
of the reason the Republicans gained so many seats in 2010 is because Democrats
were deeply over extended from their own wave election in 2006 and by additional
gains made from increased Democratic turnout in the 2008 presidential election.
One rationale behind the more conservative seat gain predictions for Democrats in
2018 by other analysts stems from the fact that in the 2010 cycle Democrats had
to defend 40 seats carried by McCain in the 2008 presidential election, but
in this cycle, there are only 25 so-called Clinton Districts. Add to that the partisan
gerrymandering that occurred after the 2010 census and there is no doubt that Democrats
are more structurally constrained than Republicans in 2010. Right now most
of the conversation centers around whether the Democrats can win the 24
seats they need to control the House, not on a wave that will compare in scope
to 2010. But the Democrats have an asset that can do much to negate these structural
disadvantages. In many districts, there are simply more Democrats than Republicans
or in the cases of “red” districts, there are enough Democrats to offset the Republican
advantage if Democratic voters have strong turnout (as seen in PA 18 and a host
of special elections that strongly favored Republicans). In elections where 30-40%
of eligible voters participate, an outnumbered party has a lot of opportunity to
offset their number disadvantage.
Based on my analyses I predict that nearly all, if not all, of
the Clinton districts will, in fact, flip to Democrats. What makes them so vulnerable
is what makes them Clinton districts in the first place. They have 3 elements that
my analysis suggests will be strongly predictive of strong Democratic Party performance
this cycle. One of these factors is the percent of the district that is college
educated because it is from this group that any “pink” surge of college educated
women will come from. The average percent of college educated residents in my 12
“will flip” districts is 43%. And that is the college education rate of the overall
population, it will be much higher among actual voters. Virginia’s 2017 state legislative
elections are a good barometer of a potential pink turnout surge from a highly educated
populace. Of the 17 Clinton districts in Virginia, Democrats won nearly all of them.
They even picked up a seat in a district that broke for Trump. And the most significant
factor explaining districts that flipped from those that didn’t (other than the
district’s partisan advantage and challenger spending relative to incumbent spending)
is the percent of college educated residents residing within the district. In districts
prone to a Democratic surge, Democrats won races they shouldn’t have been able to
win. Another key factor is Trump’s performance in the district, relative to Mitt
Romney’s performance in 2012. In some districts Trump outperforms Romney, but in
other key districts Trump trailed Romney. And what factor accounts for this? The
college education level of the district. In the 12 districts I predict will flip, the average under performance score for
Trump is -8 points. In the 12 “likely flip” districts it’s -6.2 points.
Each of these 24 districts will draw a wealth of investment from
both parties and because of their competitiveness, have produced strong challengers
(this fall I will be adding candidate and campaign quality metrics for the 60 or
so competitive districts to the analysis). I have included ratings from other forecasting
outlets in the table below (in the case of Morris, the predicted probability of
the Democrat winning the district) along with my ratings to serve as points of comparison.
Although we identify similar districts as competitive, there are significant differences
in our ratings. Districts coded here as “will flip” or “likely flip” are largely
coded as toss ups by Cook,
Inside Elections, RealClear
Politics, and Crystal Ball.
Although some of my 12 “will flip” districts display high probabilities of flipping
based on the Morris
scores, others do not. My toss up districts are those districts that are likely
to be competitive, but lack factors that make them susceptible to a surge of Democratic
voter large enough to overcome the either the structural advantage for Republicans
in that district, a strong incumbent, or in some cases both of these factors. Of
particular interest are CA 45 & 48, IL 6, and VA 7 which are seen as Lean or
Tilt R (or in the case of the Morris scores < 50%) by other outlets, but which
are all but certain to flip to the Democrats under my analysis.
The 23 districts coded as toss ups here are coded as toss ups,
lean R or even likely R by other outlets. I don’t anticipate much change in the
“will flip” categories, but the “likely flip” and “toss up” races will be refined
as additional data points become available. One of the key data points will be investment
from the RNC, DCCC, and outside entities. Assuming the Democratic Party can marshal
the resources needed to compete on a wide map, and also assuming that foreign interference
is not a factor, the negative partisanship referendum effect in 2018 should mirror
its strength in 2010 midterms, although the
scope may be limited by the structural disadvantages that will constrain
gains by Democrats. Most analysts agree that Democrats need to win the national
popular vote by at least 6% to make significant inroads towards the majority in
the House and probably by at least 8% to guarantee picking up the needed 24 seats
to control the chamber. Of course, as Hillary Clinton will tell you, it’s not merely
the size of the national vote margin, but how that margin gets distributed that
matters. This is why the Democrats can win the majority of votes and still fail
to make much headway in their seat share. The size of the enthusiasm gap among likely
voters in specific competitive districts around the nation will tell us a lot about
the ceiling for Democrats in November and there will be more public polling of these
midterms than in any midterm in history including polling in Virginia’s 4 competitive
districts by the Wason Center. Based on our initial survey in March, I anticipate
double digit enthusiasm gaps between Democrats and Republicans among likely voters
unless the Republicans decide to hold off filling Kennedy’s vacancy on the Supreme
Court.
I should also point out that there is a significant unknown right
now. How will Independent voters behave in the Trump Era? Although Independents
generally favored Republicans in the 2010 and 2014 midterms history suggests that
Independents are not immune to the midterm effect, particularly when the incumbent
president has low favorability. In the 2006 midterms when George
Bush’s overall favorability was similar to President Trump’s approval rating now
(an average of 40%) the Republicans lost Independents by a stunning 18 points, largely
due to backlash over the Iraq War as the economy was still largely stable at that
point. It is possible that after favoring
Republicans during the Obama Era, Independents will favor Democrats in 2018. The
recent (modest) uptick in Trump’s favorability is being driven largely by Republicans
and right-leaning Independents “coming home” and even among right-leaning Independents
his approval rating still lags, coming in at just 71%. His rating among left-leaning
Independents is virtually equal to Democrats, at 7% and 8% respectively. More telling
may be his favorability rating among “true” Independents Gallup reports a favorability
rating of just 26%. It should probably be noted that Obama spent most of 2010 with
a positive favorability rating, an asset that Trump has never had. Still, that didn’t
stop him from getting hammered on Election Day because negative partisanship drove
Republicans to the polls. If Independents break for Democrats and Democratic
voters surge their turnout this cycle it is possible that even the ambitious predictions
offered here will prove to be too modest. Preferences on the generic ballot among
true Independent, likely voters will be one of the most important data points from
survey data this fall.
I will be refining my predictions over the course of the general
election as more data, including data on candidate and campaign quality become available.
In marginal races I will be examining the electoral strategies deployed by candidates
in specific races and how they might impact results and will share those insights
here. It should also be noted that the predictions offered here are based on the
assumption that Donald Trump will be president on November 6th 2018, no major national
security events occur between now and Election Day, and that Democrats successfully exploit their
advantages. Stay tuned!
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