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KAMALA HARRIS WILL WIN THE POPULAR VOTE  
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Michael Podhorzer
September 26, 2024
Weekend Reading
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*
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*
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*
*
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_ Sadly, the same cannot be said with confidence for the Electoral
College battleground states. Harris needs the kind of high turnout
from contingent new voters that pushed Biden over the top (barely) in
those states. _

,

 

Absent an extraordinary upending event, _KAMALA HARRIS WILL WIN THE
NATIONAL POPULAR VOTE ON NOVEMBER 5TH._ I’m confident of that not
because she is ahead in the polling averages, or because of a
“forecast,” conventionally conceived. 

I say it because _IN THE MAGA ERA THE BEST PREDICTOR OF HOW – AND
WHETHER – SOMEONE WILL VOTE IN THE FUTURE IS HOW – AND WHETHER –
THEY HAVE VOTED IN THE PAST. _Today, there are about 91 million
Americans who have voted for Biden and House Democrats since 2016, and
about 83 million who have voted for Trump or House Republicans. If
this pool of voters votes that way again, and if they constitute 80
percent of those voting in 2024 (a fairly conservative assumption),
then the other 20 percent of voters would have to favor Trump by 18
points for him to overcome that deficit. That’s just simple
arithmetic. Let’s make a much more conservative assumption – that
Harris does only half as well as Biden did with those voters (in other
words, that she only wins them by 2.25 instead of 4.5).1
[[link removed]] In
that case, Trump would still need to win first time voters by 9
points. There’s just no evidence to suggest anything like that is in
the offing – but plenty of evidence to the contrary, as you’ll see
in this post.

I want to underscore the significance of this. This will
be_ DEMOCRATS’ FIFTH CONSECUTIVE POPULAR VOTE WIN,_ which has
happened only once before since the Civil War (Truman in 1948). It
will also mark_ THEIR EIGHTH POPULAR VOTE WIN OUT OF THE PREVIOUS
NINE PRESIDENTIAL ELECTIONS, WHICH HAS NEVER HAPPENED BEFORE. _And
Donald Trump will be only the second major party nominee to lose the
popular vote three times since the Civil War (William Jennings Bryan
is the other).2
[[link removed]]

Now, in a rational democracy, that would be the end of the story. But
we live in America. We cannot be as confident of the result in the
Electoral College states. Thus, _REASONABLE ANTICIPATIONS THAT THIS
WILL BE ANOTHER “VERY CLOSE” PRESIDENTIAL ELECTION SHOULD BE SEEN
NOT AS “REASONABLE” AT ALL, BUT AS HERALDING ANOTHER MAJOR
CRISIS. _

But that crisis is for another _Weekend Reading _post. For today,
I’m sticking to the cold, hard numbers that we need to navigate our
nightmare Frankenstein-federalist system.

As I’ve repeatedly
[[link removed]] explained
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horse race polls can’t tell us anything we don’t already know
about the Electoral College outcome – that it will likely come down
to six battleground states3
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and that the results in those states will likely be too close for us
to have confidence in even the highest quality polls. Of course, some
polls will get it right; the problem is that we don’t know which
ones until after the election. Inevitably someone will be right, but
only because so many were guessing. When there are bets on every
number at a roulette table, someone is going to win – and with just
six states in play, flipping a coin would have a reasonable chance of
being correct.4
[[link removed]]

Does this mean data can’t tell us _anything _useful ahead of time
about what will happen? Of course not! It’s just that the helpful
data is not the data you typically hear about. Beginning with the 2008
election, Catalist has been compiling and maintaining high quality
voter files, which offer crucial insights into who votes. Studying
voter files allows us to see what I said at the beginning – that the
best predictor of future voting behavior is past voting behavior. 

Therefore, in this post, _I WILL USE VOTER FILE DATA TO CONSTRUCT A
MODEL OF THE LIKELY 2024 ELECTORATE – NOT BY DEMOGRAPHICS, BUT BY
VOTE HISTORY AND BEHAVIOR._ I will model two different scenarios, one
with “low turnout” and one with “high turnout,” to show the
most consequential factors determining the final outcome. 

This post has three parts:

1)   BACKGROUND: WE’RE NOT IN KANSAS ANYMORE
[[link removed]] - Since 2016, more
people are voting, newer voters are breaking for Democrats, and few
people are changing their partisan choice from election to
election.  

2)   DEFINITIONS - There is no standard set of definitions to
describe different segments of the voter file. In this section, I’ll
define the segments I’m going to use in the model. 

3)   MODELING THE 2024 ELECTORATE - The payoff.

BACKGROUND: WE’RE NOT IN KANSAS ANYMORE

Americans have three options every other November – to vote for the
Democrat, vote for the Republican, or not to vote at all.5
[[link removed]] But
the media and commentators rigidly resist any attention or study to
who doesn’t vote and why, instead poring over what seems like a
dozen polls a day which only speak – unreliably – to the first
question.

Thus, the political press has missed one of the most important
election stories of the last eight years: _WHO VOTES IN THE MAGA ERA
IS DIFFERENT FROM WHO VOTED BEFORE._ Regular readers have probably
seen some of these charts before, but they bear repeating as
background here. 

MORE PEOPLE ARE VOTING

Since 2016, we keep essentially having the same election over and
over, because voters keep facing the same choice – a Trump/MAGA
future for America, or not. Most people already know that they _do
not_ want a MAGA future. The salience of this choice has driven
historically high turnout, which has consistently resulted in wins for
Democrats (even though many anti-MAGA voters don’t identify as
Democrats). 

Until recently, the percentage of eligible voters who participated in
elections had been one of the most stable metrics in politics. The
flat trend lines below show that, for nearly a century, turnout rates
remained within a +/- 3 point range for decades at a time – but
after 2016, as the three bubbles on the right show, we’re not in
Kansas anymore.6
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This phenomenon is especially noteworthy because, in electoral
democracies, higher turnout generally signifies greater approval of
and confidence in the political system. Yet we know that the opposite
has been the case in the United States, as all those measures of
approval and confidence have been declining for quite some
time. _MORE PEOPLE ARE VOTING NOT BECAUSE MORE PEOPLE BELIEVE ONE OR
THE OTHER PARTY WILL MAKE THEIR LIVES BETTER, BUT BECAUSE MORE PEOPLE
ARE CONVINCED THAT ONE OR THE OTHER PARTY WILL MAKE THEIR LIVES
WORSE._ 

In other words,_ FOR MANY, VOTING HAS BECOME AN ACT OF SELF
DEFENSE. _

That’s why fewer and fewer Americans identify as either Democrats or
Republicans, even though both voter participation and partisan choice
polarization are historically high.

NEW VOTERS ARE MUCH MORE ANTI-MAGA

It’s a serious analytical oversight that our political media focuses
nearly all its attention on _FOR WHOM PEOPLE WILL VOTE_ (that is,
for Harris or Trump), and almost none on _WHETHER PEOPLE WILL VOTE_.
Since 2016, having an anti-MAGA voting majority depends on previously
occasional voters casting ballots more consistently now, and those who
had not been voting deciding to cast ballots. Indeed, Biden would have
lost the Electoral College in 2020 without the support of those
“whether” voters.

_THE DIFFERENCE BETWEEN DEMOCRATS’ LOSSES IN 2016 AND SUBSEQUENT
VICTORIES HAS BEEN THE INFUSION OF THOSE NEW VOTERS. _That is most
vividly apparent in the five states that Biden flipped to win the
Electoral College. The following graph shows how Biden's margin in
each of the five states was nearly identical to Clinton’s four years
earlier (hollow red bubbles) among voters casting ballots in both
elections (solid red bubbles). _IN 2020, BIDEN FLIPPED ARIZONA,
GEORGIA, MICHIGAN, PENNSYLVANIA AND WISCONSIN BECAUSE OF THE INFUSION
OF NEW ANTI-MAGA VOTERS._ That was the case nationally as well, as he
won the 2016 and 2020 voters by the same 2 point margin Clinton
carried them, but won the new voters by about a dozen points. 

[[link removed]]

In previous _Weekend Readings_, I’ve offered several independent
data approaches to see how big a factor Trump/MAGA has been in driving
who votes in elections after 2016. For example, the following graph
shows the turnout rates in three regions – the six Electoral College
battlegrounds; the three states that I call the Blue State Blues
(California, New Jersey and New York); and the remaining 41 states. As
you can see, in 2020, turnout rates were not much different across the
three regions. But in 2022, in the battleground states – where the
MAGA threat was most salient – turnout rates far surpassed the rest
of the country. And where the threats of _Dobbs,_ etc. seemed most
remote (the Blue State Blues states), the turnout rate was the
lowest.7
[[link removed]] (For
much more see “Red Wave; Blue Undertow
[[link removed]]” and “A
Tale of Two 2022 Midterms
[[link removed]].”) 

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FEWER PEOPLE ARE CHANGING THEIR MINDS

There is substantial evidence that after 2016, substantially fewer
voters are changing their minds. The following graph8
[[link removed]] makes
this dramatically clear. Again, this shouldn’t surprise us, since
the differences between the two parties have never been as great, or
as well known, as they are today.9
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Just as an aside, because I don’t know if I’ll ever come back to
this – note the sequence 2008-2012-2016 for what it suggests about
the so-called Obama-Trump voters. TLDR: Yes there are definitely some
Obama-Trump voters in the ways they are popularly imagined (lifelong
Democrats working class whites defecting to Trump), but much more of
the phenomenon can be explained by the reversion of lifelong
Republican voters who were disaffected in 2008. See this footnote for
more.10
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THE ILLUSION OF “SWINGINESS”

If the electorate is as set as the foregoing argues, why is there so
much volatility in the polling? Two big reasons – statistical noise
with real movement in the electorate, and survey questions which
exaggerate how many voters are actually movable. 

CONFUSING STATISTICAL NOISE FOR MOVEMENT

Let’s say we’ve been asking the same 2,000 people every week for
the last year who they think they will vote for for president. You
would expect to see almost no change week to week, and not much more
change over a year or more. Indeed, this is the result we get in the
real world from panel studies that do exactly this. Yet if we ask a
different set of 2,000 people every week, we will invariably see
swings – _NOT BECAUSE INDIVIDUALS ARE CHANGING THEIR MINDS, BUT
BECAUSE WE ARE CHANGING OUR MINDS ABOUT WHO TO ASK. _

Remember, if polls showing the race to be tied right now are borne
out, that would mean a national swing away from Democrats of 4.5
points – greater than any swing from one presidential election to
the next in the 21st Century, other than 2008. And, as you can see, in
2020, few states moved as much as 4.5 points, and most moved by less
than 3 points. 

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ANSWERING “UNDECIDED” ON A SURVEY ≠ OPEN TO VOTING FOR EITHER
CANDIDATE

The common _meaning_ of “undecided” is someone who might vote
for Trump or Harris. However, the practical “_definition_” of
“undecided” is someone who says they are undecided on a survey. In
reality, there are far fewer genuinely movable voters than there are
survey respondents who say they are “undecided.” 

Moreover, the closer to the election we get, being “undecided” is
a good proxy for “probably won’t vote.” In fact, it’s a much
more accurate predictor of whether someone will vote than the standard
“are you enthusiastic” or “how likely are you to vote”
questions – because, as we know well from social science, humans are
bad at predicting their own future behavior. 

Because this is somewhat technical, and because it takes us afield
from the main points of this post, I’ve explained more about why we
know all of this in this long footnote.11
[[link removed]] Otherwise,
read on!

DEFINITIONS

Let’s begin by dividing eligible voters into two
categories: ACTIVE (people who have voted before)
and POTENTIAL (people who haven’t). Then can we subdivide those
two categories further.

ACTIVE VOTERS - I’ll spend the most time talking about these three
groups of active voters:

*
_HABITUAL VOTERS_. All those who voted in all four of the previous
four elections. Consistently, 95 percent of this group votes in the
next presidential election.

*
_CONTINGENT VOTERS: _All those who voted in at least one, but not
all, of the previous four elections. For our purposes, two major
groups of contingent voters are important:

*
_2016 VOTERS. _Those who voted in 2016 but skipped at least one of
the next three elections. 

*
_NEW VOTERS_. Those who did not vote in 2016 but have since. As you
will see shortly, THESE ARE THE VOTERS WHO HAVE DRIVEN HISTORICALLY
HIGH TURNOUT RATES. 

POTENTIAL VOTERS - Since they haven’t voted before and we therefore
don’t have information about their likely partisanship, I’ll only
show how they complete the map of eligible voters towards the end of
the piece.

*
_NEWLY ELIGIBLE VOTERS_. Those who were not eligible in the last
presidential election and who did not vote in the recent midterm.
These voters have consistently been about 11 percent of the eligible
population, not less than 10 or more than 12 percent.

*
_NON-VOTERS_. Those who have been eligible since at least the last
presidential election but have not cast a vote in a federal election.

With those categories in mind, let’s look at the composition of
active voters ahead of the 2016, 2020 and 2024 elections. As you can
see, the number of new voters12
[[link removed]] jumped _significantly_ ahead
of 2020, and has done so again ahead of 2024 after more people voted
for the first time in the last midterm.13
[[link removed]] (WHEREVER
THIS PIECE REFERS TO “NEW VOTERS,” IT IS SHORTHAND FOR
“CONTINGENT NEW VOTERS”; IF I MEAN FIRST-TIME/NEWLY ELIGIBLE
VOTERS, I WILL SPECIFY THEM AS SUCH.) 

[[link removed]]

The next graph splits up the first category further, into habitual and
2016 contingent. Combined, those voters have remained at the same
levels. But ahead of 2024, more of the previously contingent (2016)
have become habitual voters – reflecting their more consistent
engagement in the Trump/MAGA Era. 

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There are sharp partisan differences between the categories ahead of
the 2024 elections.14
[[link removed]] In
the next graph, habitual voters (green bubbles) are the least
Democratic voters of the three categories. That makes sense, since
those who vote most often usually are the most “conservative” in
the sense that they are more successful and feel more agency in their
lives. But, remember, they are somewhat more Democratic now – not
because those who were habitual voters in 2016 became Democrats, but
because those who are newly habitual voters favor Democrats more than
those who had previously been habitual voters. The key point in this
graph is how much more Democratic new voters are in every region,
including Red States. They have been activated by the threat (or
appeal) of Trump/MAGA, with more against MAGA than for. 

[[link removed]]

In the following graph, we see clearly that differences in race,
ethnicity, or education don’t explain these dramatic differences in
partisanship. The demographic profile of 2016 contingent voters (who
favored Democrats by only about 4 points) is identical to the
demographic profile of new contingent voters (who favored Democrats by
about a dozen points). And, despite consisting of a substantially
greater share of white college voters, habitual voters broke even
between the two parties. 

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MODELING THE 2024 ELECTORATE

Now, let’s use what we’ve learned so far to model how many voters
of which type are likely to show up in 2024, depending on turnout
levels. All of the numbers of voters in this section are based on the
Catalist voter file – they are administrative records, no modeling
or polling involved. All the partisan estimates for each tranche of
voters is based on Catalist modeling. I’ll look at both the national
vote and the vote in the six battlegrounds needed to win the Electoral
College.

THE POOL OF ELIGIBLE VOTERS INCLUDES:

174 MILLION ACTIVE VOTERS: 

*
72 MILLION HABITUAL VOTERS who voted in each of the last four cycles.

*
46 MILLION CONTINGENT 2016 VOTERS who voted in 2016, but not all of
the next three elections. (About two-thirds can be thought of as
“presidential” voters, having voted in 2012 and 2020 as well.)

*
57 MILLION CONTINGENT NEW VOTERS who voted in at least one of 2018,
2020 and 2022, but not in 2016.15
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73 MILLION ELIGIBLE NON-VOTERS, or citizens eligible to vote but who
haven’t. This includes ABOUT 9 MILLION YOUNG VOTERS NEWLY
ELIGIBLE since the last presidential election, less those who voted
in the 2022 midterms.

The next two panels give you some perspective on the relative size of
those groups, comparing the entire United States to the six
battlegrounds. The panel on the left describes the composition of
active voters and the panel on the right the composition of all
eligible voters. It builds from the ground up, with the base being
habitual voters. 

[[link removed]]

Of note is that in the battleground states, habitual voters make up
the greatest share in Wisconsin, which is consistent with the very
narrow range of outcomes there. Not surprisingly, habitual voters make
up the smallest share in Nevada, which has had substantial
out-migration during COVID and in-migration more recently. This makes
expectations for outcomes there especially uncertain.

2024: HIGH OR LOW TURNOUT?

Despite all the talk about whether 2024 will be a high or low turnout
election, I haven’t seen anyone specify what they mean by either
term. (And strangely, this turnout discourse seems to have disappeared
without a trace after Biden dropped out.) 

Provisionally, let’s begin by saying that a “low turnout”
election is one in which the turnout rate in each state is the lowest
it’s been in that state in the previous three elections (2012, 2016
and 2020). That works out to 142 million voters in 2024. Then, because
2020 was historic (67 percent, the highest it’s ever been since the
19th century), let’s leave that as our definition of a “high
turnout” election.

Segmenting the electorate into the vote history categories I’ve
described allows us to be fairly confident of the likelihood that
voters in those segments will vote in 2024 under different turnout
assumptions. Thus, with what we know about previous behavior patterns,
we can begin to get a sense of what 2024 might look like in either
scenario. (Geek bonus – read this footnote for more on how this
differs from “turnout modeling” you’ve read about.16
[[link removed]])

TRANCHE ONE: HABITUAL VOTERS

The next graph provides a template for understanding 2024 turnout from
the ground up. In 2020 and in 2016, 95 percent of those who voted in
the four previous elections voted in that election. That is almost
certain to be a good approximation for 2024, regardless of how engaged
other eligible voters are. I’ve allocated habitual voters to who
they voted for previously. NATIONALLY, THAT MEANS THAT HARRIS STARTS
“TIED,” AND ABOUT 3 AND A HALF POINTS BEHIND IN THE ELECTORAL
COLLEGE BATTLEGROUNDS.17
[[link removed]]

[[link removed]]

Let’s pause to think about what that means. Nationally, the race
will be decided by the 74 million other voters in the Low scenario or
99 million in the High scenario. But, IN THE ELECTORAL COLLEGE
BATTLEGROUND, HARRIS CANNOT WIN UNLESS SHE WINS A MAJORITY OF THOSE
WHO ARE _NOT_ HABITUAL VOTERS. By how much? In the Low scenario,
she has to win the remaining voters by 4 points; in the high turnout
scenario she needs to win the remaining voters by 3 points. 

This highlights an important point in this new way of thinking about
who will vote. _IF YOU ARE BEHIND WITH HABITUAL VOTERS, THEN ALL ELSE
BEING EQUAL YOU WILL DO BETTER WITH HIGHER TURNOUT, BECAUSE YOU NEED
TO WIN A SMALLER SHARE OF THE CONTINGENT VOTERS TO OVERCOME YOUR
DEFICIT WITH HABITUAL VOTERS. _

TRANCHE 2: CONTINGENT 2016 VOTERS (WHO VOTED IN 2022)

Now, let’s add contingent 2016 voters. I’m going to have to get a
bit more technical than in my conceptual categorization because those
who voted in 2016 can be usefully divided by whether they voted in
2022 as well. That’s because historically, about 90 percent of those
who voted in the second previous presidential election and the most
recent midterm vote in the next presidential election. Think of them
as essentially habitual voters who happened not to vote in all
four. NATIONALLY AND IN THE BATTLEGROUND, THIS GROUP HAS BEEN ABOUT
16 POINTS TRUMP/REPUBLICAN, while the other 2016 voters lean
Democratic, as we saw earlier. So it’s worth pulling them out. 

[[link removed]]

WHEN YOU COMBINE THESE TWO MOST-LIKELY-TO-VOTE CATEGORIES, HARRIS
“TRAILS” TRUMP BY 2 POINTS NATIONALLY AND BY 5 POINTS IN THE
ELECTORAL COLLEGE BATTLEGROUNDS.18
[[link removed]] That
means that nationally, Harris would need to win the remaining 65
million in the Low scenario by about 2 and a half points and the
remaining 90 million in the High scenario by about 2 points. In the
Electoral College battlegrounds, Harris would need to win the
remaining 7 million voters (Low) by 8 points, or the remaining 13
million voters (High) by about 5 points. 

Again, these first two tranches are the most likely to vote in
2024. _THE KEY TAKEAWAY FOR THESE GROUPS IS THAT IN THE ELECTORAL
COLLEGE STATES, HARRIS BEGINS BEHIND, AND WOULD NEED TO WIN THE
REMAINING VOTERS IN A LOW TURNOUT SCENARIO BY A GREATER MARGIN THAN
SHE WOULD IN THE HIGH TURNOUT SCENARIO._

TRANCHE 3 - CONTINGENT 2016 VOTERS (WHO DIDN’T VOTE IN 2022)

Now, we’ll look at the rest of those who voted in 2016, but not in
2022. This group of voters is more Democratic than the previous two
essentially habitual voting categories, FAVORING DEMOCRATS BY ABOUT 9
POINTS NATIONALLY AND 8 POINTS IN THE ELECTORAL COLLEGE
BATTLEGROUNDS. Since this exercise is not meant to be predictive, but
to illustrate turnout dynamics, let’s assume that about half of this
group votes in 2024 (Low) or 55 percent (High).19
[[link removed]]

[[link removed]]

ONCE YOU ROLL IN THESE VOTERS, HARRIS DRAWS EVEN NATIONALLY, with
between 47 and 70 million voters left to account for in the two
scenarios. HOWEVER, SHE IS STILL “TRAILING” BY A BIT MORE THAN 3
POINTS IN BOTH SCENARIOS IN THE ELECTORAL COLLEGE BATTLEGROUNDS. That
means that to win those states, she would need to win the remaining
6.5 million voters by about 9 points (Low) or the remaining 11 million
voters by about 5 points (High). 

TRANCHE 4 - NEW VOTERS

Now let’s turn to the voters who have been most Democratic - those
who did not vote in 2016, but have since then. NATIONALLY THEY HAVE
FAVORED DEMOCRATS BY ABOUT 13 POINTS, AND IN THE BATTLEGROUNDS BY
ABOUT 9 POINTS. _THIS IS A GROUP WITHOUT HELPFUL PRECEDENTS FOR OUR
TURNOUT ASSUMPTIONS, AS ITS SIZE AND CHARACTER ARE OUT OF SCALE WITH
WHAT PRECEDED PREVIOUS PRESIDENTIAL ELECTIONS._ 

Now – again, just to illustrate the dynamics at play, _not_ to
forecast the winner in six weeks – let’s assume that in the Low
scenario, two thirds of the new voters cast ballots with the same
Democratic margin they had voted previously. For the High scenario,
let’s assume that it’s 70 percent.20
[[link removed]]

With those assumptions, HARRIS “LEADS” BY ABOUT 3.5 POINTS
NATIONALLY IN EITHER SCENARIO, with about 9 million more votes to be
cast in the Low scenario and about 31 million more votes to be cast in
the High scenario. IN THE ELECTORAL COLLEGE BATTLEGROUND STATES, SHE
PULLS EVEN, with between 1 million (Low) and 5 million more (High) to
be cast. 

[[link removed]]

TRANCHE 5 - NEVER BEFORE 2024 VOTERS

Looking back over the 2012, 2016 and 2020 presidential
elections, BOTH NATIONALLY AND IN THE BATTLEGROUND STATES, FIRST-TIME
VOTERS CONSTITUTED A REMARKABLY CONSISTENT 10-12 PERCENT OF THE
ELIGIBLE POPULATION. Not surprisingly, about two thirds have been
younger voters. The following graph shows the results if we assume
that half of them vote in the Low scenario and 60 percent vote in the
High scenario. We don’t have a basis for assuming their
partisanship, so I’m labeling them in gray. 

As you can see, both nationally and in the battleground states,
building from the ground up yields greater turnout than the seemingly
reasonable low turnout scenario. On the other hand, building from the
ground up falls short of the high turnout scenarios. Unsurprisingly,
In both cases, turnout is higher in the battleground states because,
as I noted earlier, turnout was substantially higher in those states
in the 2022 midterms than they were in the rest of the country. 

[[link removed]]

CONCLUSION

If you’ve made it this far, I hope you share my confidence that
Harris will win the popular vote, and understand why: that those who
have already voted in at least one of the last four elections (1)
favor Harris, (2) have switched partisan sides in very small numbers,
and nearly equally on each side, and (3) will constitute such a large
share of all voters as to be too much for first time voters to
overcome even if they favor Trump by implausibly large numbers.  

Sadly, the same cannot be said with confidence for the Electoral
College battleground states. Harris needs the kind of high turnout
from contingent new voters that pushed Biden over the top (barely) in
those states, and which contributed to the Democratic near-sweep in
those states in the 2022 midterms (even as they ran against the usual
strong winds against the party in power). 

As I’ve explained, evidence indicates that this high turnout has
been motivated by loss aversion
[[link removed]] –
the belief and fear that MAGA will take away fundamental freedoms.
It’s not clear whether those stakes will be clear enough to
contingent voters this year to motivate similar turnout. As I wrote in
“About that Times Poll
[[link removed]],” while
Harris has done a terrific job reconsolidating and inspiring
Democrats, perceptions of how dangerous a second Trump Administration
will be have stalled. If that doesn’t change, we risk that too many
of those new voters who came out before will stay home in November. If
that happens, it will be an unforgivable failure of the media and
civil society to alert Americans to the very avoidable consequences of
MAGA regaining power. 

_Weekend Reading is edited by Emily Crockett, with research assistance
by Andrea Evans and Thomas Mande._

_Michael Podhorzer @michaelpodhorzer
[[link removed]]
is former political director of the AFL-CIO. Senior fellow at the
Center for American Progress. Founder: Analyst Institute, Research
Collaborative (RC), Co-founder: Working America, Catalist. He
publishes Weekend Reading. (weekendreading.net)_

1
[[link removed]] That
would happen if disproportionately more Trump than Biden voters cast
ballots, and/or if more Biden voters cast ballots for Trump than
formerly Trump voters cast ballots for Harris. 

2
[[link removed]] For
trivia buffs - Henry Clay lost three times before the Civil War.

3
[[link removed]] The
six states are Arizona, Georgia, Michigan, Nevada, Pennsylvania and
Wisconsin. See The Electoral College Landscape 
[[link removed]]for
the rationale. North Carolina is now considered a battleground as
well, with some polls showing Harris doing better there than in
Georgia. That very well may be. But since Democrats have won the state
only once since 1976, for Harris to do so in 2024 will require a
significant number of Tar Heels to defect. That’s certainly not
impossible, but it is not something that can be anticipated from voter
file data. 

4
[[link removed]] A
further problem, lest you throw this back in my face when I’m right,
is that other statistical forecasts don’t come with an explanation
for the outcome - it’s all very black box. When I say that Kamala
Harris is going to win the popular vote, I’m also showing how that
will happen based on an accurate model of voting behavior, which I’m
disclosing as well.

5
[[link removed]] I
treat voting for a third party as not voting. All partisan percentages
are of the two-party vote.

6
[[link removed]] For
the curious - the dip around 1972 was a result of the 26th Amendment
lowering the voting age to 18. Given low turnout rates for young
people, that increased the denominator by substantially more than the
numerator. I would associate the jump up in the 2004 presidential
election as a precursor to the current MAGA voting rates, as Bush was
a lightning rod then.

7
[[link removed]] These
turnout differentials were consistent across demographic groups.
It’s not the case, for instance, that Democrats won simply due to
higher turnout from the white college voters who have flocked to their
side in recent years. (Read here
[[link removed]] for
more on this point, and more explanation of this turnout rate
chart.) 

8
[[link removed]] Data
Sources:1972 to 2008 from NYT exit poll archive
[[link removed]]s;
2012 and 2016 from CCES post-election surveys
[[link removed]] using validated vote weights;
2020 is an average of the following: National Election pool/Edison
polling retrieved from CNN
[[link removed]], AP
Votecast
[[link removed]] exit
polls published by WSJ [[link removed]],
Pew American Trends Panel 78
[[link removed]] survey
using validated vote weights, and CCES post-election survey
[[link removed]] using
validated vote weights.

9
[[link removed]] The
percentage of voters defecting is not the percent of the entire
electorate; it is the percentage of voters from the specified partisan
vote choice in the prior election that voted for an opposite party
president in the next election. For example, exit polling estimates
that, within the subset of voters who voted for Clinton in 2016 and
then voted again in 2020, 4% of those voters voted for Trump in
2020. 

10
[[link removed]] As
you can see, in 2008, there were a lot of Bush-Obama voters, although
that was little noticed then or subsequently. ANES polling
[[link removed]] found
that 17 percent of Obama voters in 2008 had been for George W. Bush in
2004. According to CCES data, Obama-Trump voters had previously voted
for Republican congressional candidates by a 31-point margin,
Republican Senate candidates by a 15-point margin, and Republican
gubernatorial candidates by a 27-point margin. (For more
[[link removed]].)
That was followed in 2012 and 2016, where we see switchers to
Republican far outnumbering switchers to Democrats – in other words,
the return of many of those Bush-Obama voters to the Republican
fold. 

In 2008, many of those who voted for Bush twice voted for Obama
because of all the factors we’re so familiar with - the crash, Iraq,
Katrina, etc. In 2012, we see the lowest level of Republican to
Democratic defection in the time series, reflecting the near peak of
such defections the previous year.

11
[[link removed]] The
proportion of those who say they are “undecided” or
“independent” in surveys – but who are certain to vote for one
party or the other – has been increasing substantially since 2008.
As it turns out, however, we can be certain about how many of those
who say they are undecided on surveys will vote if they cast a ballot
if we ask other questions as well. When I was at the AFL-CIO, we did
extensive investigations into finding the best way to determine
whether someone was actually undecided between the two candidates or
parties. 

Here's an example of an experiment we ran that can illustrate what I'm
talking about. The standard questions about partisanship are (1) what
party the voter supports, and if independent, which way they lean; and
(2) which candidate the voter supports, and if not declared, which way
they lean. We started tacking a question on at the end along the lines
of: Do you always vote for Democrats, usually vote for Democrats,
usually vote for Republicans, or always vote for Republicans? We
didn’t offer an option like “both sides equally,” which meant
respondents had to volunteer such an answer. Given this choice, about
90 percent said they usually or always vote for one or the other
party. Then when we conducted panel back surveys after the election,
we consistently found that exercise was overwhelmingly correct for
those who didn't declare earlier in the survey – and that _THOSE
WHO VOLUNTEERED A DIFFERENT ANSWER USUALLY DIDN'T VOTE AT ALL_. 

There’s a reason that question worked so well. THE STANDARD PARTY
ID QUESTION FALLS SHORT BECAUSE IT ASKS RESPONDENTS TO OWN A PARTISAN
IDENTITY – SOMETHING MANY ARE UNCOMFORTABLE WITH. ASKING PEOPLE WHO
THEY _WILL _VOTE FOR FALLS SHORT BECAUSE ALL OF US ARE BAD AT
PREDICTING OUR FUTURE BEHAVIOR. BUT THE END OF SURVEY QUESTION CATCHES
PEOPLE OFF GUARD AND ASKS THEM TO REPORT SOMETHING THAT HAS AN
OBJECTIVE ANSWER – WHAT DID THEY DO. 

Also, let’s think about someone who would never vote for Trump but
was very unhappy about Biden when he was still in the race. The
pollster wants the respondent to answer the question “Will you vote
for Biden or Trump?” literally – as in, “If you vote, will you
vote for Biden or Trump?” But that respondent, who is anti-Trump but
sad about Biden, easily chooses “undecided” to mean they are in
some sense reluctant to say they are for Biden. 

THIS IS A CLASSIC AND PERVASIVE ERROR IN THE MEDIA’S ANALYSIS OF
THEIR OWN POLLS: THEY ASSUME THAT RESPONDENTS ARE ANSWERING THE
QUESTION THE POLLSTER WANTS THEM TO. Question writing is more
difficult than it appears, because what the words mean to the pollster
are not always what the words mean to the survey taker. That’s why
in our work at the AFL-CIO, we took a cue from the social sciences and
always experimented with different ways of asking the same question to
be sure that we were getting the responses to the question we
intended. UNFORTUNATELY, MOST MEDIA POLLING ANALYSTS PROCEED WITH
COMPLETE CONFIDENCE THAT THE RESPONSES ARE TO THE QUESTION THEY
INTENDED. 

We found the most accurate way to identify actually movable voters was
with a combination of two questions - asking about the favorability of
both candidates (or parties) on a four point scale (very/somewhat
favorable/unfavorable). In 2018 and 2020, those who were very
unfavorable of only one party – even if they were somewhat
unfavorable of the other party – voted against that party about 95
percent of the time. We called the rest “partisan bystanders,”
which we split into two subcategories. “Passive bystanders” had a
somewhat favorable or unfavorable opinion of both parties; “hostile
bystanders” were those who had very unfavorable opinions of both.
After each election, most of those who indeed switched sides were
partisan bystanders.

[[link removed]]

12
[[link removed]] In
2020 and after, referring to those voting for the first time after
2016; in 2016, referring to those voting for the first time after
2008.

13
[[link removed]] Note
- in order to generate a comparable category “new voters” for the
2016 election, I looked back to those who had voted in 2008 for an
apples to apples comparison. 

14
[[link removed]] Source:
Catalist scores every record on its file with what they call Vote
Choice Index (VCI), which is intended to rate the likelihood of that
voter having voted for a Democrat. VCI is much more accurate than
traditional polling-based modeling because scores are normalized to
the actual votes cast in each precinct.

15
[[link removed]] For
the sake of clarity, this category includes those who had voted before
2016, but not in 2016. Although small in number as a part of this
category compared to those voting for the very first time, they are
similar in outlook - being either Black voters who had been mobilized
by Obama but were lukewarm about Clinton, and those who sat out
because they perceived Romney to be a RINO.

16
[[link removed]] Even
before 2008, we had begun to build turnout models on an individual
state basis. The idea was essentially, that if you datamined all the
information about voters in the state available on the voter file, you
could rank order all the voters on the file in terms of their
likelihood of voting. Although the scores were 0 to 100, they were not
literally probabilities. Soon after, when demographic characteristics
were added, turnout models became the most reliably predictive large
scale voter models we had – far more so than, say partisan or vote
choice modeling. I’ve moved away from that approach because in the
MAGA/Trump era, we can see that what’s on the ballot has become a
major factor in whether contingent voters cast ballots. We can see
that clearly in the 2022 midterms, where voters with similar turnout
scores voted at different rates in the MAGA battlegrounds and the rest
of the country. See Red Wave; Blue Undertow
[[link removed]]. 

17
[[link removed]] I
use words like “about” to modify numbers to remind readers that
estimates, even when they deceptively use decimal points, are just
that - estimates. And I will almost always use graphic representations
for estimated numbers to produce a useful visual margin of error. If I
use precise numbers it’s only for administrative records, such as
how many people voted in the last election.

18
[[link removed]] I
use quotation marks to remind the reader these are estimates in a
simulation.

19
[[link removed]] This
is based on how similar voters turned out in earlier elections.

20
[[link removed]] This
seems reasonable based on how voters so defined turned out in previous
cycles - however, as I’ve said, this is now a much bigger group, so
I’m extra caveating.

* elections
[[link removed]]
* electoral college
[[link removed]]
* battleground states
[[link removed]]
* young voters
[[link removed]]
* voter turnout
[[link removed]]

*
[[link removed]]
*
[[link removed]]
*
*
[[link removed]]

 

 

 

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