With the second set of democratic debates over last week, the race to be chosen as the Democrat who’ll face Trump in November 2020 is truly under way, including having already had the first serious drop-out, Eric Swalwell, whose campaign focusing on gun violence never really took off. That leaves us with around 24 contenders still fighting, and still the possibility of more joining the race.

However, at this point there is an extremely low chance of the candidates polling at a tenth of a percent, no matter how entertaining (Williamson), making any sudden headway, so this introduction will focus on the top 10, according to the rolling average of polls found on RealClearPolitics

So, with no further ado, let’s start with number one

1. Joe Biden

Age: 76
Highest office: Vice President
Home State: Delaware
Current polling: 31%

Bio: As the former Vice President to President Obama, Joe Biden is probably the best known person on the list. After a brief stint as a lawyer, Biden was elected a Senator at the young age of 30, and served for 41 years until becoming VP in 2009. His political expertise lies in foreign policy, having served as the chair of the Foreign Relations Committee for a number of years. His personal life is sadly filled with tragedy: only weeks after winning his first race for the Senate, his wife and daughter both died in a road accident, leaving him the single father of two boys, Beau and Hunter. His son Beau also passed away in 2015 from brain cancer, which is believed to be a key reason why Biden did not run for president in the 2016 race.

Why he could win: with President Trump being so unpopular among democrats, this time round polling shows that most democrats would prefer a candidate that has a good chance of winning over someone closer to their own positions, and that ‘electable’ candidate is often seen to be Biden. He has high favorables among swing voters, and his blue collar experience is seen as a strength in the key states of Michigan, Wisconsin and Pennsylvania. His policy positions are not radical, and his connections to Obama, who remains incredibly popular with Democrats, could be all he needs to win the general election next year. This is all borne out in the polling data, where he has consistently led the pack, even before he announced he was running, and currently is twice as popular as the second place candidate.

Why he might not: in political circles, Biden is known as a gaffe-machine – favourites include asking a man in a wheelchair to stand up at a rally and blessing the wrong not-dead parent of a colleague on St Patricks day. He also isn’t the best campaigner, having unsuccessfully run for president twice before, in 1988 and 2008. His 1988 campaign is particularly notable for ending after he got caught plagiarising a speech from then-UK Labour leader, Neil Kinnock. At 76, his age is also beginning to show, arguably more than the 77 year old Sanders, with slurring and forgetfulness quite visible in both debates so far. Finally, although extremely popular on the moderate side of the party, the ‘new left’/ AOC side of the party has a pretty low opinion of him, which could hurt him if they stay home on election day if he’s the candidate.

My % chance of winning: 30%

 

2. Bernie Sanders

Age: 77
Highest office: Senator
Home State: Vermont
Current polling: 15.8%

Bio: after a long youth spent campaigning on various left wing issues, including early Civil Rights activism, Sanders got involved in formal public service at the age of 39, becoming the mayor of Burlington, Vermont, as an out and proud Socialist, defeating the incumbent Democrat by just 10 votes. He served 8 years from 1980 to 1988, and then went on to become an Independent member of the House of Representatives from 1990, and a Senator from 2006. In 2016, he gained national fame when he came 2nd to Hillary Clinton in the race to be the Democratic nominee for president.

Why he could win: at second place in the polling to a gaffe-prone Biden, Bernie could well move into first if he can widen his base. His policy positions have had a noticeable effect on the democrats since 2016, for example, wanting a public option to Obama was the most left-wing position in 2016, but today it’s a given that anyone from the party’s left, moderates or centrists will support at least some variation on universal healthcare. Finally, his radical ideas are simultaneously firing up energy on his wing of the party without seeming to cost him much support when paired up against Trump in polls in the key swing states in the Midwest.

Why he might not: despite a strong core set of supporters, it is very difficult to win the primary without reaching out to other parts of the democratic membership, which Bernie doesn’t appear to be doing. Furthermore, his left lane is also occupied by the increasingly popular Elizabeth Warren. Unlike other candidates, he already has almost universal name recognition, so his room to grow is severely limited. As the oldest candidate, who would be 80 upon being sworn in, his age is likely to become an issue even if he does start gaining in the polls. Some of his more extreme policies, like banning private health insurance are way less popular than variations of Medicare for all that do not do so. Finally, despite a lot of life experience, he is wide open to attacks on his inability to get much done: he has only passed 7 bills in his 30 years in Congress, 2 of which are about renaming post offices and one renaming a holiday, and a popular anecdote from his youth tells of him getting kicked out of a socialist commune for not working enough.

My % chance of winning: 10%

 

3. Elizabeth Warren

Age: 70
Highest office: Senator
Home State: Massachusetts
Current polling: 15.5%

Bio: Although once a Republican, Warren now represents the left flank of the Democratic party along with Sanders, although unlike him, calls herself a capitalist, not a socialist. Warren graduated and briefly worked as a lawyer, before moving into law academia, where she became known as one of the leading US experts in bankruptcy law, and was a Harvard law professor. She became a Senator in 2012, and under the Obama administration she worked to grow and strengthen the newly established the Consumer Financial Protection Bureau – an agency to protect ordinary citizens against being exploited by large companies.

Why she could win: her polling average trend has been extremely impressive – starting at 4% in February, she has slowly but consistently inched her way up to 15% now, without the large jumps and dips that other candidates have shown. As is it highly likely that Sanders, as the farthest left candidate, won’t gain enough support from the moderates, and so she could start swallowing his 15% and head towards 30%, while also not facing the fierce opposition that he has from the DNC. She’s a policy wonk through and through, and is known for her detailed policy positions on her website, with her repeat line becoming ,”I have a plan for that!”.

Why she might not: in head to head polls Warren does not fare as well as Sanders or Biden against Trump, so if people are looking first for electability, it could hurt Warren here. Like with Sanders, her position of banning private health insurance could cost support among moderates. She was also bogged down early in the primary by a controversial spat with President Trump, where she claimed to be part native American, but a DNA test found that to be just one person 6 generations back. The Cherokee nation publicly condemned her for having put ‘Native American’ on college admission applications on these grounds. Some Democrats fear that Trump labelling her Pocahontas could bring down the tone of the debate in 2020 to a level where his tactics become much more effective.

My % chance of winning: 22%

 

4. Kamala Harris

Age: 54
Highest office: Senator
Home State: California
Current polling: 8.3%

Bio: Harris is a California native, from mixed Indian and Jamaican parents. She spent many years working as the district attorney, then Attorney General of California, before becoming a senator in 2016. She gained national attention in her questioning of Rod Rosenstein and Jeff Sessions over Trump’s firing of James Comey.

Why she could win: Harris jumped up from roughly 6 to 15% in the polls following her clash with Joe Biden in the first televised debates, when she brought up his history with busing. Although this was not repeated in the second debate, it did show her ability to win over a crowd, her fighting ability should she face Trump in a debate, and it cemented her position in the top tier of contenders. She also sits somewhere between the progressives and the moderates, and so isn’t particularly unpalatable for any wing of the party from a policy viewpoint. Finally, the combination of being mixed race and female gets her a lot of support from those in the Democratic party for whom minority representation is an important issue.

Why she might not: just as the first debate showed why she could win, the second debate showed why not. Her performance was somewhat lacklustre, simultaneously failing to land any strong attacks on Biden while being seriously hurt by an attack from Tulsi Gabbard on her history as AG, who claimed she had suppressed information about innocent people on death row, and had laughed about smoking marijuana while locking up people for it, among other accusations. It is not the place of this piece to verify these claims either way, but ultimately the truth of them isn’t important, people’s perception is: if people believe Harris to be disingenuous it could cost her the nomination. Lastly, although her policy middle-ground means not alienating either side, it also could mean she’s everyone’s 2nd or 3rd choice, and she could fail to gain enough 1st choice votes to get through to the end.

My % chance of winning: 18%

 

5. Pete Buttigieg

Age: 37
Highest office: Mayor of South Bend
Home State: Indiana
Current polling: 5.5%

Bio: Pete Buttigieg (BOOT-edge-edge) burst into the national scene in February when a video went viral where he attacked Mike Pence for abandoning his Christian values to ‘support the porn-star president’. He is currently serving as the mayor of South Bend, Indiana, population ~100,000. Despite his young age, he boasts an impressive CV: Harvard graduate, Rhodes Scholar to Oxford, speaker of 8 languages, Afghanistan war vet and McKinsey consultant, all before becoming the youngest mayor in America. Notably, as pictured above with his husband, Chasten, ‘Mayor Pete’ is the first serious gay candidate to ever run for president.

Why he could win: the very fact that a 37 year old (minimum age for president is 35) is polling ahead of a number of better-known Representatives and Senators is testament to Buttigieg’s ability to convey his message, primarily based around democratic reform (ending the electoral college, balancing and de-politicising the supreme court, making DC and Puerto Rico states). He is also openly religious, which is often avoided in Democratic politics, but is a clear open invitation for independents or disaffected Republicans to consider the other side. If he does win the nomination, his background in turning round a crumbling, midwest city could really help him in the necessary swing states.

Why he might not: for all his talent, he is massively lacking in experience that is not in short supply in this primary. In the second debate, his position between the moderates and progressives had the same failure as Harris to steal a lot of people’s 1st choice, even if people are generally favourable towards him. Many online commentators suggest that Buttigieg is a likely future president, but just not this time round. It will be worth watching if either Warren or Harris get the top spot, as Buttigieg will be in top contention as a VP pick, as a young male from the centre of the country, to balance out the two older females from the coasts.

My % chance of winning: 10%

 

6. Beto O’Rourke

Age: 46
Highest office: Representative in the House
Home State: Texas
Current polling: 2.5%

Bio: Beto O’Rourke took the national stage in 2018 when he turned down the chance to run again for his House seat that he had held since 2012 and instead challenge Ted Cruz’s Senate seat, losing 50.9%-48.3% – a result that was much closer than many initially expected.

Why he could win: in an election where electability is key, being a straight, white male, without being in your late 70s, and having moderate policy positions, could just be enough. O’Rourke himself is making a big play of whether a popular Texan democrat vs an unpopular NY Republican could result in Texas going blue in 2020, and some polls do suggest that it is possible. In terms of the electoral college, the democrats winning Texas would make their victory almost certain.

Why he might not: while riding high at 9.5% in polling in April, he has been on a slow decline since then, having spent the last month between 2 and 3%. In both debates, he failed to distinguish himself, and being whacked by Julian Castro in the first, and being completely forgettable in the second. Policy-wise, Beto hasn’t really stood out among the crowd and offered anything unique.

My % chance of winning: 2%

 

7. Cory Booker

Age: 50
Highest office: Senator
Home State: New Jersey
Current polling: 2.3%

Bio: as a Rhodes scholar and Harvard law graduate, Booker has been involved in public office since shortly after university, serving as municipal councillor, then mayor of Newark from 2006 to 2013, and since has served as a senator for New Jersey. If elected president, he would be the first vegan to serve as POTUS.

Why he could win: Booker represents a general decent play for all the things you might want from a candidate: he was rated the third most liberal senator, while simultaneously is not seen as being a radical like Sanders or Warren. He is black, so could win back some voters who voted for Obama in 2012 but did not vote at all in 2016, and he speaks Spanish and so could possible court the Hispanic vote.

Why he might not: unlike many others in the field, Booker doesn’t seem to have a single issue that he owns, and perhaps explains some of the reason his support isn’t too high. If he tries to compete as ‘the black candidate’, he’ll still face challenges from Biden and Harris, who are polling higher with black voters. He’s not unknown either, so it’s not likely he’ll shoot up with more air time. He has been criticised for his links to donors in the pharma sector, which dominates the NJ economy. Lastly, while his CV may look ideal for a VP pick on paper, the specifics make it unlikely: Sanders or Biden would very probably choose a woman for VP; Buttigieg has confirmed he would have a gender-balanced ticket; if Harris gets it, it’s possible they may wish to avoid two black people on the same ticket; if Warren gets it, the geographical play of her MA background and his NJ background seems like a pretty weak combination considering where the battle states are.

My % chance of winning: 4%

 

8. Andrew Yang 

Age: 44
Highest office: Entrepreneur, no public office held
Home State: New York
Current polling: 1.5%

Bio: Yang is the biggest, serious outsider contending for the Democratic ticket, having never held any elected office. His background is as an entrepreneur, and the founder of the not-for-profit Venture for America, which helps young people start businesses in struggling cities. He is known for his incredibly detailed policies, including his flagship policy – a Universal Basic Income (UBI) of $1000 a month for every citizen – as well as his tag lines – MATH (Make America think harder), and “the opposite of Donald Trump is an Asian man who loves math”.

Why he could win: Yang is nothing if not ambitious in his policy platform of UBI, Medicare for All, a carbon tax etc. He just managed to qualify for the 3rd debate in September, which required multiple polls at 2%, and has knocked out more than half the field so far, so he’s clearly being taken seriously and out-performing seasoned Democratic politicians. He also boasts a popular online following, and is reportedly winning over many independents, libertarians and disaffected Republicans.

Why he might not: while Yang is a good speaker, and fantastic on detailed answers on the fly, he simply represents too much of an unknown in an election where electability is the number 1 priority. While his fans are crazy about the idea of a UBI, it is a pretty divisive policy polls wise, so another big risk if he were to win the nomination. However, Yang has publicly discussed the idea of helping however he can, including serving in a cabinet capacity. My person prediction says he has good odds of landing such a job, especially as something like Labor Secretary, if not a new position for automation.

My % chance of winning: 2%

 

9. Tulsi Gabbard

Age: 38
Highest office: Representative in the House
Home State: Hawaii
Current polling: 1.3%

Bio: as the second youngest running candidate behind Mayor Pete, Gabbard’s key distinction is that she is only one of two (Pete again) veterans running, although she has made this much more central to her platform of peace abroad and ending needless wars. She has served in the House since 2012, and was the first Hindu elected to congress.

Why she could win: as anyone watching the debates has seen, she is a very confident and competent performer – the 538 team described her as the best public speaker of the 20 on stage. She also landed serious blows on Kamala Harris’ record as AG, which were not really countered. Although she’s not near the top of the pack, were Trump suddenly to escalate to war with Iran, her military experience and anti-war position could see her leap in the polls.

Why she might not: Gabbard’s previous positions have been pretty unpopular. Her position on Syria got her labelled as an apologist for Assad, and a Russian stooge. Additionally, she had some former links with anti-gay organisations, although she has since renounced her younger beliefs, and now has a good record on LGBT issues. Yet, if she were to gain in the polls, I would expect a lot of attacks around these to come her way. Finally, a lack of experience on her part suggests that she is unlikely to be chosen this time, even if she does have a strong party future ahead of her.

My % chance of winning: 1%

 

10. Julian Castro

Age: 44
Highest office: Secretary of Housing and Urban Development under President Obama
Home State: Texas
Current polling: 1%

Bio: coming from a political family, both Julian and his twin Joaquin (serving in the House) are notable figures in the democratic party. After serving as mayor of San Antonio, TX from 2009, he joined the Obama administration in 2014 as the Secretary for Housing and Urban Development (HUD), and the youngest member of the cabinet.

Why he could win: as the only hispanic person running, he could gain from other subdivisions of the party being split over multiple candidates. He was largely seen as successful in the first debate, attacking Beto O’Rourke’s border plans as insufficient. Although he is polling quite low, if Trump upped the rhetoric once more on the Mexican border, it could well play into Castro’s hands and push him towards the top.

Why he might not: as with others above, Castro lacks experience somewhat, having never contested a state-wide race, never mind a country-wide one. Despite the advantage of being the only hispanic, that has so far failed to push him much above 1% in any polls, although he could change this with more name recognition. Additionally, his position of decriminalising crossing the border isn’t actually very popular across all Americans. If either Warren or Harris get the nomination, Castro would likely be (with Buttigieg) a top contender for VP. 

My % chance of winning: 1%

In the last article, we looked at how the key to winning a US presidential election is correctly navigating your way around the electoral college, and we ended with looking at the fact that three states (Pennsylvania, Wisconsin and Michigan) swung to Trump after decades of being solidly Democrat. In this article, we’ll look at what happened to cause this.

Our first issue is whether it was more that Trump won the election, or whether Hillary lost it. As Obama won in 2012, Hillary didn’t really need to do anything new, she didn’t need to gain a single state more than he had done and that would make for a comfortable win. As it happened, Hillary lost Wisconsin, Michigan, Ohio, Pennsylvania, Iowa and Florida, without winning any new states. The automatic assumption might be compared to the last time, the total votes for Democrats went down and for Republicans went up. In reality, although Trump ’16 got roughly 2 million votes more than Romney ’12 did, the number of votes for Obama ’12 and Hillary ’16 were almost identical: 65,915,795 to 65,853,514, i.e. Hillary got 99.9% the number of votes Obama four years earlier.

Additionally, Hillary comfortably won in terms of the popular vote, beating Trump by roughly 3 million. So if Hillary won the popular vote, and got the same number of votes as Obama, then the answer lies in the state-by-state changes, and here we see a huge range across the country: at the high end, compared to the number of people voting for Obama ’12, Hillary increased her vote by 23.4% in Utah; on the opposite side, Hillary decreased the vote by 24.9% in North Dakota. Crucially, these swings were not random, so to see how it played out across the country, we can look at the map below.

Firstly, we should not ignore that the good points for Hillary, and a future piece will examine the changing circumstances in places like Texas. However, as this piece is focusing on why Hillary lost, we will only look at where the vote went down. As we can see, 17 of the 50 states saw a substantial drop of at least 10% compared to the previous election, and I’d like to suggest that we can split these 17 states into 3 groups.

1. Unique circumstances

In the first group, we place Hawaii, Vermont and Maine. In Hawaii, one possible reason for the decrease is that Barack Obama was born in Hawaii, and so there was more enthusiasm for a native of their state. When we compare Hillary ’16 to Kerry ’04, Hillary is still up around 35,000 votes (~230k to ~265k), so it’s not so bad. In Vermont and Maine, unlike 2012, which was a 2-way race in each state, 2016 was de facto a 3-way in Vermont and de jure a 3-way in Maine. In Vermont, Hillary got 20,000 fewer votes than Obama ’12, but there were 18,000 write-in votes for local Bernie Sanders. In Maine, Gary Johnson stood for the Libertarian party, receiving 38,000 votes, compared to the 41,000 fewer Hillary got compared to Obama ’12.

All three of these states went blue in both 2012 and 2016; these are interesting changes, but don’t really contribute to the story of why Hillary lost.

2. Deep red states

To start, let’s compare the map above with the map below:

Hillary largely lost votes across the northern states between the coasts, but they show an interesting divide compared to how they voted in 2012. Our second block are those states that are strongly Republican, and consist the northern rockies area (ND, SD, WY, ID, MT), to which we’ll also add Missouri, Mississippi and Western Virginia. These 8 states were primarily strong Republican voters in 2012, and all of them voted Republican in the 5 elections from 2000 to 2016.

There are more nuanced reasons to why each of these saw a fall in democratic votes, but to keep it simple, we can make a safe assumption that a candidate like Hillary Clinton, who represented the epitome of the DNC establishment, isn’t going to be very popular in areas that never vote for Democrats. Either way, all 8 of these states stayed red between 2012 and 2016, so like our 3 ‘unique circumstance’ states, they didn’t cause Hillary to lose.

3. The Rust Belt

For those unfamiliar with the term, the Rust Belt (RB) is a term for an area of the midwest that had high levels of industrial and manufacturing jobs in the post-war boom, but has had a sharp decline in those jobs in the last few decades.

There’s not a strict definition of what does and does not count as the RB, so for simplicity we’ll say it’s the 5 main states that are red in the map (PA, OH, IN, IL, MI) and we’ll stretch it to include Iowa, Wisconsin and Minnesota too.

What’s interesting is when we compare the 2012 vote map with the 2016 democratic change map. Firstly, we can see that this is a region that overall voted comfortably for the democrats in 2012, with seven of the eight (no Indiana) going blue. Secondly, we can see that in another seven of our eight RB states (no Illinois) had a drop in votes, and six (no Pennsylvania) had at least a 10% drop between ’12 and ’16. Thirdly, of the six states that flipped from blue to red and won Trump the election, five are in this region. Finally, even in the two states that did not flip (blue Minnesota and red Indiana), we still saw the same direction of travel as their neighbours, i.e. a Democratic vote drop of over 10%.

So, could it be a coincidence that almost all the states that changed the outcome of the election are contiguous and had the same voting shift? Surely not. A one-layer-deep answer to the answer in the question of this article is that Trump won because the RB went from blue to red. In my opinion, any answer to that question that does not primarily focus on this region simply isn’t paying attention to the numbers.

The above answer, however, still doesn’t address the issue posed earlier: did Trump win because he won the RB, or because Hillary lost it?

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To take a slight shift of gears, let’s look at little at the polling for the 2016. Was this loss in the RB something that pollsters saw coming? Simply, the answer is no. Let’s focus on five of the 8 RB states: Indiana, Michigan, Wisconsin, Ohio and Pennsylvania, all of which Obama won in ’08. It depends how you average the polling, but if you go by the aggregated polling data from the popular site RealClearPolitics, the average poll lead for Hillary by election time was 3.6% in Michigan, but Trump won it by 0.3%. They said Hillary led by 6.5% in Wisconsin, but Trump won by 0.7%. They said Trump would win by  10.7% in Indiana but he really won by 19%. Similar errors were made in PA and OH. And that’s just according to RCP – the team at FiveThirtyEight had slightly different polling averages, so, in a number of them Trump’s under-estimation was even bigger.

Now, a simplistic answer to this is ‘oh, well Hillary wasn’t that popular a candidate, so the polls overestimated her popularity.’ But this wasn’t true nation wide. The predictions pollsters made in New York and Texas were pretty much on the money. And the predictions for California actually underestimated Clinton by about 6 points. So we can’t say that this was just a general failure on the pollsters’ part. The same thing as happened with an unusual voting pattern in the RB also happened with the polls there.

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So, to understand whether Trump won this area or Hillary lost it, let’s take an in-depth look at our five focus states from above (MI, PA, OH, WI, IN). We’ll start with PA, as it’s overall the outlier.

		2012	2016	diff
Pennsylvania	D	2,990,274	2,926,441	-63,833
	R	2,680,434	2,970,733	290,299

Here we can see that this was more of a Trump win than a Hillary loss – he really did a decent job of increasing his vote share compared to Romney ’12. However, in many ways, this state is split and is only a half-RB state. The reason for this can be seen in the rust belt map above. For one, there is the split between the RB and coal belt. But perhaps more importantly, a large part of the population is in right hand edge of the state. Pennsylvania is home to ~12m people, around half of whom live in the greater Philadelphia area alone. Geographically, Philly isn’t RB – it’s basically part of the East Coast area where Hillary kept or increased her vote.

When we break it down on a county-by-county level this seems to hold. In Philadelphia county, Hillary got 99% the vote that Obama did in ’12. However, the picture is different when we look at the centre and left thirds of the state, which are much more in line with the history and geography of the rest of the RB. If we take five counties at random from across those two thirds of PA (Greene, Beaver, McKean, Huntingdon and Lycoming counties) and examine their Democrat vote change from ’12 to ’16, we see exactly what we saw in the rest of the RB: falls from 12% to 24%, averaging 18% overall. This is a very different picture to the average fall of just 2.1% in Pennsylvania as a whole.

Either way, we can say that in total, Trump won Pennsylvania (but Hillary also kind of lost the RB belt part.)

Next, Indiana.

		2012	2016	diff
Indiana	D	1,152,887	1,033,126	-119,761
	R	1,420,543	1,557,286	136,743

This is a little different: the number that Trump increased his vote by was a little higher, but basically around the same amount as the Democratic vote fell by. The number doesn’t tell us if these people switched, or whether Dems didn’t vote this time and non-voters from 2012 did vote for Trump, but we’ll basically call this a draw: Trump won and Hillary lost.

However, this was a red state that stayed red. Let’s now look at WI, MI and OH. Importantly, these three RB states went from blue to red, and between them carried 44 electoral votes. If they had stayed blue, Hillary would have won 271 to 260 (8 electoral votes went to neither candidate).

First, Ohio and Michigan.

		2012	2016	diff
Michigan	D	2,564,569	2,268,839	-295,730
	R	2,115,256	2,279,543	164,287
Ohio	D	2827709	2,394,164	-433,545
	R	2661437	2,841,005	179,568

In both of these states, the number of people who stopped voting Democrat was in the region of double the number of new Republican votes. In Michigan, if Hillary had only lost 95% of the number she did, she would have won. I think it’s fair to say that these two states were Hillary losses more than Trump wins.

Finally, Wisconsin.

		2012	2016	diff
Wisconsin	D	1,620,985	1,382,536	-238,449
	R	1,407,966	1,405,284	-2,682

It’s hard to argue with numbers. Trump lost votes, so it wasn’t that he won the state over at all; Hillary lost over 200,000 voters – not people who changed their mind about which party to vote for, but people who came out to vote for Obama ’12, and just stayed at home when it came to Clinton ’16. This is a clean Hillary loss.

So across the RB, it’s a not a perfectly clean narrative, but overall, it was much more strongly Hillary’s loss than Trump’s win that changed the outcome of the election.

And so we have our two-layer-deep answer to the question of why Trump won: the RB flipped, and it was Hillary’s loss. But it still doesn’t get to the question of why these voters who did vote in 2012 failed to do so in 2016.

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At this point, let’s look at some of the reasons that people attribute to Hillary’s losses in the RB region. A bit of googling comes up with a couple of common arguments.

Disclaimer: from here on, both the arguments from others and from myself start straying away from pure data and start mixing in anecdotal evidence and conjecture. I believe everything above is factual, but from now it is more on the side of opinion. 

The first form of the argument can be found in this article from Politico – it basically revolves around the idea that Hillary had a terrible ground game in a number of states. It tells stories like a volunteer turning up, asking for a yard sign, being told they don’t statistically change the outcome, and her leaving not to return. Voter data collection was poor, and so they couldn’t react to fix issues because they didn’t know what they were.

There is some merit to the idea that ground game played a factor, but it can’t have been the whole picture. Two reasons against this (and a third a bit later): firstly, I don’t think it rings true on a human level. The 2nd Obama election was a less heated affair: the enthusiasm for Obama was a little down from 2008, and he was running against a pretty moderate Republican. Compare that to the divisive 2016 choice. The idea that people who turned out in 2012 decided against turning out to vote against Trump based on not enough yard signs or enough people knocking on their doors doesn’t seem very plausible, even less so when it would have to attribute for more than 1 in 10 Obama ’12 voters. This can’t possibly be the whole picture. In fact, even in the article, the author hints to the fact this can’t be it. They reference the problem that a lack of data collecting “might have… showed the campaign that some of the white male union members they had expected to be likely Clinton voters actually veering toward Trump”. The underlying problem isn’t the campaign didn’t know that these people were veering toward Trump: it’s that the people were changing their mind in the first place. This argument simply fails entirely to address the reasons why people were changing their minds or becoming disillusioned with Clinton herself.

Argument two is about how the pollsters got it all wrong. The Washington Post complains about a large time gap from 2008 made for poor models, and incorrectly predicting the black turnout. A similar argument from American Progress highlights how they got it wrong in the turnout of non-college educated whites. However, this argument is just a higher-level repeat of the first argument: okay, so what if the polls had better modelling and did get both of those groups correct? They would have called the shift correctly, but that doesn’t explain why the shift happened in the first place.

The final argument is similar to the first, but rather than focusing on the Democratic ground game, it focuses on Hillary herself. She had a limited amount of time to visit places, and didn’t come to states like Michigan enough. Like above, we can question the idea that 10% of Obama ’12 voters failed to vote for her because she wasn’t at some point within a few hundred miles of them. But more importantly, it doesn’t hold up to the data: if you look at this map from the Boston Globe, you can see that actually she spent a huge number of her visits in Iowa, and a decent number in Ohio. Yet the fall in vote was consistent across the region, not correlated to her physical presence. Again, I’m not arguing that in-state visits don’t matter, but to chalk the entire thing up to this neither seems particularly convincing nor is backed up by the data.

So if the most common arguments are not correct, what was the underlying reason that caused people to either switch to Trump, or at least to lose enthusiasm with Clinton to the degree that they did not bother turning out to vote? I would like to suggest that it was about the economy, and more specifically how it ties in with issues around international trade and NAFTA.

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Before going into the numbers that I think back my argument up, we’ll first look at little at what NAFTA is, and the history of how trade has affected the RB, or at least how people there perceive it to have affected them.

So what is NAFTA? The North American Free Trade Agreement was the culmination of decades of smaller deals and progress towards a free-trade zone between the USA, Canada and Mexico, and was brought into law in 1994 under Bill Clinton. The effects of the agreement are highly disputed, some saying it was great for America, others that it was terrible, but one indisputable effect was that it led to a lot of jobs being lost in American manufacturing. It’s possible that more jobs were gained that made up for it, but that’s hard to prove either way, and isn’t entirely relevant right now. Let’s focus on the popular idea that factories were closed in the US, and set up in cheaper places like Mexico.

A lot of evidence suggests that perhaps automation played an equal or larger part in the reduction of the role of the manufacturing jobs, but I believe in the public perception, this hasn’t really had an effect on the narrative. Let’s say your town has a 3000 person factory that gets shut down. The owners upgrade and invest in machinery, so when they open the new factory in Mexico, it only employs 1500 people. I would suggest that people are far more likely to say that “we lost 3000 jobs that went to Mexico” than to specify that “we lost 3000 jobs when the factory moved to Mexico, however only half the jobs went to Mexicans, the other half is natural progress of technology and no one got those jobs”. It’s much easier to simplify and blame one thing, both for people in those circumstances, and even more so for the media who may want to push a particular narrative.

Similarly, there is a decent amount of evidence suggesting that perhaps places like China and other south-east asian countries were locations for equal or more jobs that got sent oversea. However, as before, I suspect that it is more likely that people simplify the message, and start using complaints about NAFTA as a short hand for complaints about all jobs lost to foreign countries, as its prominence in the news and being one single location next door, rather than lots of smaller deals over time with a number of far away places, makes it an easier target.

The number of jobs lost to NAFTA, or similar trade issues, or to include with automation, is quick tricky to pin down. One suggestion from the (surely completely unbiased) website ReplaceNafta.org uses figures from the government Trade Adjustment Assistence  schemes to place a number of ~900,000 jobs lost from NAFTA and ~3,000,000 jobs lost from all trade. A paper from the Economic Policy Institute says that between 1993 and 2013, ~850,000 jobs were displaced. The important thing here is not to get bogged down in how many jobs precisely were lost and to where, but the over-arching narrative that a very large number of jobs were lost due to NAFTA, and I suspect a much larger number of lost jobs from surrounding circumstances were attributed to NAFTA than it deserved.

To briefly argue the other side, it is true that the loss of manufacturing jobs didn’t change rate with NAFTA, although it’s important to remember that NAFTA wasn’t a one-off implementation but had decades of smaller deals that led to it. Further statistical arguments can be delved into as to how one point on a flat line doesn’t mean it didn’t matter, but I think I’ll lose my whole audience if I go there.

What we need to focus on is the lasting impact on the overall narrative that these changes left. Today, only around 1 in 3 Americans think that NAFTA is beneficial, and “just 56 percent of Americans think international trade is on the whole good for the country.” With that established, let’s head back to 2016.

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For Hillary Clinton, NAFTA has been a seagull around the neck for quite some time. The fact that it was signed by her husband perhaps put some unfair link between it and her in first place, but she did back it for quite some time. In 2008, Obama repeatedly whacked her with it, to her detriment in the primaries.

So far, we’ve only looked at the numbers around NAFTA, but I would highly recommend a brief detour to look at one town as an anecdote of the human effect of how it changed the course of the election. The piece is an interview with Lou Mavrakis, the mayor of a town that lost 2/3 of its population in the last few decades and the closure of its steel mill in the ’80s. He talks about how anyone publicly supporting Republicans in the past would get rocks through the window. He tried to get attention from the Democrats unsuccessfully to help rescue the town from its problems, but when Trump came there and promised a return of jobs, for the first time yard signs went up supporting the other side.

This is just one story, but it largely weaves in with what other people are saying. Presidential rising star Pete Buttigieg has said that the Democrats have ‘abandoned’ the midwest. The last Democrat to win in Michigan, Gary Peters also points to how failing to win “union members who didn’t trust her position on free trade” really hurt Hillary.

But from the starting position of struggling to get through to midwest voters on NAFTA, Clinton got whacked again on free trade when it came to the Trans Pacific Partnership. This time she got whacked from the left and the right. Bernie Sanders campaigned on opposing “job killing trade agreements like the TPP”, while in debates Trump won points by repeating that Hillary had called the TPP “the gold standard” in trade deals, which she then tried to get out off, which then got her a whole new round of attacks for flip-flopping.

So the theory is that opinions on trade seriously hindered Clinton in 2016 in the RB, but do the data back that theory up? It would seem so. According to RealClearPolitics, exit polling found a very clear divide when asking people whether (A) “international trade more likely takes away American jobs or (B) creates them”. Among voters in group A, Trump had a 34 point margin of victory (65 to 31). But that’s across the US – did people in the RB fall more into group A than B? From the piece:

“the gap between those who think that trade saps jobs and those who think it sustains them was much bigger in the Great Lakes region. Voters viewed trade as bad, rather than good, by 19 points (53 to 34 percent) in Pennsylvania, 16 points (48 to 32 percent) in Ohio, 15 points (50 to 35 percent) in Wisconsin, and 19 points (50 to 31 percent) in Michigan.”

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So finally, let’s link this all back up and see if we have a convincing narrative. If you are a democrat from a region where either you, your family, or your town has seen a considerable loss of jobs in the last few decades, how would you feel when it comes to voting for a candidate who seems to have championed the policies that led to this situation, and seems to be suggesting even more deals to keep this going? Or how would you feel about the man from the other party to your normal vote who is championing killing the TPP, putting up tariffs and promising to bring back jobs? For some, perhaps they thought their best choice was to switch party and vote Republican for the first time in decades. For hundreds of thousands, it looks like they couldn’t stomach either option and simply stayed home on election day.

For those outside the US, and probably not a few inside, the US electoral college might seem an unusual system – why not just let the candidate with the most votes win the election? The reason, simplified, is to avoid people in densely populated areas dominating those in rural areas by weighting them differently. Understanding where to play, therefore, becomes essential in winning or predicting the outcome of the presidential election. In two of the last five elections, the winner of the presidency was not the candidate with the most votes. This means that even if I told you today the exact number of votes each candidate will get in 2020, you still wouldn’t know who the winner is.

This article examines the idea of flipping a state, so that a state that gave votes to your opponent’s party in the last election will give them to your party this time. In simple terms, each state works as a first past the post election, so if you take 48% of the vote versus an opponent’s 46%, you get all the votes from that state (usually). If you want to understand the details of how the electoral college works further, I recommend watching this video and those related to it examining some of its flaws.

Now let’s say you have been nominated the democratic candidate for 2020/ chosen as Trump’s key re-election advisor, and you are only allowed to visit 5 states, how would you decide which ones are your best bet for winning? First, let’s simply examine which states are ‘flippable’ and which rarely change their mind. For the sake of argument, I’ve started with the 1992 election (this is arbitrary as a start date, but the 1988 election was so overwhelming that it is almost misleading to use its figures), and looked at the 6 elections since. If a state switched party every time, it would get a flip score of 6, if it’s been constant for either party, it gets a 0 score. Our flip map since 1992 therefore looks like this:

This immediately makes our electoral strategy focus much sharper. Since 1992, twenty-nine of the fifty states have not once switched their allegiance, and while you can’t take anything for granted, there’s no logic in focusing on one of those over states like Florida, which has flipped 4 times since 1992.

Now this doesn’t show an accurate picture if we’re looking only to predict what will happen in 2020. Take for example Missouri, Arkansas and Louisiana: all three states voted Democrat in ’92 and ’96, but all have been fully Republican in the five subsequent elections. In 2016, Trump beat Clinton by more than 20 points in each of the three states, so it would be pretty reasonable to assume that they won’t be swing states in contention in 2020. So let’s pull the time-frame in a little closer, this time starting in 2004, so giving each state a maximum flip score of three.

At this point, we’re down to only twelve states out of fifty that seem to be worth examining for our strategy for 2020. And if we do a single step more, Nevada, Colorado, New Mexico and Virginia all flipped between 2004 and 2008, and have been the same for the last 3 elections. That brings us down to 8 states that are most likely for our hypothetical democrat to be able to flip, or for Trump to focus on holding.

Now, there are two key factors to examine if we wanted to predict all eight of those today: the starting point and the direction of travel. Our starting point is the percentage of voters who voted Trump minus the number who voted Clinton – and, of course, note that all 8 of these recent swing states went for Trump in 2016. With this basic calculation, we can rule out three of the 8 as too difficult to swing: Trump crushed Clinton in Indiana by 19%, so it’s very unlikely to be taken back (this isn’t too surprising: other than Obama’s first election, it’s been Republican every election since 1992); and two lesser but still strong results – Iowa by 9.4% and Ohio by 8.1%.

Our final five show much closer margins:

North Carolina – 3.6%
Florida – 1.2%
Wisconsin – 0.7%
Pennsylvania  – 0.7%
Michigan – 0.3%

Since we know those starting points, we should also consider the direction of travel: how have  recent 2-term presidents done in their first election vs their second? With few data points over time, it’s hard to gather meaningful trends on this, but it seems to be declining over the last few decades. Reagan got 8% higher share in his second run, Clinton was down to 6%. H W Bush still went up, but only by 2%, and Obama went down by 2%. Now, the entire point of this article is to focus on specific places, not a flat percentage shift over the whole country, but assuming there is an equal shift, just 1% down for Trump in 2020 could mean him losing Wisconsin, Pennsylvania and Michigan, as above, and with that, the electoral college would crown his opponent the winner.

Taking our 8 states that have flipped in the last three elections, we also need to consider their electoral vote count. Hilary Clinton got 232 votes in 2016 (538 total, 269 to draw, 270 to win). Therefore, assuming all else stays the same, 38 more votes are needed for a Democrat to win in 2020.

As above, Iowa is probably already out of contention, but its six electoral votes means it wasn’t too important anyway. If the 2020 Democrat takes Florida’s 29 votes, that puts them at 259, so Wisconsin would make it a draw, and any of the other 5 would put them over.  It’s worth mentioning here that in 2016, Clinton only narrowly took New Hampshire  (by 0.3%), and it did go Republican as recently as 2000 and is worth only 4 electoral votes.  But as above, if Florida and and Wisconsin bring it to 269 each, it could be a tiny state like this that makes all the difference.

Now, there is one final thing to examine to have the full picture: at the start of this article, we assumed that we shouldn’t target states that haven’t previously flipped in the last seven elections. But as some states become less swing-y over time, some states that were once solid can suddenly become swing states. We looked at 1992 to 2016, and 2004 to 2016, but 2016 itself was a very unusual election. The three states we have just decided are the most swingable in 2020 (WI, PA, MI), were not considered likely swing states before 2016: all three voted Democrat in all six elections up to 2012.

So what happened? These were not states that were in close contention after Obama – he won them all both times by around 10% each time.

We’ll examine what happened in the next article: why did Trump win 2016?