OK, we can all agree that the November election result was a shocker. According to news reports, even the Trump campaign team was stunned to come up a winner.

So now seemed like a good time to go over various theories floating around in political science and political reporting and see where they stand, now that this turbulent political year is drawing to a close. By the time I was done writing it up for Slate, I came up with 19 lessons learned. I thank my colleague Bob Erikson for help on some of these.

1. The party doesn’t decide.

We can start with the primaries, which destroyed the Party Decides theory of Marty Cohen, David Karol, Hans Noel, and John Zaller, who wrote in 2008 that “unelected insiders in both major parties have effectively selected candidates long before citizens reached the ballot box.” You can’t blame authors of a book on political history–its subtitle is “Presidential Nominations Before and After Reform”–for failing to predict the future. But it does seem that the prestige of the Party Decides model was one reason that Nate Silver, Nate Cohn, Jonathan Chait, and a bunch of other pundits not named Nate or Jonathan were so quick to dismiss Donald Trump’s chances of winning in the Republican primaries.

Indeed, I myself was tempted to dismiss Trump’s chances during primary season, but then I read that article I’d written in 2011 (http://campaignstops.blogs.nytimes.com/2011/11/29/why-are-primaries-hard-to-predict) explaining why primary elections are so difficult to predict (multiple candidates, no party cues or major ideological distinctions between them, unequal resources, unique contests, and rapidly-changing circumstances), and I decided to be careful with any predictions.

2. That trick of forecasting elections using voter predictions rather than voter intentions? Doesn’t work.

Economists David Rothschild and Justin Wolfers have argued that the best way to predict the election is not to ask people whom they’ll vote for, but rather ask whom they’ll think will win (http://www.nytimes.com/2012/11/02/us/politics/a-better-poll-question-to-predict-the-election.html). Their claim was that when you ask people whom they think will win, survey respondents will be informally tallying their social networks, hence their responses will contain valuable information for forecasting. When this idea was hyped back in 2012, I was skeptical (http://themonkeycage.org/2012/11/people-can-predict-elections-even-when-polls-cant/#comment-37868), taking the position that respondents will be doing little more than processing what they’d seen in the news media, and I remain skeptical, following a 2016 election that was a surprise to most.

3. Survey nonresponse is a thing.

It’s harder and harder to reach a representative sample of voters, and it’s been argued that much of the swing in the polls is attributable not to people changing their vote intention, but to changes in who responds or doesn’t respond. In short, when there is good news about a candidate, his or her supporters are more likely to respond to polls. Doug Rivers, David Rothschild, Sharad Goel, and I floated this theory following some analysis of opinion polls from 2012 (http://www.stat.columbia.edu/~gelman/research/published/swingers.pdf), and it seems to have held up well during the recent campaign season (http://www.slate.com/articles/news_and_politics/politics/2016/08/don_t_be_fooled_by_clinton_trump_polling_bounces.html)

The only hitch here is that the differential nonresponse story explains variation in the polls but not the level or average shift. The final polls were off by about 2 percentage points (http://statmodeling.stat.columbia.edu/2016/11/09/explanations-shocking-2-shift/), suggesting that, even at the end, Trump supporters were responding at a lower rate than Clinton supporters.

4. The election outcome was consistent with “the fundamentals.”

Various models predict the election outcome not using the polls, instead using the national economy (as measured, for example, in inflation-adjusted personal income growth during the year or two preceding the election) and various political factors. In 2016 the election was growing slowly but not booming (a mixed signal for the voters), the incumbent party was going for a third term in office (traditionally a minus, as voters tend to support alternation), and the Republicans controlled both houses of Congress (a slight benefit for the Democrats in presidential voting, for that minority of voters who prefer party balancing), and, on the left-right scale, both candidates were political centrists relative to other candidates from their parties. This information can be combined in different ways: Running a version of the model constructed by the political scientist Doug Hibbs, I gave Hillary Clinton a forecast of 52 percent of the two-party vote (http://www.slate.com/articles/news_and_politics/politics/2016/08/why_trump_clinton_won_t_be_a_landslide.html). Fitting a similar model but with slightly different parameters, political scientist Drew Linzer gave Clinton 49 percent (https://pkremp.github.io/report.html). In October the political science journal PS published several articles on forecasting the election, including one from Bob Erikson and Chris Wlezien who concluded, “the possibility of greater campaign effects than we typically observe should constrain our confidence in the predictions presented here.” (https://www.cambridge.org/core/journals/ps-political-science-and-politics/article/div-classtitleforecasting-the-presidential-vote-with-leading-economic-indicators-and-the-pollsdiv/8212BC860F9BAF1570EBE2B8CF603709/core-reader)

All these fundamentals-based models have uncertainties on the order of 3 percentage points, so what they really predicted is that the election would not be a landslide. The actual outcome was consistent with these predictions. That said, a wide range of outcomes–anything from 55-45 to 45-55–would’ve jibed with some of these forecasts. And the non-blowout can also be explained by countervailing factors: Perhaps Trump was so unpopular that anyone but Clinton would’ve destroyed him in the general election, and vice versa. That seems doubtful. But who knows.

5. Polarization is real.

Democrats vote for Democrats, Republicans vote for Republicans. It’s always been thus—what would the party labels mean, otherwise—but cross-party voting keeps declining, and members of the out-party hold the president in lower and lower esteem. Consider, for example, Donald Trump’s criticism of Barack Obama during the presidential debates. Obama is popular so this might seem to have been a mistake to stand against him—but Obama is deeply unpopular among Republicans, especially those Republicans who are likely to vote.

A corollary of polarization is that, if there aren’t many people in the middle to be persuaded, it makes sense for candidates to focus on firing up their base, and this is a key part of the story of the success of the Trump campaign. You can bet that activists of both parties will have learned this lesson when 2020 comes along.

6. Demography is not destiny.

We’d been hearing a lot about how the Republican party, tied to a declining base of elderly white supporters, needs to reassess. For example, here’s Jamelle Bouie in Slate, under the heading, “It Lost Black Voters. Now It’s Losing Latinos. What’s Left Is a Broken, White GOP” (http://www.slate.com/articles/news_and_politics/cover_story/2016/10/trump_and_the_gop_are_alienating_latinos_the_way_they_once_alienated_black.html): “The latest tracking poll from Latino Decisions shows Republican nominee Donald Trump with 16 percent support, versus 74 percent for Hillary Clinton. Looking ahead to November, the group expects that electorate to cast the vast majority of its votes for Clinton, 82 percent to 15 percent for Trump, which would be the most lopsided total in history.” According to exit polls, the Latino vote ended up dividing 66%-28%, a clear Clinton lead but nothing like the forecast from Latino Decisions—a forecast that should’ve been suspect, given that it contradicted the organization’s own polls! Longer term, it may well be that the Republican party needs to change with the times, but destiny hasn’t happened yet.

7. Public opinion does not follow elite opinion.

Perhaps the most disturbing theoretical failure of political science is the general idea that voters simply follow elite opinion. This worked in 1964 to destroy Goldwater, for instance. Or so the story goes. The implication is that voters had to be told Goldwater was scary. They could not figure it out for themselves.

In 2016, Trump was opposed vigorously as dangerous, incompetent, xenophobic, tyrannical, and unhinged, by almost everybody in elite circles: most of his Republican primary opponents at one time or another, a large number of conservative intellectuals, former Republican candidates Romney and McCain, the various Bushes, the media, almost all newspaper editorialists including those that were reliable Republican supporters, all Democrats, about 10 Republican senators, and even some pundits on Fox News. Further, Trump’s breaking of all the standard niceties of politics was there for all to see for themselves. But half the voters said, we go with this guy anyway. The falcon no longer hears the falconer,” as W. B. Yeats put it.

8. There is an authoritarian dimension of politics.

Political scientists used to worry about authoritarianism within the electorate. Mainstream politicians, ranging from Republicans on the far right to lefties such as Sanders, tend not to go there. Trump did. In doing so he broke the rules of politics with extreme comments about his opponents, etc., that are hard to forget. But a significant segment of the electorate, maybe 20 percent, have always been waiting for its authoritarian champion on what we now call the alt-right dimension. There had not been one in the modern era. Trump’s absolute dominance of the political news for over a year signifies this uniqueness. There had been others with this sort of appeal—Joe McCarthy (http://statmodeling.stat.columbia.edu/2016/06/08/donald-trump-and-joe-mccarthy/), George Wallace—but they never came close to becoming our national leader.

9. Swings are national.

When you look at changes from one election to the next, the country moves together. If you plot vote swings by county, or by state, you see much more uniformity in the swing in recent years than in previous decades (http://statmodeling.stat.columbia.edu/2009/01/14/state-by-state/). The swing from 2012 to 2016 was also close to uniform. There’s been lots of talk of Pennsylvania, Michigan, and Wisconsin, and these three states did make the difference in the electoral college, but similar swings happened all over the country. To put it another way, nonuniform swings were essential to Trump’s win, but looking at public opinion more broadly, the departures from a national swing were small, and consistent with the increasing nationalization of elections in recent decades.

10. The ground game was overrated.

The Democrats were supposed to be able to win a close election using their ability to target individual voters and get them out to the polls. But it didn’t happen this way. The consensus after 2016, which should’ve been the consensus earlier: Some ground game is necessary, but it’s hard to get people to turn out and vote, if they weren’t already planning to.

11. News is siloed.

For years we’ve been hearing that liberals hear one set of news, conservatives hear another, and moderates are being exposed to an incoherent mix, so that it’s difficult for anyone to make sense of what everyone else is hearing. There have always been dramatic differences of opinion (consider, for example, attitudes toward civil rights in the 1950s and the Vietnam war in the 1970s) but research on public opinion has shown an increase in partisan polarization in recent decades. The 2016 election, with its sharp divide between traditional news organizations on one side and fake news spread by Twitter and Facebook on the other, seems like the next step in this polarization.

It’s the political version of Moore’s Law, which says that every time the semiconductor manufacturers have run out of ways to squeeze more computing power on a chip, they come up with something new. Whenever it starts to seem like there’s no more room for Americans to polarize, something new comes up—in this case saturation of social media by fake news, along with a decline of the traditional TV networks and continuing distrust of the press.

12. The election wasn’t decided by shark attacks.

Political scientists Chris Achen and Larry Bartels have argued that voters are emotional and that elections can be swayed by events such as shark attacks that should logically be irrelevant to voting decisions. Others have analyzed data and claimed to find that close elections can be decided by the outcomes of college football games (with happy voters being more likely to pull the lever for the incumbent party’s candidate). Others have reanalyzed these data and found no such effect (http://statmodeling.stat.columbia.edu/2016/10/29/no-evidence-shark-attacks-swing-elections/). What does 2016 say about all this? Not much.

You can’t prove a negative so it’s possible that irrelevant stimuli could have made all the difference. But the big stories about this election were that (a) lots of bad information about Donald Trump did not sway much of the electorate, and (b) Clinton’s narrow Electoral College loss may well be attributed to FBI leaks, which were relevant to the voting decision in reminding voters (perhaps inappropriately) of concerns about her governing style. The 2016 election was not about shark attacks or football games but rather about big stories that didn’t matter much, or canceled each other out.

13. Overconfident pundits get attention.

From one direction, neuroscientist Sam Wang gave Hillary Clinton a 99 percent chance of winning the election; from the other, cartoonist and jar opener (http://statmodeling.stat.columbia.edu/2011/04/16/dilbert_update/) Scott Adams gave 98 percent odds in favor of Trump. Looking at it one way, both Wang and Adams were correct: Clinton indisputably won the popular vote while Trump was the uncontested electoral vote winner. After the election, Wang blamed the polls, which was wrong. The polls were off by 2 percent, which from a statistical standpoint wasn’t bad. Indeed this magnitude of error was expected from a historical perspective (http://statmodeling.stat.columbia.edu/2016/11/11/david-rothschild-sharad-goel-called-probabilistically-speaking/), even if it did happen to be consequential this time. The mistake was not in the polls but in Wang’s naive interpretation of the polls which did not account for the possibility of systematic nonsampling errors shared by the mass of pollsters, even though evidence for such errors was in the historical record. Meanwhile, Adams explains Trump’s victory as being the result of powers of persuasion, which might be so but doesn’t explain why Trump received less than half the vote, rather than the landslide that Adams had predicted.

I continue to think that polling uncertainty could best be expressed not by speculative win probabilities but rather by using the traditional estimate and margin of error. Much confusion could’ve been avoided during the campaign had Clinton’s share in the polls simply been reported as 52 percent of the two-party vote, plus or minus 2 percentage points.

There’s a theory that academics such as myself are petrified of making a mistake, hence we are overcautious in our predictions; in contrast, the media (traditional news media and modern social media) reward boldness and are forgiving of failure. This theory is supported by the experiences of Sam Wang (who showed up in the New York Times explaining the polls after the election he’d so completely biffed, http://www.nytimes.com/2016/11/19/opinion/why-i-had-to-eat-a-bug-on-cnn.html) and Scott Adams (who triumphantly reported that his Twitter following had reached 100,000).

14. Red state blue state is over.

Republicans have done better among rich voters than among poor voters in every election since the dawn of polling, with the only exceptions being 1952, 1956, and 1960, which featured moderate Republican Dwight Eisenhower and then moderate Democrat John Kennedy. Typically the upper third of income votes 10 to 20 percentage points more Republican than the lower third. This was such a big deal that my colleagues and I wrote a book about it! (http://press.princeton.edu/titles/9030.html) But 2016 was different. For example, here are the exit polls (http://www.cnn.com/election/results/exit-polls): Clinton won 53 percent of the under-$30,000 vote and 47 percent of those making over $100,000, a difference of only 6 percentage points, much less than the usual income gap. And we found similar minimal income-voting gradients when looking at other surveys. Will the partisan income divide return in future years? Will it disappear? It depends on where the two parties go. Next move is yours, Paul Ryan.

15. Third parties are still treading water.

The conventional wisdom is that minor parties are doomed in the U.S. electoral system. The paradox is that the only way for a minor party to have real success is to start local, but all the press comes from presidential runs. Anyway, 2016 seems to have confirmed conventional wisdom. Both major parties were highly unpopular, but all the minor parties combined got only 5.6 percent of the vote. On the other hand, 5.6 percent is a lot better than 1.7 percent (2012), 1.4 percent (2008), 1.0 percent (2004), or 3.7 percent (2000).

Glass half full is that minor parties are starting to get serious; glass half empty is that not much bloomed even in such fertile soil.

16. A working-class pundit is something to be.

Filmmaker and political activist Michael Moore gets lots of credit for writing, over a month before the election (http://michaelmoore.com/trumpwillwin/), an article entitled “5 Reasons Why Trump Will Win,” specifically pointing to the Rust Belt, angry white men, voter turnout, and other factors that everybody else was writing about after the election was over. Moore even mentioned the Electoral College. And unlike the overconfident pundits mentioned above, Moore clearly stated this as a scenario (“As of today, as things stand now, I believe this is going to happen …”) without slapping a 98 or 99 percent on to it.

What if Hillary Clinton had won 52 percent of the two-party vote and a solid Electoral College victory? Would we now be hearing from pundits with a special insight into white suburban moms? Maybe so. Or maybe we’d still be hearing about the angry white male, since 48 percent of the two-party vote would still be a lot more Trump support than most were expecting when the campaign began.

17. Beware of stories that explain too much.

After the election, which shocked the news media, the pollsters, and even the Clinton and Trump campaigns, my colleague Thomas Basboll wrote that “social science and democracy are incompatible. The social sciences conduct an undemocratic inquiry into society. Democracy is an unscientific way of governing it.” (http://secondlanguage.blogspot.com/2016/11/the-liberal-arts-of-being-ruled.html)

Maybe so. But Basboll could’ve written this a few days before the election. Had the election gone as predicted, with Clinton getting the expected 52 percent of the two-party vote rather than the awkwardly distributed 51% that was not enough for her to win in the Electoral College, it still would’ve been true that half of American voters had refused to vote for her. So there’s something off about these sweeping election reviews: even when you agree with the sentiments, it’s not clear why it makes sense to tie it to any particular election outcome.

The Republicans have done well in political strategy, tactics, timing, and have had a bit of luck too. One party right now controls the presidency, both houses of Congress, most of the governorships, and soon the Supreme Court. But when it comes to opinions and votes, we’re a 50/50 nation. So we have to be wary of explanations of Trump’s tactical victory that explain too much.

18. Goldman Sachs rules the world.

This theory appears to still hold up. Goldman Sachs candidate Hillary Clinton managed to lose the electoral vote, but Goldman Sachs Senator Chuck Schumer may now be the most powerful Democrat in Washington, while former Goldman Sachs executive Steve Bannon will be deciding strategy inside the White House. So it looks like the banksters are doing just fine. They had things wired, no matter which way the election went.

19. The Electoral College was a ticking time bomb.

Yup.

P.S. More here.