Category Archives: Hillary Clinton

Structural Model Regression Output

Democratic Vote Share Structural Model
Dependent variable:
Adjusted R20.94
Residual Std. Error0.03 (df = 188)
F Statistic222.02*** (df = 15; 188)
Note:*p<0.1; **p<0.05; ***p<0.01

Electoral Map 2016 — Structural Model

Electoral Map 2016: The Structural Model

PoliticalEdu is developing three electoral models for 2016.  The first, the structural model, takes data from the 2000, 2004, 2008, and 2012 presidential elections to run a linear regression that determines the relationship between a handful of variables, including state demographics, and number of Democratic public officials, and the Democratic vote share.  It is developed by averaging two approaches: one which ignores candidate favorability and a second which includes in the regression the difference between Hillary Clinton and Donald Trump’s net favorability (the results from those models can be found here and here.  Clearly, Trump’s historically low favorability ratings could potentially cost him the election).

The structural model assesses the underlying electoral landscape separate from campaign actions.  By accounting for factors such as the state partisan voter index (developed by the Cook Political Report), the percent of House seats occupied by a Democrat, and region, we can understand how states are inclined to vote without campaign activities or candidate quirks.  Of course, considering Clinton and Trump have high unfavorable ratings, a pure structural analysis will likely miss the mark (hence averaging it with a structural model that includes favorability).  We have also developed a state battleground model to analyze poll results.

The structural model serves as a baseline.  We can expect these, or similar, results if the campaign ended today.  Between now and November 8, one variable will be adjusted: the difference between Clinton and Trump’s net favorabilities.  Numbers are from Gallup.

Overall, the model explains around 94 percent of the vote share variation during the four elections.

Predicting third party candidate vote shares is difficult because they fared poorly in previous elections, but polls indicate 2016 will be different.  Regression models won’t work.  Instead, using a Libertarian and Green Voter Index, vote shares for Gary Johnson and Jill Stein can be modeled.  The voter indices approximate each state’s inclination to vote for a Libertarian/Green Party candidate by taking state results from the past four elections and dividing them by the LP/GP national result.  This index can then be multiplied by Johnson and Stein’s national polling average to estimate their vote share in any given state.

An example should clarify the method (the following numbers are all made up): Say in Alabama the Libertarian candidate received 0.5% in 2000, 0.25% in 2004, 1% in 2008, and 2% in 2012.  Nationally, that candidate earned 1% in 2000, .50% in 2004, 1.5% in 2008, and 3% in 2012.  The index for each year is 0.5, 0.5, .67, and .67.  Averaging the four, Alabama would have a Libertarian Vote Index value of 0.59.  To estimate Gary Johnson’s 2016 vote share in Alabama, I multiple 0.59 by his national polling average (which I have weighted to account for pollster accuracy and date).

With a Libertarian and Green Party candidate included, Clinton and Trump vote shares need to be adjusted.  To determine how much to subtract from each, I find the difference in polling averages between the weighted Clinton vs. Trump average and the weighted Clinton vs. Trump vs. Johnson vs. Stein polling averages.  From there, I divide the difference between each candidate’s polling average by the total number of percentage points lost between Clinton and Trump.  Their initial vote share estimates are then subtracted from the difference quotient multiplied by expected Johnson and Stein vote shares.

These values will obviously change as Johnson and Stein’s poll numbers fluctuate and the difference between the two polling averages changes.  As such, this model will be updated weekly (assuming new polls are released during the week).

Including Johnson, this is the electoral map 2016:


electoral map 2016


The map belies the closeness of many states.  Here is a table of states that could very easily change the election.

Clinton +5-7.5Clinton +2.5-4.9Clinton +0-2.4
New HampshireOhio
Trump +0-2.4Trump +2.5-4.9Trump +5-7.5
North CarolinaIndiana

This post will be updated!

can trump win

Can Trump Win? Yes, Very Easily

Can Trump Win the Presidency?

Democrats are convinced that Donald J. Trump will not be elected president.  And they have good reason for that belief: Trump has managed to insult many crucial demographic groups, most notably Latinos and women.  But Democratic thinking mimics that of Republican elites nearly 10 months ago.  Remember when all GOP candidates and many elected officials stated that Trump would not become the nominee?  Such cocksure statements ultimately proved to be false.  Trump wantonly attacked 2008 Republican nominee John McCain because he was captured in war, compared Ben Carson to a child molester, ceaselessly harassed Lindsey Graham, brazenly dismissed the last Republican president (George W. Bush), insinuated that Ted Cruz’s father took part in John F. Kennedy’s assassination, and assailed 2012 Republican nominee Mitt Romney.  Yet he won.

What makes Democrats so sure that Trump won’t win the general election?  Yes, he has a foot-in-mouth habit, flip-flops constantly, and puts forth absolutely no effort in learning public policy, but none of that has mattered.  No ideological attacks have changed his poll numbers.  No debate attacks over his conservative bona fides or outlandish policy ideas diminished his chances of winning the nomination.  In fact, through it all, Trump supporters — a true cult — fell deeper and deeper for their illiberal candidate.  Why would that change for the general election?  Better yet, why, given his many missteps and poor standing among Latinos and women, can Trump win?

All it takes is one event over the next 5.5 months and all those laughing when asked “can Trump win?” will spend election night pondering where they went wrong; all it takes for Trump to become president is one event.

That event is a domestic terrorist attack.

Prior to the Paris and San Bernardino attacks, Trump’s poll numbers had started to stagnate and even dip.  However, following the terrorist strikes and his Muslim ban proposal, his numbers rocketed.  The chart below shows his poll numbers from the beginning of November through the end of 2015 (he soared almost 10 points, or 40 percent, in that time frame).

trump poll numbers
Source: RealClearPolitics

For some reason, a man with no foreign policy experience — a man who touts being the Grand Marshall of a parade as pro-Israel credentials and has cited hosting beauty pageants in foreign countries as international experience — is viewed as tough on terrorism.  That’s true beyond just Republican voters.  A domestic terrorist attack could very well provide Trump with an irreversible boost in the polls, one which would flip the current electoral standing.

Here’s the scary part: ISIS has every reason to encourage a lone-wolf terror attack in the United States before the general election.  Trump is a boon to ISIS’s recruitment: ISIS thrives on an incorrect notion that the West is at war with Islam.  But Trump almost makes that idea correct.  His want to ban Muslims from the country and register Muslims citizens here (when asked about how that idea differed from Hitler’s Jew registry, Trump responded “you tell me”) lends weight to the (incorrect) idea that Western democrats and individuals despise Islam and want to see it eliminated.  Using Trump and his policy ideas in recruitment advertisements and videos will help ISIS find new members.

ISIS leaders are not dumb.  They understand politics and surely know that a Trump presidency would strengthen their standing.  And I have to imagine they realize that the best way of electing Trump would be to launch or encourage a domestic terror attack.

As seen in Brussels, terrorist strikes are frighteningly easy.  There are many vulnerable points in American mass-transit systems.  A strike in any of those spots would result in numerous casualties and surely would succeed in terrorizing the nation, pushing undecided voters into Trump’s camp given his (horrendously flawed) image as a tough man.

One terrorist attack and an illiberal politician whose policies could well push America on a road to proto-fascism may be swept into the Oval Office.

We need to defeat Trump early — Democrats need to destroy his candidacy before he destroys them (and the country).  That means super PACs need to front-load advertisements; the Clinton campaign needs to do the same.  Bernie Sanders, if he insists on staying in the race, needs to focus his ire on Trump, not Clinton.  Rank and file Democrats need to volunteer and donate to the party and its presumptive nominee early so the party can destroy Trump’s poll numbers and standing with voters.

Trump needs to be put down right away; otherwise, the uncertainty of the next 5.5 months might be a boon to his candidacy.

So, can Trump win?  Yes, and very easily.

wisconsin democratic primary predictions

Wisconsin Democratic Primary Predictions

We’re back with our Democratic prediction model, which fared very well during Western Saturday (it correctly predicted the winner in each of the Alaska, Hawaii, and Washington caucuses and its vote share estimates also fell close to the actual results).  While those results likely did not change the trajectory of the race, they have certainly infused Bernie Sanders with momentum: In the past week, Wisconsin polls flipped from having Clinton up 6 points to Sanders being up an average of 5 points.

Our Wisconsin Democratic primary predictions show two different (and simultaneously expected) results.  The table below depicts win probabilities for the two candidates.  It largely aligns and mimics the polls — Sanders has a clear advantage and is indubitably favored, but not overwhelmingly so (a win probability one would expect with a candidate leading the polls by just more than the margin of error).

Hillary Clinton Win Probability

Bernie Sanders Win Probability


However, the vote share model tells a different story.  The vote share Wisconsin Democratic primary predictions point to a decisive, landslide victory for Sanders.  Our vote share model relies heavily on demographics and those of Wisconsin trend favorably to Sanders — the state is overwhelmingly white (82 percent) with a very small African American and Hispanic population (6 and 5.6 percent, respectively).  These demographics are similar to those of Minnesota, a neighboring state which Sanders handily won (with 62 percent of the vote; Minnesota also favored Sanders because it was a caucus).  Sanders fares very well with white voters and their large presence in the state’s electorate leads to the model advantaging him in the primary.  In other words, if he’s to make up the delegate gap, Wisconsin is very favorable terrain to net a large number of them.

Hillary Clinton Vote Share

Bernie Sanders Vote Share


Will our predictions bear out?  Based on polls, it seems so, though given Sanders’ recent momentum and financial resources (which could fund a substantial last-minute ad blitz), it would not be surprising to see Sanders win by slightly larger margins.  Considering that Wisconsin is 82 percent white, the predicted margin is actually rather disappointing for Sanders – favorable demographics in a medium sized state offer him an increasingly rare opportunity to pick up a large amount of delegates and begin to meaningfully close his deficit.  We predict the below delegate allocation:

Hillary Clinton Delegate Expectation

Bernie Sanders Delegate Expectation


These targets, again, seem reasonable given the polls.  If Sanders earns more than 46 delegates from the primary, it will be a good day for him.  If he passes 50, it will be a very good day for Sanders (though, unless indicative of beating polls and expectations, the single victory here will not alter any race dynamics).

As always, take these numbers with grains of salt as they reflecting underlying electoral conditions, not the campaigns or the candidates or momentum or news, etc.  These estimates may well be wrong (we fully admit that) and in the case they are, we’ll go right back to the drawing board to refine and edit our models.  Any comments about these forecasts or our models are welcomed!

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