Princeton Election Consortium

A first draft of electoral history. Since 2004

Is Nate Silver a little too excited about his model?

September 9th, 2014, 7:06am by Sam Wang



I guess when you’re the King of the Nerds, you have to be willing to engage in a little trash talk. I think this is a good time to administer a lesson in probability* – and also question who is doing the “heavy favoring” around here. [*see postscript - Sam] [Read more →]

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A quick note on the PEC Senate model

September 4th, 2014, 9:06pm by Sam Wang


[Update, Friday 1:00pm: The Election Day prediction now takes into account the new Kansas Senate race, scoring it as a tie.]

Welcome, new readers! Washington Post, Reddit, Krugman readers…great to see you all. I just wanted to make a few quick notes to orient everyone as to what’s going on here at PEC. We’re a bit topsy-turvy because of the Kansas Senate race. We hope to recover soon.

The main thing to know about PEC’s calculations is that we only use polling data. This approach led us to have a perfect record of Senate forecasting in 2012. In 2010, we missed one race – the Nevada Reid-vs.-Angle race. Our track record is excellent.

We do not use “fundamentals” at all, as practiced by The Upshot, The Monkey Cage, or FiveThirtyEight. To learn more about why this matters, read my June piece in POLITICO. In 2012 I argued that fundamentals are useful research tools, but may be unsuitable for everyday forecasting.

The banner above lists two probabilities. The first number is a “snapshot” view of current polling conditions. It states how an election held today would turn out. It takes into account the new Orman(I)-vs.-Roberts(R) matchup in the Kansas Senate race. In an election held today, Democrats+Independents would control the chamber with 90% probability.

The second number is an Election Day probability – a real prediction of Democratic+Independent control in the November election. it is based on treating the snapshot as a random walk that has fluctuated from day to day since June. I won’t get into it now, but here’s how it worked in the 2012 Presidential race.  Based on this approach, the Election Day probability of Democratic/Independent control is 65%.

However, the Election Day prediction does not take into account yesterday’s developments in the Kansas race. If Kansas were redefined as a tossup race, the Election Day probability of Democratic/Independent control would rise to between 70% and 85%. I am thinking about how (and whether) to implement that.

→ 32 CommentsTags: 2014 Election · Senate

Game change: Kansas Democrat drops out of Senate race

September 3rd, 2014, 8:57pm by Sam Wang


[Update, Thursday 9:45am: see my new piece at The New Yorker.com. -SW]

Chad Taylor (D) just dropped out of the Kansas Senate race. I declare this the political news of the week. To understand why, read my essays here (The New Yorker) and here (PEC). Basically the probability of Democratic control of the Senate is about to pop up by 20-30 percent.
[Read more →]

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Brief update

August 30th, 2014, 7:33am by Sam Wang


Thanks for your feedback. The comment thread from the previous post clarified my thinking. Drew Linzer dropped in! Also, welcome to Rachel Maddow viewers.

The banner at the top of the page gives the poll-based “snapshot probability” for who would end up controlling the Senate based on an election held today. Based on PEC’s track record since 2004, this will move toward the final outcome in the coming weeks.

Long-term forecasting is based on methods that worked nearly perfectly in 2010-2012. We will soon install code to display the long-term forecast, which is also based purely on polls. Currently, the long-term forecast for Democratic control on Election Day is 65%, about 2-1 odds in favor.

→ 44 CommentsTags: 2014 Election · Senate

Senate Democrats are outperforming expectations

August 28th, 2014, 9:42am by Sam Wang


[Note: this  is a work in progress. I'm basically seeking comment as I develop a November predictive model. Please give your feedback... -Sam]

I’ve been asked why the PEC Senate poll snapshot is more favorable to Democrats than forecasts you’ll find elsewhere: NYT’s The Upshot, Washington Post’s The Monkey Cage, ESPN’s FiveThirtyEight, and Daily Kos. All of these organizations show a higher probability of a Republican takeover than today’s PEC snapshot, which favors the Democrats with a 70% probability.

Today I will show that in most cases, added assumptions (i.e. special sauce) have led the media organizations to different win probabilities – which I currently believe are wrong. I’ll then outline the subtle but important implications for a November prediction. [Read more →]

→ 84 CommentsTags: 2014 Election · Senate

Could a Kansas independent shift control of the Senate?

August 27th, 2014, 2:36pm by Sam Wang


Normally, both Kansas Senate seats are deep red: one’s been Republican since Franklin Roosevelt was President, and the other one dates back to Woodrow Wilson. So it’s not surprising that even though incumbent Senator Pat Roberts has an abysmal 27% job approval rating, polls indicate that he would still beat his Democratic opponent, Chad Taylor. However, there’s a third option: independent Greg Orman. And a recent PPP survey indicates that Orman could beat Roberts one-on-one.

This is especially interesting because in the current polling snapshot, Republicans are most likely to control 50 or 51 seats. But what if a seat that is >90% likely to go red were suddenly to go to an independent? Check out the rest of the story here. (Then comment below.)

Update: I have more comments below:  [Read more →]

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GOP governors pay a price for blocking the ACA

August 22nd, 2014, 9:36pm by Sam Wang


It’s a part of the GOP mantra to oppose the Affordable Care Act (also known as Obamacare) in all its forms. But does that pay off at the local level? I’ve been analyzing governor’s races around the country, and I found a surprise. I wrote about it today for The New Yorker.

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A wave election…or a ripple?

August 19th, 2014, 2:00pm by Sam Wang


The chairman of the National Republican Campaign Committee is confident that this November he expects a wave election. Is this true…or political trash talk? I weigh in at The New Yorker. It’s my first piece for them. Check it out!

→ 13 CommentsTags: 2014 Election · House · Politics · Senate

Why you’re wrong to get excited about “60%”

August 4th, 2014, 2:35pm by Sam Wang


Some people are excited (positively or negatively) about Nate Silver’s column today giving a probability of a GOP takeover at 60%. To cut to the chase: I do not think that number means what you think it does. [Read more →]

→ 34 CommentsTags: 2014 Election · Senate

And then there were…four?

July 30th, 2014, 4:33pm by Sam Wang


Of the 36 Senate seats up for election, up to nine of them have been worth watching closely. These races will determine who controls the Senate. Over the last month a few seem to have dropped out of consideration. Now, with a new burst of polling, the playing field – at least for now – includes as few as four races. These races, plus a few others, will be crushed by attention.

The new polls, from YouGov/NYT and other organizations, confirm what I’ve said and hinted at: Georgia might be moving out of the competitive range (toward the GOP), and maybe Alaska too (toward the Democrats). That would leave four competitive Senate races. In an election held today, there is an 85% probability that each side would have between 49 and 51 votes; much of that probability is concentrated in a perfect 50-50 split.

Only four races - Kentucky, Iowa, Louisiana, and Colorado – have no clear leader at the moment. If we assign all the other races, that gives 48 Democrats/Independents and 48 Republicans.

Here is where key races stand today. Note the return of Jerseyvotes, which I’ll explain in a moment.

State Median margin Jerseyvotes
Kentucky McConnell +2.0±1.3% 100
Iowa Tie 69
Louisiana Tie 55
Alaska Begich +5.0±6.0% 52
Arkansas Cotton +4.0±1.3% 41
Colorado Udall +1.0±1.8% 28
Montana Daines +7.0±0.7% 1.2
Georgia Perdue +6.0±2.0% 0.8
Michigan Peters +5.5±0.9% 0.4
North Carolina Hagan +7.0±2.7% <0.1

[Read more →]

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