Tag Archives: Polling

Reliance On Broken Polling Data Will Leave “Analysts” Stumped When Republicans Hold The House, by Duane Norman

For the last few election cycles, pollsters have been mostly and their errors are all in one direction: overestimating the Democratic vote. From Duane Norman at fmshooter.com:

Similar to the 2016 election, political pundits have been stating for months that the Democratic party is all but a sure thing to win enough seats to control the House of Representatives.  The Drudge Report recently featured the below headline highlighting FiveThirtyEight’s prediction:

We predicted that the Republican party would lose some seats but hold the House, even prior to the contentious Kavanaugh confirmation hearings.  Since then, the Republican party’s position has only strengthened, buoyed by non-stop campaigning by President Trump amid record-breaking crowds.  Still, this has not changed the tune of the political pundits (or the gamblers) who continue to predict a Democratic House and return of Speaker Pelosi.  

No one is more vocal about this then the aforementioned Nate Silver, who heads up FiveThirtyEight and presumably stands behind his calculations.  We will give him the benefit of the doubt and examine his “deluxe” forecast, instead of the “classic” cited above:

Well if he thinks Democrat House odds are 83%, he must love them at 67%, where he can currently bet them on PredictIt:

Odds taken from PredictIt on 10-23-2018 at 2:20PM

The major flaw in FiveThirtyEight’s forecasts is their near-total reliance on polling data, with little analysis given to the districts themselves, as stated in their methodology:

We’re adjusting poll results in three ways: Polls of registered voters or all adults are adjusted to a likely-voter basis; older polls are adjusted based on shifts in the generic congressional ballot since the poll was conducted; and polls are adjusted for house effects (the tendency for a firm’s polls to lean toward Democrats or Republicans). Polls with larger sample sizes and those conducted by higher-quality polling agencies are given more weight, as are more recent polls.

To counter this, FMShooter will examine three “close” districts in Florida, a swing state that commonly rates as “purple”, and where voting results frequently mimic the national mood in any given election year.  The most obvious example FiveThirtyEight’s data failure is in FL-27, the district containing Miami Beach and south Miami, which they are stating is all but certain to flip:

The district has been represented by Ileana Ros-Lehtinen since 2013, in spite of its heavy blue tilt.  Ros-Lehtinen had won fifteen elections, but is retiring this year.  Competing for the seat are Donna Shalala, Bill Clinton’s former HHS secretary, and Maria Salazar, a Telemundo news anchor.  The district is over 71% Hispanic, and this should be an easy flip for Democrats, except…

Shalala is a member of the heavily-disliked Clinton cabal, and does not speak Spanish in a heavily Hispanic district.  Salazar, meanwhile, has been on TV for years as an anchor, and is attempting to fill a longtime Republican seat.  While we do not expect the Republicans to win this seat, we certainly think the odds are much closer to 50/50 than the 80+% Silver’s analysts have assigned to the race.

FiveThirtyEight has another nearby district, FL-26, as a toss-up:

Two-term Republican incumbent Carlos Curbelo won both of his elections fairly handily, by three and twelve points respectively.  A district local, he has a relatively low Trump score according to FiveThirtyEight themselves, opposing Trumpwhen it represented his district.

His opponent Debbie Mucarsel-Powell is a political unknown, whose father was killed in Ecuador, a country with far stricter gun laws than the US.  That of course hasn’t stopped her from making tighter gun control a linchpin of her platform, a foolish strategy in the “gunshine” state.

We’re not sure what has changed in the district that will lead Mucarsel-Powell to make up even three points, especially with President Trump’s work to carry the party on the national level.  With the Kavanaugh hearings being used by Curbelo against Mucarsel-Powell, we estimate the odds of Curbelo winning are far above the 54.6% (or 50-50 “classic” forecast) that FiveThirtyEight is projecting.  

But perhaps the most blatant area of FiveThirtyEight’s data failure is in FL-15:

Containing Lakeland and other Tampa Bay exurbs, the district has been a Republican stronghold for decades.  Even in 2008, when the national party was carried by former President Obama, it was lost by 15 points (when it was the 12th district).  Dennis Ross, the district’s current Representative, is retiring, and Florida State Representative Ross Spano is the GOP nominee to fill the seat.

The district is nearly 60% white, a demographic which heavily favors President Trump.  Ross’s opponent, Kristen Carlson, is somewhat of an unknown to us, running on what appears to be the party platform.  While most will attribute the national mood and a “blue wave” to the generic ballot swinging, the reliance on polls instead of solid analysis will more than likely leave Democratic voters disappointed with the results in FL-15.

Nate Silver would be wise to turn back the clock to the GA-06 special election in 2017, where tens of millions of dollars were spent by the DNC attempting to flip a solidly Republican seat.  Silver followed the polls, delivering this cringeworthy prediction:

If the above races follow our non polling-driven analysis, as opposed to a fancy website which relies on the generic ballot to forecast, it might be time for Silver to admit that his polling data is broken in the Trump political era

 

Note: The oddsmakers seem to also be following polls and data like Silver’s, delivering what we believe to be mispriced markets on betting websites.  See parts one, two, and three of our Midterm Election guide for Senate races that we like.  We plan on providing a final segment to the guide just before the election, updating one or two Senate races with new predictions.  

Trump’s Data Team Saw a Different America—and They Were Right, by Joshua Green and Sasha Issenberg

Pollsters, like generals, may fight the last war. They may have plugged Obama’s black and millenial support into their models (Hillary did noticeably worse than Obama with both groups) and plugged in Romney’s white, older, rural support, without taking into account that these groups were much more enthusiastic for Trump. From Joshua Green and Sasha Issenberg at bloomberg.com:

Nobody saw it coming. Not the media. Certainly not Hillary Clinton. Not even Donald Trump’s team of data scientists, holed up in their San Antonio headquarters 1,800 miles from Trump Tower, were predicting this outcome. But the scientists picked up disturbances—like falling pressure before a hurricane—that others weren’t seeing. It was the beginning of the storm that would deliver Trump to the White House.

Flash back three weeks, to Oct. 18. The Trump campaign’s internal election simulator, the “Battleground Optimizer Path to Victory,” showed Trump with a 7.8 percent chance of winning. That’s because his own model had him trailing in most of the states that would decide the election, including the pivotal state of Florida—but only by a small margin. And in some states, such as Virginia, he was winning, even though no public poll agreed.

Included in the new issue of Bloomberg Businessweek, Nov. 14-20, 2016, which features two covers on Trump’s American Revolution. Subscribe now. (l-r) Photographers: M. Scott Brauer for Bloomberg Businessweek; Jonno Rattman for Bloomberg Businessweek
Trump’s numbers were different, because his analysts, like Trump himself, were forecasting a fundamentally different electorate than other pollsters and almost all of the media: older, whiter, more rural, more populist. And much angrier at what they perceive to be an overclass of entitled elites. In the next three weeks, Trump channeled this anger on the stump, at times seeming almost unhinged.

“A vote for Hillary is a vote to surrender our government to public corruption, graft, and cronyism that threatens the survival of our constitutional system itself,” Trump told an Arizona crowd on Oct. 29. “What makes us exceptional is that we are a nation of laws and that we are all equal under those laws. Hillary’s corruption shreds the principle on which our nation was founded.”

His hyperbole and crassness drew broad condemnation from the media and political elite, who interpreted his anger as an acknowledgment that he was about to lose. But rather than alienate his gathering army, Trump’s antipathy fed their resolve.

He had an unwitting ally. “Hillary Clinton was the perfect foil for Trump’s message,” says Steve Bannon, his campaign chief executive officer. “From her e-mail server, to her lavishly paid speeches to Wall Street bankers, to her FBI problems, she represented everything that middle-class Americans had had enough of.”

Trump’s analysts had detected this upsurge in the electorate even before FBI Director James Comey delivered his Oct. 28 letter to Congress announcing that he was reopening his investigation into Clinton’s e-mails. But the news of the investigation accelerated the shift of a largely hidden rural mass of voters toward Trump.

Inside his campaign, Trump’s analysts became convinced that even their own models didn’t sufficiently account for the strength of these voters. “In the last week before the election, we undertook a big exercise to reweight all of our polling, because we thought that who [pollsters] were sampling from was the wrong idea of who the electorate was going to turn out to be this cycle,” says Matt Oczkowski, the head of product at London firm Cambridge Analytica and team leader on Trump’s campaign. “If he was going to win this election, it was going to be because of a Brexit-style mentality and a different demographic trend than other people were seeing.”

To continue reading: Trump’s Data Team Saw a Different America—and They Were Right