CALCULATING DEMOCRATS' CHANCES OF REGAINING THE SENATE

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• Document Creation Date: January 17, 2025
• Document Release Date: December 11, 2024
• Case Number: F-2017-00086
• Publication Date: January 11, 2016

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Calculating Democrats' Chances of Regaining the Senate
Like clockwork, Statisticians reemerge to have their ten months in the political sun...
Calculating Democrats' Chances of Regaining the Senate
By Sean Trende
January 11, 2016
The developing conventional wisdom is that Democrats' chances of taking back the Senate in 2016 hinge on their ability
to claim a third term in the White House. But is this true? Like most conventional wisdom, there is some truth here, but
it probably overstates the case.
To address this question, I decided to revisit a Senate election model I developed early in 2014. I won't completely
rehash the details of the model here (you can read them at the above links), but the basic theory is simple: Our federal
elections have become so polarized that you can now predict Senate races accurately knowing just three variables: The
president's job approval rating, whether there is an incumbent in a race, and whether one party or the other nominates
a badly damaged, controversial candidate (think Christine O'Donnell).
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The data are collected from 2004, 2006, 2010 and 2012. I've updated the model to include data from 2014 as well. The
2008 results are not included because at a certain point, presidential job approval stops mattering; a president with a 25
percent job approval (which George W. Bush had in late 2008) does little more harm than a president with a 35 percent
job approval, because that difference largely occurs with partisan Republicans who are likely to vote for a Republican
regardless (more on this later). For the same reason, I do not go back to 1998-2002. In years where the job approval
question did not appear at the state level in the exit polls, job approval is estimated from the national job approval in
the exit polling, modified by the state's partisan voter index.
The model generally performs well. For starters, in early 2014, it indicated that if Barack Obama's job approval on
Election Day were 44 percent, then Republicans should gain nine seats. That is where the exit polls had his job approval,
and Republicans gained nine seats. It predicted the Democrats' vote shares pretty accurately as well, including coming
within one point of the results in hard-to-predict races like North Carolina and Colorado (there were misses in excess of
four points in South Dakota, where Larry Pressler depressed the Democratic vote, and in Oregon, where Monica
Wehby's campaign imploded). Across all years, the median error is one point, as is the mode.
When modeling, it can be useful to go back after the fact and check to see if your model did indeed predict things well.
For example, if we run the model using only the data from 2006 and 2010-2014 to try and predict 2004, it suggest that
Republicans should have picked up four seats that year, which they did. Utilizing this approach for other years in the
sample results in a prediction of Democrats picking up six seats in 2006 (they indeed picked up six), losing five seats in
2010 (they lost six), and losing one seat in 2012 (they picked up two). Incidentally, it performs terribly in 2008, predicting
Democratic gains of 13 seats. Republicans over-perform the predictions by about seven points on average. This seems to
validate the assumption that 2008 is too dissimilar to include.
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So what does this model predict for 2016? Well, we're faced with two problems. First, we don't know what President
Obama's job approval will be. There are a few ways to deal with this, but I ultimately utilized the same approach as I did
in 2014: by generating random numbers following a normal distribution around various means (I'll explain more on this
below).
More importantly, we don't know where problem candidates will surface, so I assigned probabilities. I gave Republicans
a 10 percent chance of nominating a problem candidate in Nevada (where Sharron Angle is considering another bid), 30
percent in Florida, 10 percent in Illinois, 10 percent in New Hampshire, 10 percent in Alaska, 20 percent in Arizona, and
30 percent in Indiana. I also marked Wisconsin as a state with a problematic incumbent, given Ron Johnson's steeper-
than-usual learning curve. One could make a case for including Mark Kirk in Illinois as well, but I ultimately opted not to
consider him problematic (mostly because I had made a judgment call in the opposite direction with Johnson).
I then ran the model with some different assumptions about where Obama's job approval would likely be this fall. For
example, let's assume that the most likely outcome is that the president's job approval will stay more or less around 45
percent, but acknowledge that it could be higher or lower. If we run 10,000 simulated races within these parameters,
then the median outcome is no net change in the makeup of the Senate. Democrats win control of the Senate only
about 5 percent of the time in this scenario.
On the other hand, if we see the president's job approval increase to 50 percent (with allowances on either side) then
the median likely outcome is a Democratic pickup of two seats, with Democrats winning the Senate 26 percent of the
time.
If we see a substantial increase in the president's job approval, to around 55 percent, Democrats win the Senate around
67 percent of the time, and pick up five seats. At 60 percent job approval, Democrats pick up eight seats, and control the
Senate 94 percent of the time (this is different from what I found in 2014 because the model's parameters have been re-
estimated, there have been fewer Republican retirements than I anticipated, and problematic challengers, at least for
now, haven't really emerged).
Finally, we can run the model directly on a variety of job approval ratings, and estimate Democratic gains. This estimates
that the president would have to improve his job approval to 46 percent for a Democratic takeover to be realistic, and to
53 percent for it to be more likely than not.
As always, there are caveats. First, there are probably too many states included. I included states classified as anything
other than "Safe" by the Cook Political Report. In this instance, it includes California. In a normal electoral system, with a
quality GOP candidate, you can see scenarios where Republicans win this seat at Obama's current job approval. But
neither is the case in California, and it is hard to see a Republican winning there (unless two Republicans sneak into the
top-two primary). Likewise, the GOP's recruiting failure in Colorado probably makes it much less likely to flip than the
model suggests. Usually these cancel each other out (in other words, there are similar categorizations that help
Democrats), but this cycle I can envision the Democratic long shots (Arizona, Georgia, Indiana and Missouri) flipping
much more easily than I can Colorado or California.
In addition, the model does have some significant misses, which reminds us that candidates really do matter, even
beyond the "damaged candidate" category I utilize. For example, the model cannot figure out how Kelly Ayotte won by
25 points in 2010, or how Lincoln Chafee managed to keep it relatively close in 2006. It rarely sees Heidi Heitkamp
winning. So an unusually good recruiting season could push things toward Democrats; Maggie Hassan (pictured, with
Hillary Clinton) probably has a better chance of winning in New Hampshire than "generic Democrat."
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We might also wonder whether open presidential seats work in the same fashion as seats where we have an incumbent
running. Open elections still seem to be referenda on the incumbent, so it is probably the better assumption that Senate
elections will function in the same manner. But it is nevertheless an assumption.
Finally, we have to take seriously the possibility that a candidate like Donald Trump or Ted Cruz could damage
Republican down-ticket candidates. While I believe that these candidates' chances in the general election are probably
understated by most pundits, they could turn this election into a real "choice" election, rather than the traditional
referendum.
Overall, I do think this model probably overstates Republican chances somewhat. But I thought the same thing in 2014,
and it proved to be spot on. But for now, the fact that Republicans have relatively few retirements in vulnerable seats
provides them with a bit of a bulwark against a narrow Democratic win. But it isn't a significant one, and an upsurge in
Democratic fortunes could make it very difficult for Republicans to hold the Senate.
Sean Trende is senior elections analyst for RealClearPolitics. He is a co-author of the 2014 Almanac of American Politics
and author of The Lost Majority. He can be reached at [e-mail]. Follow him on Twitter
@SeanTrende.
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