How Popular will the President be in November?

Most presidents are less popular when mid-terms are held than they are in late spring.

In an earlier piece about the “generic” Congressional ballot question, I presented the trends in support for the parties over the course of the summer for a few mid-term elections.  However that question has been asked on a more limited basis than the standard Presidential job-approval question, which Gallup began asking back when FDR served.  As I showed earlier, trends in the job-approval question track inversely with changes in the generic-ballot item. Given the tie between presidential popularity and mid-term outcomes, we might ask how the job-approval question has tracked before mid-term elections.  Given that President Trump’s approval rating stands at a bit under 42 percent today, where might it be come November?

I have compiled Gallup’s job-approval scores for all mid-term elections back to Harry Truman’s second term in 1950.  I have calculated separate averages for first-term and second-term presidents since the additional experience voters have with second-term presidents should limit the effects of most events before the election.

As expected, first-term presidents show a larger change in their job-approval scores than second-termers.  Indeed, excluding the anomalous 1974 election after Nixon resigned, second-term presidents saw their popularity grow on average by about a percentage point.  Nearly all first-term presidents saw their popularity decline as the election grew near, falling an average of 3.8 percent between May and October.

Among first-term presidents, only Jimmy Carter had an approval rating as low as Donald Trump’s at the end of the spring.  Carter saw his rating improve over the course of the summer, but much of that rise came after the Camp David summit with the then-presidents of Egypt and Israel in September, 1978.  Otherwise first-term presidents generally see a decline of about four points on average in their job-approval scores as the summer wears on.  (Leaving out Carter in 1978 raises that figure to five.) On that basis we might expect to see Trump’s job-approval score in the high thirties come Election Day.

One mitigating factor might be that Presidents who start off with ratings under fifty percent show smaller declines than those with a majority of citizens approving of their performance in the spring.  Presidents whose approval score was above fifty percent in May/June watched their ratings fall an average of 4.5 percent by October.  For those Presidents, like Trump, starting with a rating below fifty the average decline was just 1.6 percent.

Will there be a “Singapore Surge?”

Republicans are hoping the Singapore summit will boost the President’s approval ratings, but summit meetings have historically had only small effects. Nor were those effects uniformly positive.

Pundits have speculated that Donald Trump’s meeting with North Korea’s Kim Jong-un might improve Republican chances in the November elections.  “[Trump’s] new willingness to sit down with Kim to work on a peace deal, RNC members believed, would boost his approval rating and make him far less of a drag on congressional Republicans trying to keep control of the House and Senate this November,” wrote S. V. Date in the Huffington Post at the end of last month.  Some of that same optimism was apparent again yesterday. “Ron Kaufman, an RNC member from Massachusetts and once a top adviser to 2012 GOP nominee Mitt Romney, said Trump’s ability to get a meeting with Kim would play well with voters. ‘In real America? Absolutely,’ he said. ‘It will help the president’s numbers, and it will help to some degree in the midterms.'”

The problem with this theory is that summits have had limited effects on presidential approval ratings.  Using the job-approval data from Gallup I compiled the average approval score for roughly the two months prior to a summit and the two months following and calculated the change as shown below.

Most summit meetings have had only marginal effects on the President’s popularity on the order of a few percent up or down.  Nor can we attribute all the changes we see to the summits themselves.  For instance, the fall in Ronald Reagan’s approval ratings after his Washington summit with Mikhail Gorbachev in 1987 resulted largely from the revelations of the Iran-Contra scandal which appeared soon after the summit.  Nor do all summit meetings improve the President’s image. The 1974 meeting between Gerald Ford and Leonid Brezhnev led to the SALT II accords, but they were denounced by Republican opponents like Ronald Reagan and criticized by major newspapers like the New York Times.

A number of summits considered important by historians had little influence on public opinion.  Even an event as tumultuous as Nixon’s trip to China in 1972 increased his approval rating by less than four points.  Kennedy’s supposed failure to stand up to Khrushchev in Vienna cost him a bit over five points. A year before Khrushchev had stormed out of the Paris meeting with Eisenhower over the U-2 crisis.  Eisenhower’s popularity suffered a slightly larger hit.

As I wrote earlier about the effect of the Syrian bombings, opinions about Donald Trump are much too crystallized to react to something like a summit.  And if the intention was to influence the fall election, why didn’t Trump hold out for a meeting in September or October when it might have mattered?  Few voters will be taking the Singapore summit into account when they go to the polls in November.

Update: I added Jimmy Carter’s involvement with the Camp David accords in September, 1978, to the list.  His approval rating rose substantially in the short term, from an average of 40.8 in the two months before the summit to 49.5 in the two months thereafter.  His approval scores were already moving upward after hitting a nadir of 38 the previous July, but they did jump five points between the poll earlier in September and the next sounding in October.  This bump in Carter’s approval persisted through the November, 1978, midterm election.  Perhaps Trump should have waited until the fall to meet with Kim.

Don’t Count Those Chickens Just Yet

Support for the President’s party on the generic House ballot is historically lower on election day than in the spring.

Most “generic ballot” polls attempting to forecast the 2018 general election have shown a narrowing of the gap between Democrats and Republicans in the past month or two.  The gap was widest at the end of 2017 when Trump’s job-approval numbers reached their lowest point.  While Republicans have regained a bit of ground since then, Democrats still have about a 5-7 point lead in recent polls.

Before Republicans get too excited by this rebound, we should examine the trends for the Trump Administration in the context of previous elections.  Here are two charts that depict the trends in the difference between support for the President’s party and support for the opposition in generic ballot polls.  The data for 2006 and 2008 comes from RealClearPolitics; the remainder comes from the archives at HuffPost Pollster that I have used in earlier postings.  In each case I have averaged polls by month, combining together May and June, and July and August, when polling is less frequent than in the fall.

For both Obama years, 2010 and 2014, we see a fairly linear decline in the Democrats’ margin over the Republicans on the generic ballot.  Unsurprisingly the fall in Democrats’ fortunes was much more substantial in 2010, when Obama observed that his party had been “shellacked” in the midterm.

In 2006 the Republicans faced a double-digit deficit in the spring.  Though they shaved a couple of points off the Democrats’ lead by September, the Mark Foley scandal ended any hopes of a Republican come-back.

The Republicans begin the summer of 2018 facing a five-point deficit which might not be enough to swing the House of Representatives to the Democrats.  If the history of past presidents is to be believed, though, the Republicans’ prospects may worsen as we head into November.

 

 

The Strange Case of 1976

1976 was a horrible year for Senate Republicans; adjusting for that fact makes a slight difference to my 2018 predictions.

Re-examining the results for my original model of Senate elections, it was hard to ignore how poorly the model fit the data for 1976.  Here is a graph of the model’s predicted vote for Senate and the actual vote that shows what an “outlier” 1976 is.  While Truman rallied Senate Democrats in 1948, even that event just hovers on the edge of the statistical “margin of error.”  The Republicans’ failure in the 1976 election after Richard Nixon was forced from office stands truly alone compared to the rest of the postwar elections in my dataset.

If 1976 had been a normal presidential election year, the Republicans’ Senatorial prospects would have looked fairly rosy.  Gerald Ford was running for re-election, real personal income was growing at two percent, and the Democrats were defending seats won in 1970 by a (two-party) margin of 56-44 at the height of the anti-war and anti-Nixon fervor.  That generally pro-Republican climate predicts the GOP should have won nearly 52 percent of the popular vote for Senate.

But, of course, the 1976 election was anything but normal.  It was the first presidential election after the Watergate scandals had forced Richard Nixon from office in disgrace.  Rather than winning the popular vote by the predicted four-point margin, the Republicans could muster only the same share of the vote they won back in 1970, 44 percent.  Though a number of seats changed hands, at the end of the day the Democrats held the same 61-seat Senate majority they did before the 1976 election.

I can adjust statistically for the anomalous 1976 election by adding a “dummy” variable to my model that is one in 1976 and zero otherwise.  Adjusting for 1976 radically improves all aspects of my model.  Its predictive power as measured by adjusted R-squared rises from 0.43 to 0.56, and all the coefficients are more precisely estimated.

Adding this dummy variable implicitly treats Gerald Ford as different from other Presidents running for re-election.  Ford was apparently so compromised by Watergate that his presence at the top of the ticket did not generate the kind of support his fellow Republican candidates for Senate might have expected.  With the 1976 adjustment, the overall effect of Presidential candidacies rises from 2.5 to 3.1 percent, suggesting Ford’s performance was suppressing the estimate for other Presidencies.

Adjusting for 1976 also increases the compensating effect (“regression-toward-the-mean”) of the prior vote for a Senatorial class.  With the suppressing effect of 1976 removed, I now estimate that the Democrats’ lopsided Senate victory in 2012 should be worth about 2.3 percent to the Republicans this November, compared to the 1.9 percent figure I presented earlier with no adjustment for 1976.

For comparison to the chart above, here are the predicted and actual values for the model adjusted for 1976:

Including a dummy variable for 1976 sets its residual to zero and places its predicted value precisely on the line.  The largest positive outliers are now 1978 and two Presidential years, Truman in 1948 and Barack Obama in 2016.

The effects of this modification on the predictions in my earlier article are quite modest.  Without adjusting for 1976, I predicted the Republicans will win 48.1 percent of the popular vote if Trump’s approval rating is at forty and real disposable personal income rises two percent.  With the adjustment that figure rises to 48.4 percent.

The overall conclusion remains that no likely combination of factors predicts that the Republicans will win a majority of the popular vote for Senate this fall.

 

 

This Dog Won’t Wag

Donald Trump’s polling figures showed little change after last year’s attack on Syria.

The 1997 movie Wag the Dog introduced the public to a notion common among pundits and historians, that Presidents like other political leaders might engage in military actions overseas to distract from problems at home.  With a President beset from many sides, pundits have opined whether Friday’s attack on Syrian chemical weapons facilities might have been motivated, at least in part, by the same diversionary motive.

Friday’s action reprises the Tomahawk missile attack conducted by American forces against a Syrian airfield a year ago.  That equally brief sortie had little short-term effect on President Trump’s job-approval ratings and no long-term effects at all.  Here is the trajectory for “net approval,” the difference between the percent of American adults who say they approve of how the President is “handling his job” minus the percent who disapprove.1  President Trump has been “underwater” since his Administration began with more Americans disapproving of his performance than approving.

The most optimistic “wag-the-dog” interpretation of this chart might credit a two or three point positive bump in President Trump’s net approval rating after the attack on the Syrian airfield on April 7th of last year.  Yet a couple of other prominent events might give us pause.  Trump’s approval rating actually improved after Michael Flynn had to resign as National Security Advisor, but it soon fell back down. Last year’s attack on Syria itself took place at a time when Trump’s rating was already recovering.  Perhaps the apparent gain after the attack was just the continuation of that trend.

When partisans are routinely described as “tribal,” we can hardly expect many of them to change their minds about President Trump just because of a single military attack. Republicans endorse his performance in office by margins of 85-10, while Democrats disapprove by an even greater margin of 9-90 unfavorable. For people so solidly entrenched in their partisanship even a missile attack against a sovereign nation can have little sway.

Perhaps, then, we should look at the opinions of self-described “independents.” Maybe their opinions will be more sensitive to current events like a strike on Syria. Sadly those seeking a wag-the-dog effect will once again be disappointed.


Independents’ appraisals of President Trump tracked rather closely to the Gallup figures above (with the exception of the weird spike at the turn of the year).2 Again, whatever small gain the 2017 Syrian attack may have imparted to Trump’s approval ratings among independents quickly dissipated a few weeks later.

 


1Since the beginning of this year, Gallup has reported only weekly job-approval ratings. I appended the 2018 data to the 2017 weekly averages.

2Because Gallup does not report partisan breakdowns, I have averaged together the soundings archived at Pollster that do. This sample includes 313 polls that reported approval ratings for independents. They were conducted by thirteen different organizations, with four each constituting about a sixth of the observations (Politico/Morning Consult, YouGov/Economist, IpsosReuters and SurveyMonkey).

Can the Republicans Hold the Senate in 2018?

Historical voting patterns and current economic and political conditions predict the Democrats can win 18 of the 33 Senate seats in contention this fall and perhaps take back control of that body.

The departure of Paul Ryan as Speaker provides yet another piece of evidence in favor of the Democrats taking back the House of Representatives this fall.  Faced with this prospect Senate Majority Leader Mitch McConnell and other Republican legislators and strategists argue that the party must now focus its efforts on maintaining its one-vote lead in the Senate.  In this essay I examine the prospects for a Democratic Senate victory as well.

At first glance, the Democrats’ prospects seem quite poor. The current “class” of Senators running for re-election last faced their voters in 2012 when Barack Obama was re-elected President. That helped the Democrats win or retain a number of seats in unlikely places like North Dakota, Missouri, and Montana. Twenty-three Democrats were elected to the Senate that year, compared to eight Republicans and two independents.  With so many more Democratic seats up in 2018, we might expect the GOP to maintain or even expand its slim Senate majority this fall.

However the Democrats themselves held a similar advantage in the 2016 election but failed to win back the Senate. The Republicans needed to defend the 24 seats they won during their “shellacking” of the Democrats in 2010, while just ten Democratic seats were at risk. Nevertheless the Democrats managed to swing only two seats into their column in 2016, suggesting that the relative number of seats at risk may not be a very powerful predictor of the eventual outcome.

One factor in the Democrats’ favor is the absence of Donald Trump at the top of the ballot come November.  Updating the chart from my previous article to include the 2016 election does not change this basic fact:

The Democrats did better than expected in the 2016 Senate elections, winning 53.7% of the popular vote.  That raised the average for the six “open seat” elections, when the President was not standing for re-election, to 48.8% from the figure of 47.9% I reported in 2016.  In general, though, having the President at the top of the ticket adds, on average, four percentage points to the vote for his co-partisans in the Senate. The Republicans are thus starting from behind despite the disparity in seats at risk.

Along with whether the President is standing for re-election, I identified three other factors that have systematically influenced the vote for Senate candidates since World War II:

  • the size of the previous popular vote for the current “class” of Senators facing re-election;
  • the President’s job approval ratings in polls near mid-term elections; and,
  • the year-on-year change in real disposable personal income per-capita.

That framework enables us to examine some possible scenarios for this fall.

There is some evidence that the size of the vote for a Senatorial class does influence how well that class fares six years later. The party advantaged in one election sees a drop in support when facing re-election.  In 2018 that factor helps the Republicans by about 1.8 percent, still not enough to overcome the deficit from not having the President at the top of the ticket.

As I find for House elections, a President’s “job-approval” rating influences the outcomes of Senatorial races.  A ten-point increase in the percent of Americans approving of the President’s performance results in a 1.2 percent increase in support for Senatorial candidates of the President’s party.

On the economic front, the Republicans have repeatedly touted their recent tax cut as providing an impetus to support for their party. As Bloomberg reported after a GOP retreat in February, “With President Donald Trump’s stubbornly low approval ratings and historical trends suggesting they’ll lose seats in the November mid-term elections, party leaders told lawmakers their salvation lies in hammering on the message that the tax cuts passed at the end of last year are putting more money in voters’ pockets.”

My earlier findings confirm that growth in real disposable personal income does have an effect on vote for the President’s co-partisans in the Senate.  In the simulations below, raising personal income growth by one percentage point yields an increase in the predicted vote for Republican candidates this fall by about 1.4 percent.

We can put these findings together and examine the model’s predictions for the Senatorial vote in 2018 given different combinations of presidential job-approval and growth in personal income.


or, visually,

In no likely scenario does my model predict a popular-vote majority for Republican Senate candidates this fall. Which of these scenarios might we see play out in November?

The job-approval figures I use in this analysis come from Gallup, since only that organization has published these ratings as far back as the 1940s.  Like most other pollsters Gallup has reported a slight rebound in Trump’s approval figures over the past couple of months, but they are still running around forty percent.

Gallup has begun reporting weekly ratings this year which explains the much lower variability of its 2018 results.  Also Gallup’s polling shows no systematic partisan bias in either direction but hews closely to the polling “consensus.”  However, Gallup may underestimate approval for President Trump by about 1.6 percentage points because it surveys all adults rather than just registered voters.

Personal income growth, despite the tax cuts, does not provide much reassurance for the Republicans either. Real disposable personal income per capita has shown only modest growth over the past few months, running at about 1.5 percent on an annualized basis.


While there has been a slight downtick since the January peak of 1.6 percent, it seems plausible that real personal income per-capita will show a gain in the neighborhood of 1.5 percent by November.

From the table of predicted vote outcomes, a job-approval rating of 40 and even two percent personal income growth corresponds to a 52-48 split in the popular vote favoring Senate Democrats this fall.  Because there is little “bias” in the translation from votes to seats in the Senate, winning 52 percent of the popular vote translates into a two or three seat margin this fall.


Using the equation shown in that chart, if the Republicans win 48 percent of the popular vote for Senate this fall, they should come away with only fifteen seats (45% of the 33 seats at risk).  A three-seat victory for the Democrats would flip control of the Senate even given the Vice President’s deciding vote.

The “Generic” Congressional Ballot Question

Democrats would lead by nearly fourteen points in “generic” Congressional ballot polls next November if the trends seen since Trump took office continue.

I have written earlier about how methodological differences among pollsters can lead to significantly different results.  In my analyses of Presidential approval I showed how Donald Trump’s approval ratings varied depending on the choice of sample to interview and the interviewing method chosen.  In this piece I apply the same approach to the so-called “generic” ballot question, typically “If the elections for Congress were being held today, which party’s candidate would you vote for in your Congressional district?”  Some pollsters mention the Democrats and Republicans in this question, others leave it more open-ended like the example I just gave.

I have focused on the net difference in support for generic Democratic and Republican candidates.  This ranges from a value of -4 (Republican support being four points greater than Democratic support) to a high of +18 in the Democrats’ direction.  Here is a simple time plot showing how support for the Democrats on this question has grown while Trump has held office.

The Democrats held a small lead of just under four points on the day Trump took office.  Since then the Democrats’ lead has slowly increased to an average of eight points.

What’s surprising about these data is that they do not show the usual methodological differences we see in the presidential series.  Here are a few regression experiments using my standard array of predictors.

Choice of polling method has no systematic relationship with Democratic support on the generic ballot question. In contrast, Trump’s job-approval ratings run one to two points higher in polls taken over the Internet.  Another striking difference is the greater level of support found for Democrats in polls of registered or “likely” voters.  Again, the job-approval polls show an opposite effect, with polls of voters displaying greater levels of support for Trump than polls that include all adults.  I have also included separate effect measures for the two most-common pollsters in this sample, Politico/Morning Consult and YouGov/Economist.  Job-approval polls taken by the former organization show a pro-Trump “bias” of about three percent; on the generic ballot their polls place Republican support about five points higher than other polls.  YouGov/Economist polls also have Republican tilt on this question, though they show a slight anti-Trump bias in job-approval polls.

If we extrapolate these results to the fall election on November 6th (655 days after the Inauguration), and include the effect for registered voters, the model predicts the Democrats’ lead in generic ballot polls would reach nearly fourteen percent (=4.07+2.62+0.011*655).  A margin that large would easily overwhelm the built-in advantage Republicans hold based on partisan self-selection and gerrymandering.  Even if the Politico figure is correct, adding in that pro-Republican factor brings Democratic support down to nine points on election day.  That result would still reach nine percent, or a Democratic/Republican split of about 54-45.  That 54 percent figure still exceeds the 53 percent minimum I estimated earlier would result in Democratic control of the House of Representatives.

Using the model for the relationship between seat and vote divisions presented earlier, a 57 percent margin in the national Congressional vote would translate into the Democrats’ winning 55 percent of the House seats for a margin of 239-196.

Republicans Continue to Leave the House

Three more Republican House Members announced they would not seek re-election this week, bringing the total number of retiring Republican Members to 34 according to the New York Times. That figure compares to 16 Democrats, for a net Republican difference of +18.  We have to look back to the Democratic landslide in 1958 to see a mid-term with double-digit net Republican retirements.  For Democrats, only in 1938 and 1978 did the number of their retirements exceed Republican retirements by ten or more.

This increase of three net Republican retirements raises the predicted Democratic seat swing to 41 using the relationship depicted in the previous article.

I have shown in earlier postings that the relationship between seats and votes that advantaged Democrats in the years after World War II moved steadily in the Republicans’ direction beginning in 1980 and, with the help of gerrymandering, became even more favorable for the Republicans after 2010.  That might temper our belief in a prediction for an election being held in 2018.  First, the 2018 retirement margin of -18 is close to the observed maximum of -21 in 1958.  Perhaps the 1958 election is an “outlier” and without it the relationship is less steep than we observe.  However slope and intercept coefficients estimated with 1958 excluded are numerically nearly identical to those estimated with that year included.  So it’s unlikely that the historical model is radically overestimating the likely result next fall.

Another test is to let the relationship differ before and after 1992 to see whether the structural changes that we observe in the seats/votes relationship in the current era appear in the relationship for retirements and seat swings.  Once again, allowing the coefficients to differ before and after 1992 showed no measurable statistical difference. While the effects of gerrymandering and partisan self-segregation may make the House less vulnerable to “waves” of Democratic support, there is no evidence for that thesis looking at retirements as a predictor of seat outcomes.

These estimates have a lot of uncertainty attached.  The standard error of estimate is about 28 seats.  That means there is about a two-thirds chance that the actual swing will be somewhere between 13 and 67 seats.  Since the Democrats need a swing of at least 24 seats to win control of the House, even a retirement margin of 18 is not enough to ensure a change in party control.

The regression model taking President’s partisanship into account is a bit more conservative; it predicts a swing of 37 seats.

Update (2/26/18) – One more Republican has announced he is leaving the House, along with one more Democrat.  The net difference remains at +18.

What Do House Retirements Tell Us About the Future?

The pace of Republican retirements predicts that Democrats should take back control of the House of Representatives this fall by a margin of eight or nine seats.

This week Edward Royce (R-CA), Chair of the House Foreign Affairs Committee, and Darrell Issa (R-CA), former Chair of House Oversight and Reform, joined 27 of their fellow House Republicans by announcing that they are retiring from the chamber.  About half are leaving public office entirely, while the remainder are seeking another office like governor or senator.  (Issa has threatened to run for the House again in an adjacent district.)

On the other side of the aisle, fourteen Democrats have announced that they will be leaving the House of Representatives.  Only five of them are leaving public office, though Ruben Kihuen (D-NV) may be joining them subject to an investigation into allegations of sexual harassment.

Many pundits have interpreted the much higher retirement rate for Republicans to be a bellwether for this fall’s Congressional election.  If no one else announces a retirement, the Republicans will face a net loss of fifteen seats going into the midterms.  Just how large a threat do such retirements pose to Republican control of the House?

These two charts show the relationship between the net Republican margin of victory in terms of seats in the House and the net partisan difference in retirements.  It turns out that retirements tell us essentially nothing about Congressional outcomes in Presidential years, but they are quite informative in mid-term elections like 2018.  Here is the chart for Presidential years:

In presidential years we see little relationship between net Republican retirements and how well the party fares in the upcoming general election. What matters more are Presidential “coattails” with Republican swings in years when Eisenhower (1952), Nixon (1960, 1972), and Reagan (1980) ran.  Democrats were favored when they ran along side Johnson in 1964, Obama in 2008, and Franklin Roosevelt in 1944.

A much different picture appears if we look at the same relationship for mid-term years.

Now the number of Republican seats won or lost depends much more directly on the number of retirements.  The line is anchored by the Republicans’ success in the 1938 midterm and their dramatic losses in the 1958 election. If the figure for net retirements remains at fifteen, the Republicans are predicted to lose about thirty-two seats next November.  That would give the Democrats control of the House with a margin of eight seats.

However, because the President’s party historically loses seats in midterms, we should expect to see more retirements from the President’s party in midterm years.  When Democrats presided over a midterm, an average of four more Democrats retired from office than did Republicans.  When the Republicans held the White House in a midterm year, retirements from their ranks outnumbered Democratic retirements by an average of six.

So some of the strong relationship we see between retirements and midterm losses arises simply because the President’s co-partisans are jumping ship knowing that their party will do more poorly in the upcoming midterm.  That leaves us with the question of whether retirements have any additional predictive power once we take the President’s partisanship into account.  Retirements still matter in this better specification, though that effect just achieves statistical significance.


Based on these estimates, in a year where the Democrats hold the White House, and the number of retirements on both sides of the aisle is equal, the model predicts that the Republicans should gain about thirty seats.  When the Republicans hold the White House, and retirements are equal, the Democrats should gain about twelve seats (= 30.2 – 42.1 = -11.9).  Regardless of which party controls the Presidency,* Republicans are predicted to lose 1.4 seats for every retirement.  Applied to the current circumstances, this formula predicts a Democratic victory by thirty-three seats, or one more than predicted by the simpler model.

 

 

*Allowing the relationship between retirements and seat outcomes to vary separately depending on which party controlled the White House added no explanatory power.

 

How Doug Jones Won

Comparing last night’s results for the Special Election in Alabama to prior elections in that state shows the path which brought Doug Jones his unlikely victory.  Like all special elections, the Alabama election unsurprisingly failed to mobilize as many voters as last year’s Presidential contest, but the turnout last night did exceed the 2014 mid-term figure by four percentage points.  Alabamians apparently thought this race was worth the effort.

Jones gained nearly as many votes in this special election as Hillary Clinton polled in November, 2016, despite an electorate 37 percent smaller than for the Presidential election.

Doug Jones expanded the Democratic electorate in the largest Alabama counties when we compare his results to those polled by 2014 Democratic gubernatorial candidate Parker Griffith.  (There was no Democratic candidate for Senator on the ballot that year.)

Jones won 671,151 votes last night, an improvement of 57 percent statewide over Griffith’s 427,787 total three years ago.  The graph shows clearly that Jones’s advantage grew as a function of county size as measured by total turnout.  His best performances were in Madison County, where aerospace center Huntsville is located; Shelby County, which includes suburban Birmingham; and Baldwin County, just east of Mobile.  Moore carried both of the latter counties over Jones but by severely diminished margins compared to Republican performance in prior elections. Jones doubled the Democratic vote in Lee County, home to Auburn University, and made a significant gain in Tuscaloosa where the University of Alabama is located.

Moore’s support, in contrast, was strongest in the smallest counties.  Here I am comparing Moore’s performance last night to the total vote cast in the Republican primary runoff election against Luther Strange late last September.  Moore needed to mobilize sufficient numbers of Strange voters to add to his own totals going into last night’s election.  He failed to do so.

Statewide Moore received about 35 percent more votes than he and Strange together polled in September.  However Moore saw his smallest gains in the largest counties, the opposite of the pattern we saw for Jones.

Running a simple regression of Jones’s lead over Moore against demographic variables shows the dominant power of mobilized African-Americans with smaller effects for the proportions of Hispanics and people with a college degree.

In a county with no blacks, no Hispanics, and no one with a college degree, Moore would beat Jones by 79 points, e.g., 89-10.  The size of the black population played the most important role in determining support for Jones.  His lead expanded by 1.6 percent for every one percent increase in the percentage of blacks.  Looking at the “standardized” coefficients, which provide a measure comparable “importance,” the proportion of a county’s residents holding a college degree also mattered, but its influence was a bit under half that of the size of its black population. Variations in the size of a county’s Hispanic population had a much smaller effect and just achieves significance.These three variables alone account for about ninety-four percent of the variance in Jones’s lead over Moore.

Jones’s victory with a margin of 1.5 percent over Moore suggests that the polls that included cell phone respondents were right on track.  As I wrote yesterday, “Taken together, [my analysis of polling data] suggests that Jones has averaged a 1-2 percent lead in polls taken since the Washington Post story that included calls to cell-phone users.”  Polls limited to landline households, which predicted a Moore victory, were off the mark.