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Spatially speaking, the SPD performed better than expected in the 2017 German Federal Elections, while the CDU did worse. And the AfD is the least-liked party of them all

There is a long political science tradition of modeling voting decisions as based on which party a voter is “closest” to in a policy space. This space can, in principle, be of any dimensionality; for both theoretical and empirical work, the assumption of a two-dimensional policy space is frequently used.

Voting in such a framework is simple – voters calculate the distances between their own ideal point in the policy space and the positions of all parties competing for votes. They then vote for the party that is closest to their ideal point. There is no consideration of e.g. how likable a candidate is or whether a voter feels particularly attached to a specific party. All that matters is distance. In addition, voters’ preferences (their ideal points) are fixed and exogenously given and there is no abstention.

We can use this model to gauge which parties over- or underperformed in the 2017 German Federal elections, given their policy stances and given the stated preferences of voters. For voter’s ideal points, we turn to the GLES post election survey data and use the questions on  preferences over taxation and immigration to measure the ideal point of a voter on an economic and a societal dimension, respectively. For parties’ positions on the same two dimensions we use data from the Chapel Hill expert survey. Here is what this looks like:

Political parties are positioned around the center of the distributions on the two dimensions. Warmer colors denote that more voters with those preferences can be found in these regions of the policy space, while the dark blue color that can be found towards the extremes of the distributions indicate that there are few voters whose ideal points are located there.

Some parties, like the CDU/CSU and the SPD, are closer to where the bulk of voters are, while others like the FDP, the AfD, the Left party and the Greens, position themselves more to the edges. How should these positions translate into votes? If we assume voting based solely on minimum-distance considerations, the SPD should have gotten a mere 14.3 percent of the votes instead of the 20.5 percent it actually received. In contrast to this over-performance, the CDU/CSU should have received 39.1 percent of the votes instead of the 33 percent it ended up with. The table shows these numbers for all the parties currently in the German Bundestag

Party Expected Minimum Distance Vote Share Actual Vote Share Difference
CDU/CSU 39.5 33 -6.5
SPD 14.3 20.5 6.2
GREENS 9.8 8.9 -0.9
LEFT 7.9 9.2 1.3
FDP 9.9 10.7 0.8
AFD 18.5 12.6 -5.9

While the Greens, the Left party and the FDP performed about as predicted by a minimum-distance model, the AfD performed much worse than minimum-distance considerations would suggest.  One of the reasons for the discrepancy between predicted support and electoral performance might be the likability of parties. The GLES data contain information on how voters view parties. Respondents are asked to voice their opinion on parties by using an 11 point scale with a range from -5 to +5 where -5 stands for “I don’t think anything of this party at all” and +5 denotes “I think very highly of this party”. This question goes beyond mere distances in a policy space. It also covers emotional and longer-term attachment to political parties. 

Using this measure, we find that the AfD is the least liked party with an average value of 2.77 on the -5 to +5 scale. A full 60 percent of voters chose the worst possible judgment for the AfD. By comparison, the SPD has a mean favorability value of 7.4. However, we find an almost identical number for the CDU. Even considering the somewhat lower values for the CSU, the favorability rating cannot explain why the CDU/CSU underperformed their minimum-distance spatial expectations.

Maybe, then, it was all about the candidates? Comparing the favorability ratings of Chancellor Angela Merkel and then-candidate for the Chancellory Martin Schulz of the SPD, we find that the difference between Schulz and Merkel is about 1.25 in Merkel’s favor. In other words: If Merkel had been seen as unfavorably as Schulz, the CDU/CSU would have done even worse. On the other hand, a candidate Schulz with Merkel’s favorability rating would have outperformed the SPD’s spatial forecast by an even wider margin.

Looking ahead, these findings are good news for the CDU and not so good news for the SPD. With the SPD already outperforming their levels of support suggested by a spatial perspective, it is not clear how the party could increase their vote share, especially not if the SPD moved to a position further to the left. For the CDU, the party’s longtime strategy of steering a calm course could just be what is needed to bring voters back who should have voted for the party based on their preferences, but didn’t do so in the 2017 elections. In any event, neither party stands to gain from moving further to the extremes.

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On the map: Turnout and party support in the 2017 German federal elections

Following up from yesterday’s post, we can also look at a map of Germany to see where the electoral losses for the  center-right CDU/CSU were most severe. The party incurred their most severe losses in parts of Saxony and Bavaria, former party strongholds, but also in the Southwestern state of Baden-Württemberg.

Change in electoral support (party vote) for the CDU/CSU in the 2017 German federal elections

By contrast, the far-right party AfD increased their vote share most markedly in East Germany and parts of Bavaria.

Change in electoral support (party vote) for the AfD in the 2017 German federal elections

Finally, we can look at the change in turnout. Turnout increases were largest in Bavaria and parts of East Germany. As we have seen,  increased mobilization benefited the AfD and hurt the CDU/CSU.

Change in voter turnout in the 2017 German federal elections

Interpretation:  The AfD was able to asymmetrically mobilize voters that supported their anti-immigrant and anti-establishment positions. In September 2017, less than two weeks before the election, more than 80 percent of AfD supporters said that the “AfD is the only party through which I can express my protest against current policies”. The same share of AfD supporters agreed that the “AfD does not solve any problems, but at least they tell it like it is.” (Source: ARD-DeutschlandTREND). This, together with the turnout analysis, suggests that the AfD mobilized previously alienated voters by taking positions that were not represented by other parties in the political arena.

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How voter mobilization benefited the far-right German AfD

The September 24, 2017 German federal elections saw the far right, anti-immigrant and euro-skeptical party “Alternative for Germany” (“Alternative für Deutschland” – AfD) surging to third place behind chancellor Merkel’s center-left CDU/CSU and the Social Democrats. With the AfD’s success the focus of most observers, an interesting phenomenon has been largely overlooked, namely the fact that the AfD disproportionately benefited from increased turnout. We analyzed some of the available data at the level of electoral districts and found that the AfD was particularly strong in those districts that saw the largest increase in voter turnout.

The following table shows results from a regression analysis that models vote share as a function of a number of covariates, including the change in electoral participation (the turnout variable). Focussing on model 3 where the AfD’s vote share is the dependent variable, we find that the AfD massively benefitted from an increase in turnout. Increasing the change in turnout (i.e. mobilization) from its mean by one standard deviation leads to a one percentage point increase in AfD votes.

Determinants of Electoral Success, German Federal Elections 2017
CDU/CSU SPD AfD
(1) (2) (3)
Change in Turnout from 2013 0.214* -0.872*** 0.510***
(0.116) (0.119) (0.103)
Population Density -0.000*** -0.000*** -0.000***
(0.000) (0.000) (0.000)
Disposable income per capita 0.000* -0.000*** 0.000
(0.000) (0.000) (0.000)
Higher Education (percentage Abitur) -0.002*** 0.001*** -0.002***
(0.000) (0.000) (0.000)
Unemployment -0.006*** 0.011*** 0.003**
(0.001) (0.001) (0.001)
Percentage migration background -0.002*** -0.001*** 0.001***
(0.000) (0.000) (0.000)
East -0.073*** -0.134*** 0.112***
(0.008) (0.008) (0.007)
Constant 0.427*** 0.286*** 0.107***
(0.032) (0.033) (0.028)
Observations 299 299 299
R2 0.718 0.724 0.729
Adjusted R2 0.711 0.717 0.723
Residual Std. Error (df = 291) 0.032 0.033 0.028
F Statistic (df = 7; 291) 105.830*** 108.835*** 111.919***
Notes: ***Significant at the 1 percent level.
**Significant at the 5 percent level.
*Significant at the 10 percent level.

This is substantively important, given that the AfD fell short of clearing the threshold for parliamentary representation by just 0.3 percent in the 2013 federal elections. On the other hand, the SPD massively lost from an increase in turnout, showing that the party was not able to speak to its voters.

Of the other variables, we observe a number of significant effects. Most importantly the AfD is stronger in the east. On average, going from a Western district to one in the East increases AfD vote share by more than 11 percent.

Secondly, the AfD is stronger in less populated areas, i.e. outside the big cities. The AfD is also stronger where voters are less educated and where unemployment is higher.

Finally, the AfD is stronger in districts where the share of the population with a “migration background” is higher. It is important to note that the Federal Returning Office defines “migration background” as follows: “Migration background means foreign nationals plus all those Germans who came to Germany after 1955 plus all those Germans with at least one parent who came to Germany after 1955” – “Als Personen mit Migrationshintergrund werden alle zugewanderten und nicht zugewanderten Ausländer sowie alle nach 1955 auf das heutige Gebiet der Bundesrepublik Deutschland zugewanderten Deutschen und alle Deutschen mit zumindest einem nach 1955 auf das heutige Gebiet der Bundesrepublik Deutschland zugewanderten Elternteil definiert.” (Federal Returning Office). Immigrants from Russia who came to Germany in the early 1990s and who disproportionately support the AfD could explain this effect. (see, for example, here.)

How important was each of these variables in relation to each other? To see this, we can turn to z-score standardized coefficients (beta coefficients) and their graphic representation on the following figure:

The strongest predictor in relative terms is the East dummy, then the education variable, followed by population density, the change in turnout from 2013, the percentage of people with migration background, and finally the unemployment variable. Note that the variable that captures disposable income is not significant.

We can conclude by pointing out that the AfD success cannot be explained by economic grievances. The variable that captures income is not significant and the unemployment variable is a poor predictor once other factors have been taken into account. What matters most is the division between Eastern und Western districts. In the East, many voters seem to be alienated from established parties and possibly from the system as a whole. The AfD with their anti-system rhetoric was able to mobilize these voters. The geographic and educational divide of the electorate is reminiscent of the situation in other countries, for example in the US.