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.