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Bei der Entwicklung der räumlichen Modelle des Parteienwettbewerbs spielt die Valenz eine wichtige Rolle. Trotz der theoretischen Relevanz bleibt die Mess- und Schätzmethode der Valenz unterentwickelt. Angesichts dieser Forschungslücke schlägt dieser Beitrag ein statistisches Modell vor, das die gleichzeitige Schätzung der Kandidatenpositionen und der Valenz ermöglicht. Ein wichtiger Vorzug dieses Modells liegt darin, dass man nur die Kandidatenbeurteilungen per Skalometer benötigt, der in den meisten Umfragedaten verfügbar ist. Dieses Modell wird auf Daten angewendet, die in Rahmen der Konstanzer Oberbürgermeisterwahl 2012 erhoben wurden.
We draw attention to a simple yet underappreciated way of forecasting the outcomes of elections involving two rounds of voting: surveying the voters’ candidate evaluations in first round exit polls, poststratifying the sample proportions of reported votes to official first round election returns, and redistributing the votes for eliminated competitors according to their supporters’ lower-order preferences among the viable alternatives in round two. We argue that the approach is likely to outperform standard pre-election surveys, due to its better coverage and reduced measurement error, and the possibility of correcting for sample selection. We set out the practical details of the method and demonstrate its usefulness by employing a recent German mayoral election as an empirical case. Thirteen candidates were competing in the first round, while there were six candidates in the decisive second round. The runoff result was forecast two weeks in advance with an average absolute error of less than one percentage point.