Method(olog)ische Grundlagen der Statistik und ihre Anwendungen



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Towards a Paradigmatic Shift in Pre-election Polling Adequately Including Still Undecided Voters - Some Ideas Based on Set-Valued Data for the 2021 German Federal Election.


Dominik Kreiß, Thomas Augustin

Within this paper we develop and apply new methodology adequately including undecided voters for
the 2021 German federal election. Due to a cooperation with the polling institute Civey, we are in
the fortunate position to obtain data in which undecided voters can state all the options they are still
pondering between. In contrast to conventional polls, forcing the undecided to either state a single
party or to drop out, this design allows the undecided to provide their current position in an accurate
and precise way. The resulting set-valued information can be used to examine structural properties of
groups undecided between specific parties as well as to improve election forecasting. For forecasting,
this partial information provides valuable additional knowledge, and the uncertainty induced by the
participants’ ambiguity can be conveyed within interval-valued results. Turning to coalitions of
parties, which is in the core of the current public discussion in Germany, some of this uncertainty
can be dissolved as the undecided provide precise information on corresponding coalitions. We
show structural differences between the decided and undecided with discrete choice models as well
as elaborate the discrepancy between the conventional approach and our new ones including the
undecided. Our cautious analysis further demonstrates that in most cases the undecideds’ eventual
decisions are pivotal which coalitions could hold a majority of seats. Overall, accounting for the
populations’ ambiguity leads to more credible results and paints a more holistic picture of the political
landscape, pathing the way for a possible paradigmatic shift concerning the adequate inclusion of
undecided voters in pre-election polls.

Arxiv Technical Report (Uploaded 24.09.2021):