Publications


Thurner, P. W., Mauerer, I., Bort, M., Klima, A. & Küchenhoff, H. (2020). Integrating Large-Scale Online Surveys and Aggregate Data at the Constituency Level: The Estimation of Voter Transitions in the 2015 British General Elections. Survey Research Methods 14(5): 461–476. doi:0.18148/srm/2020.v14i5.7628

 

What have been the underlying voter shifts that led to the victory of the Conservative Party in the 2015 British general election – against all predictions by pollsters? Analyses of voter transitions based on (online) surveys and recall questions are plagued by sampling and response biases, whereas aggregate data analyses are suspect of the well-known ecological fallacy. We propose a systematic statistical combination of individual-level survey and administrative data at the constituency level to identify regional electoral shifts between the 2010 to 2015 British general elections. The large-scale individual-level data collected by the British Election Study Internet Panel (BESIP) allow us to locate more than 28,000 respondents in their constituencies. We estimate voter transitions based on a recently developed Bayesian Hierarchical Hybrid Multinomial Dirichlet (HHMD) model. We discover substantial deviances from pure survey-based estimations of transition matrices.


Thurner, P. W., Kunz, F., Miclut, A., Mauerer, I., Klima, A. & Küchenhoff, H. (2020). Die Schätzung von Wählerwanderungen zwischen den Bundestagswahlen 2013–2017 mit Hilfe von Online-Paneldaten und Aggregatdaten in Hybridmodellen. Wahlen und Wähler – Analysen aus Anlass der Bundestagswahl 2017. Edited by H. Schoen, & Weßels, B., Springer VS. Forthcoming.


Mauerer, I. (2020). The Neglected Role and Variability of Party Intercepts in the Spatial Valence Approach. Political Analysis 28(3): 303–317.

doi:10.1017/pan.2019.41

 

Empirical applications of the spatial theory of elections typically rely on the discrete choice framework to arrive at probabilistic voting models. Whereas in the classic model voter choice is solely a function of spatial proximity, neo-Downsian models also incorporate voter-specific nonpolicy attributes, which are represented by sociodemographic characteristics. One prominent line of such probabilistic  models, Schofield’s Valence Model, additionally includes party valences into voter utility functions. The model rests on the estimated party intercepts to measure the valence advantages empirically. The party intercepts are ordered based on their values, and then this valence ranking is used further to predict equilibrium locations. The paper demonstrates that this measurement strategy  does not provide unique results in fully specified models due to central properties of discrete choice models and the specific nature of party intercepts in these models. Drawing on a simple example based on mass election surveys from Germany, it is shown that the valence ranking, the crucial factor to investigate how valence differences affect the nature of spatial competition, is highly sensitive to arbitrary coding decisions. As a consequence, it is impossible to represent valence with the constants and to infer something substantial from the resulting valence ranking.


Mauerer, I. & Schneider, M. (2019). Perceived Party Placements and Uncertainty on Immigration in the 2017 German Election. Jahrbuch für Handlungs- und Entscheidungstheorie Volume 11. Edited by M. Debus, Tepe, M. & Sauermann, J., Wiesbaden: Springer Nature, 117–143. doi: 10.1007/978-3-658-23997-8

 

Almost all national election studies contain policy scales that are intended to measure where respondents perceive parties or candidates on central campaign issues. These placements form the basis for models of survey responses, party perceptions, and voter choice. It is well known that the placements might be affected by uncertainty. We use the finite mixture model `BetaBin' to study response patterns to party placements on policy issues. The model consists of a placement part and an uncertainty part. Whereas the placement part of the model accounts for lower and higher placements on the ordinal scales, the uncertainty component accounts for tendencies to locate the parties on the middle or at the extremes of the policy scales. We use the 2017 German national election and apply the model to the immigration issue. Our results demonstrate that uncertainty strongly influences the respondents' perceptions of most parties. Neglecting this structure leads to worse models as indicated by performance measures.


Mauerer, I., Pößnecker, W., Thurner, P. W., & Tutz, G. (2015). Modeling Electoral Choices in Multiparty Systems with High-Dimensional Data: A Regularized Selection of Parameters Using the Lasso Approach. Journal of Choice Modelling 16: 23-42. doi: 10.1016/j.jocm.2015.09.004

 

The increased usage of discrete choice models in the analysis of multiparty elections faces one severe challenge: the proliferation of parameters, resulting in high-dimensional and difficult-to-interpret models. For example, the application of a multinomial logit model in a party system with J parties results in maximally J−1 parameters for chooser-specific attributes (e.g., sex and age). For the specification of alternative-specific attributes (usually: positions on issues and issue distances), maximally J parameters for each political issue can be estimated. Thus, a model of party choice with five parties based on three political issues and ten voter attributes already produces 59 possible coefficients. As soon as we allow for interaction effects to detect segment-specific reactions to issues, the situation is even aggravated. In order to systematically and efficiently identify relevant predictors in voting models, we derive and use Lasso-type regularized parameter selection techniques that take into account both individual- and alternative-specific variables. Most importantly, our new algorithm can handle for the first time the alternative-wise specification of the attributes of alternatives. Applying the specifically adjusted Lasso method to the 2009 German Parliamentary Election, we demonstrate that our approach massively reduces the models' complexity and simplifies their interpretation. Lasso-penalization clearly outperforms the simple ML estimator. The results are illustrated by innovative visualization methods, the so-called effect star plots.


Mauerer, I., Thurner, P. W., & Debus, M. (2015). Under Which Conditions do Parties Attract Voters’ Reactions to Issues? Party-Varying Issue Voting in German Elections 1987-2009. West European Politics 38(6): 1251–1273. doi: 10.1080/01402382.2015.1026562

 

Are voters’ choices influenced by parties’ position-taking and communication efforts on issues during a campaign? And if so, do voters’ reactions to issues differ across parties? This article outlines a research design for the statistical identification of party-varying issue reactions within the established paradigm of the Spatial Theory of Voting. Using a special feature of conditional logit and probit models – i.e. the estimation of alternative-specific coefficients instead of fixed ‘generic’ issue distance effects – it is possible to detect asymmetrically attached issue saliencies at the level of the voters, and hence at the demand-side of politics. This strategy opens a new way to systematically combine insights obtained by saliency approaches with the Spatial Theory of Voting. An application to the German parliamentary elections from 1987 to 2009 demonstrates that it is predominantly parties taking polar positions – and, more specifically, niche parties taking polar positions – that induce such asymmetric issue voting.


Thurner, P. W., Mauerer, I., & Binder, M. (2011). Parteienspezifisches Issue Voting bei den Bundestagswahlen 2002 bis 2009. In Wählen in Deutschland. Politische Vierteljahresschrift, Sonderheft 45, 302-320. Edited by R. Schmitt-Beck, Baden-Baden: Nomos, 302–320. [Link]