Estimation of voter transitions based on ecological inference: an empirical assessment of different approaches

摘要

The analysis of voter transitions is an important area of electoral studies. A main strategy is to use aggregate data provided by the offices of statistics regarding districts, precincts, communities etc. and to rely on ecological inference. Ecological inference, however, is plagued by the well-known indeterminacy problem. In this article, we present the so far most extensive systematic empirical comparison of commonly used approaches for ecological inference of the analysis of voter transitions. Our evaluation is based on diverse simulations for multiple assumptions and scenarios. Based on recent election data for the German metropolitan city Munich, we are able to show that an application of the hierarchical multinomial-Dirichlet model, which is implemented in the R-library eiPack, exhibits the best overall estimation performance. Other prominent approaches frequently used by practitioners, e.g. the Thomsen logit approach, proved to be inconsistent. Furthermore, we demonstrate that appropriate data preprocessing is crucial for achieving reliable results.