Do We Need Taagepera's Quantitatively Predictive Logical Models in Political Science? Evidence from Polish Local Elections

• Published in: Representation (McDougall Trust) Vol. 59; no. 2; pp. 329 - 345
• Main Author: Michalak, Bartłomiej
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 03.04.2023; Taylor & Francis Ltd
• Subjects: district magnitude; Electoral systems; Local elections; Logic; number of parties; Polish local elections; Political science; Predictions; Quantitative analysis; quantitatively predictive logical models
• ISSN: 0034-4893; 1749-4001
• DOI: 10.1080/00344893.2022.2075031

Rein Taagepera, considerably assisted by Matthew S. Shugart, is an author and advocate of one of the most interesting methodological approaches in recent years; and this applies not only to political science but also - more broadly - to social sciences based on quantitatively predictive logical models. This method consists of constructing - based on deduction and the principles of logic - a conceptual logical model which is subsequently supposed to be subject to testing by dint of a statistical analysis of empirical data. In this paper, on the basis of an analysis of the works by Taagepera and Shugart on the subject, a comprehensive reconstruction of the said approach shall be conducted. The quantitatively predictive logical model of the number of seat-winning parties in the electoral district shall serve as an exemplary pattern of constructing and - more importantly - it will allow for testing the predictive powers of this sort of models. So far no one has tried to test this model by looking at data from local elections. A large sample of electoral districts obtained from Polish local elections in 2018 gives such a unique opportunity.