The Essential Role of Statistical Inference in Evaluating Electoral Systems: A Response to DeFord et al

Katz, King, and Rosenblatt (2020, American Political Science Review 114, 164–178) introduces a theoretical framework for understanding redistricting and electoral systems, built on basic statistical and social science principles of inference. DeFord et al. (2021, Political Analysis, this issue) inst...

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Bibliographic Details
Published in:Political analysis 2023-07, Vol.31 (3), p.325-331
Main Authors: Katz, Jonathan N., King, Gary, Rosenblatt, Elizabeth
Format: Article
Language:English
Subjects:
Bias
Election results
Elections
Electoral systems
Estimates
Redistricting
Social sciences
Statistical inference
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Summary:Katz, King, and Rosenblatt (2020, American Political Science Review 114, 164–178) introduces a theoretical framework for understanding redistricting and electoral systems, built on basic statistical and social science principles of inference. DeFord et al. (2021, Political Analysis, this issue) instead focuses solely on descriptive measures, which lead to the problems identified in our article. In this article, we illustrate the essential role of these basic principles and then offer statistical, mathematical, and substantive corrections required to apply DeFord et al.’s calculations to social science questions of interest, while also showing how to easily resolve all claimed paradoxes and problems. We are grateful to the authors for their interest in our work and for this opportunity to clarify these principles and our theoretical framework.
ISSN:1047-1987
1476-4989
DOI:10.1017/pan.2021.46