Testing Penrose Limit Theorem: A case study of French local data

In 1946, Penrose argued that in a weighted quota game, if the number of players is sufficiently large and the weight associated with the largest player is bounded, the Banzhaf/Penrose power of a player is approximately proportional to its weight. This conjecture is now known as the Penrose Limit Theorem (PLT). However, as the weight of the largest player increases and/or when it is surrounded by an ocean of small players, its Banzhaf/Penrose power approaches one, even if its own weight is far less than 50% of the total weight. This paper aims to empirically determine the conditions under which this assertion holds. Can we identify the threshold weight (as a percentage of the total sum of weights) below which the Penrose Limit Theorem applies? To address this question, we analyze a panel of 1,251 French intercommunal councils, where each town is represented by a given number of delegates. In particular, we compare the normalized Banzhaf index of the largest city to its weight in the council. As a consequence, we propose an alternative allocation rule that French law might adopt, considering factors such as the weight of the largest city in the council and the number of its members. • Empirical validation of Penrose’s Limit Theorem in French inter-communal councils reveals its dependence on municipality size and council composition. • The theorem holds as long as the size of the major player is bounded, and the number of players plays a role, too. • Using a toy theoretical model, an original apportionment method is proposed to reduce the power of the largest municipality and promote fairer representation.

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Publication Details

Journal
Mathematical Social Sciences
Published
2025-05-24
DOI
https://doi.org/10.1016/j.mathsocsci.2025.102418
Citations
1
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
1.49

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article

Testing Penrose Limit Theorem: A case study of French local data

Vincent Merlin, Zineb Abidi
1 citations
Mathematical Social Sciences
Data Management and Algorithms
1.49
article

Testing Penrose Limit Theorem: A case study of French local data

Vincent Merlin, Zineb Abidi
article en
1 citations

Abstract

In 1946, Penrose argued that in a weighted quota game, if the number of players is sufficiently large and the weight associated with the largest player is bounded, the Banzhaf/Penrose power of a player is approximately proportional to its weight. This conjecture is now known as the Penrose Limit Theorem (PLT). However, as the weight of the largest player increases and/or when it is surrounded by an ocean of small players, its Banzhaf/Penrose power approaches one, even if its own weight is far less than 50% of the total weight. This paper aims to empirically determine the conditions under which this assertion holds. Can we identify the threshold weight (as a percentage of the total sum of weights) below which the Penrose Limit Theorem applies? To address this question, we analyze a panel of 1,251 French intercommunal councils, where each town is represented by a given number of delegates. In particular, we compare the normalized Banzhaf index of the largest city to its weight in the council. As a consequence, we propose an alternative allocation rule that French law might adopt, considering factors such as the weight of the largest city in the council and the number of its members. • Empirical validation of Penrose’s Limit Theorem in French inter-communal councils reveals its dependence on municipality size and council composition. • The theorem holds as long as the size of the major player is bounded, and the number of players plays a role, too. • Using a toy theoretical model, an original apportionment method is proposed to reduce the power of the largest municipality and promote fairer representation.

Mathematical Social SciencesVol. 137
Centre National de la Recherche Scientifique (FR), Université Paris-Est Créteil (FR), Normandie Université (FR), Équipe de Recherche sur l’Utilisation des Données Individuelles en Lien avec la Théorie Économique (FR), Université de Caen Normandie (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 19%
Data Management and Algorithms
1.49
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