A Comparison Between the Methods of Apportionment Using Power Indices: the Case of the US Presidential Elections

Fabrice Barthélémy () and Mathieu Martin

Annals of Economics and Statistics, 2011, issue 101-102, 87-106

Abstract: In this paper we compare five well-known methods of apportionment, advanced respectively by Adams, Dean, Hill, Webster and Jefferson. The criterion used for this comparison is the minimization of the distance between a power vector and a population vector. Power is measured with the well-known Banzhaf power index; the populations are those of the constituent states of the U.S.A. We first explain the conditions under which this comparison has plausibility. We then compare apportionment methods in terms of their capacity to move power in states closer to their populations. The election of the U.S. President by an electoral college is studied by examining 22 censuses since 1790. Our analysis is largely based on that used in the book by Balinski and Young [2001]. The empirical findings are linked to theoretical results.

Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.jstor.org/stable/41615475 (text/html)

Related works:
Working Paper: A comparison between the methods of apportionment using power indices: the case of the U.S. presidential elections (2011)
Working Paper: A comparison between the methods of apportionment using power indices: the case of the U.S. presidential election (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:2011:i:101-102:p:87-106

Access Statistics for this article

Annals of Economics and Statistics is currently edited by Laurent Linnemer

More articles in Annals of Economics and Statistics from GENES Contact information at EDIRC.
Bibliographic data for series maintained by Secretariat General () and Laurent Linnemer ().