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Econometrica
Article
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zbMATH Open
Article . 2019
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Econometrica
Article . 2019 . Peer-reviewed
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https://dx.doi.org/10.7916/d8-...
Other literature type . 2018
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Trading Votes for Votes. A Dynamic Theory

Trading votes for votes. A dynamic theory
Authors: Palfrey, Thomas R.; Casella, Alessandra;

Trading Votes for Votes. A Dynamic Theory

Abstract

We develop a framework to study the dynamics of vote trading over multiple binary issues. We prove that there always exists a stable allocation of votes that is reachable in a finite number of trades, for any number of voters and issues, any separable preference profile, and any restrictions on the coalitions that may form. If at every step all blocking trades are chosen with positive probability, convergence to a stable allocation occurs in finite time with probability 1. If coalitions are unrestricted, the outcome of vote trading must be Pareto optimal, but unless there are three voters or two issues, it need not correspond to the Condorcet winner.

Country
United States
Keywords

330, Vote Trading, Economics, FOS: Political science, condorcet winner, stability, Resource and cost allocation (including fair division, apportionment, etc.), vore trading, voting, Voting theory, Voting, Condorcet Winner, Stability, Political science, Voting, Vote Trading, Condorcet Winner, Stability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
bronze