Empirical and Computational Approaches to Collective Choice editors, Simon Medcalfe, Shane Sanders
Contributor(s): Medcalfe, Simon
| Sanders, Shane.
Material type: 
Article
In:
Public Choice v.199, n.1-2, april 2024, special issueSummary: This special issue examines empirical and computational approaches to collective choice, the aggregation of individual preferences to form a public or social choice via some aggregation rule. Some of the aggregation rules considered herein include Borda rule, rank sum aggregation, and majority rule. Arrow (1951) demonstrated that axiomatic rationality at the individual level cannot assure freedom from aggregation paradoxes in collective choice, and this special issue considers several novel data sets and computational and experimental methods to assess the robustness of contemporary aggregation rules and settings. The collected papers provide much-needed evidence in a field that has traditionally presented empirical challenges.
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| OP 1443/2024/198/1/2 Public Choice | OP 1443/2024/198/3/4 Public Choice | OP 1443/2024/199/1/2 Public Choice | OP 1443/2024/199/1/2 special issue Empirical and Computational Approaches to Collective Choice | OP 1443/2024/200/1/2 Public Choice | OP 1443/2024/200/1/2 -1 The political business cycle of tax reforms | OP 1443/2024/200/1/2 -2 A tale of government spending efficiency and trust in the state |
This special issue examines empirical and computational approaches to collective choice, the aggregation of individual preferences to form a public or social choice via some aggregation rule. Some of the aggregation rules considered herein include Borda rule, rank sum aggregation, and majority rule. Arrow (1951) demonstrated that axiomatic rationality at the individual level cannot assure freedom from aggregation paradoxes in collective choice, and this special issue considers several novel data sets and computational and experimental methods to assess the robustness of contemporary aggregation rules and settings. The collected papers provide much-needed evidence in a field that has traditionally presented empirical challenges.
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