A Mathematical Model For Optimal Decisions In A Representative Democracy
Magdon-Ismail, Malik, Xia, Lirong
–Neural Information Processing Systems
Direct democracy, where each voter casts one vote, fails when the average voter competence falls below 50%. This happens in noisy settings when voters have limited information. Representative democracy, where voters choose representatives to vote, can be an elixir in both these situations. We introduce a mathematical model for studying representative democracy, in particular understanding the parameters of a representative democracy that gives maximum decision making capability. Our main result states that under general and natural conditions, 1. for fixed voting cost, the optimal number of representatives is linear; 2. for polynomial cost, the optimal number of representatives is logarithmic.
Neural Information Processing Systems
Dec-31-2018
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