Stability of networks under horizon-K farsightedness

B-Tier
Journal: Economic Theory
Year: 2019
Volume: 68
Issue: 1
Pages: 177-201

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Abstract We introduce the concept of a horizon-K farsighted set to study the influence of the degree of farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. A set of networks $$G_{K}$$ G K is a horizon-K farsighted set if three conditions are satisfied. First, external deviations should be horizon-K deterred. Second, from any network outside of $$G_{K}$$ G K there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ G K . Third, there is no proper subset of $$G_{K}$$ G K satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ G 1 is always unique. For generic allocation rules, the set $$G_{1}$$ G 1 always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set, and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks.

Technical Details

RePEc Handle
repec:spr:joecth:v:68:y:2019:i:1:d:10.1007_s00199-018-1119-7
Journal Field
Theory
Author Count
3
Added to Database
2026-01-24