Welfare and Distributional Effects of Joint Intervention in Networks

2022-06-08

Social Science Research Network

AI Summary

This paper investigates how a planner can jointly intervene in agents’ marginal utilities and network link weights to maximize social welfare while characterizing distributional consequences. We model strategic interactions and externality propagation using game-theoretic tools and develop a network equilibrium framework. We formally characterize the efficiency–fairness trade-off under joint intervention—the first such analysis—and introduce a distribution-sensitive metric for intervention effectiveness. Using convex optimization and counterfactual welfare allocation analysis, we uncover an inherent paradox: aggregate welfare gains co-occur with increased inequality in welfare distribution. Our main contributions are: (1) the first theoretical model of welfare trade-offs under joint intervention; (2) Pareto-improving design principles for interventions; and (3) computationally tractable, interpretable policy guidelines for network governance that simultaneously address efficiency and equity objectives.

Problem

• Optimizing joint interventions in agent utilities and network link weights
• Analyzing welfare effects through network eigenvalues and eigen-centrality dispersion
• Exploring efficiency-equity trade-offs between joint and single interventions

Innovation

• Joint intervention optimizes both agent utilities and link weights
• Optimal link changes proportional to eigen-centrality products
• Network converges to complete or bipartite structure with large budget