Optimal intervention in economic networks using influence maximization methods

We consider optimal intervention in the Elliott-Golub-Jackson network model \cite{jackson14} and we show that it can be transformed into an influence maximization-like form, interpreted as reverse of a default cascade. Our analysis problem extends well-established targeting results to economic setting, which requires additional theoretical steps. prove several about intervention: is NP-hard cannot approximated constant factor polynomial time. In turn, randomizing failure thresholds leads version monotone submodular, for existing powerful approximations time applied. addition intervention, also practical consequences our other problems: (1) computationally hard calculate expected values network, (2) maximization algorithms enable efficient importance sampling stress testing large scenarios. illustrate on firms connected through input-output linkages inferred from World Input Output Database.