Early warning indicators and macro-prudential policies: a credit network agent based model

Credit network configurations play a crucial role in determining the vulnerability of the economic system. Following the network-based financial accelerator approach, we constructed an agent based model reproducing an artificial credit network that evolves endogenously according to the leverage choices of heterogeneous firms and banks. Thus, our work aims at defining both early warning indicators for crises and policy precautionary measures based on the endogenous credit network dynamics. The model is calibrated on a sample of firms and banks quoted in the Japanese stock-exchange markets from 1980 to 2012. Both empirical and simulated data suggest that credit and connectivity variations could be used as early warning measures for crises. Moreover, targeting banks that are central in the credit network in terms of size and connectivity, the capital-related macro-prudential policies may reduce systemic vulnerability without affecting aggregate output.