Production networks and failure avalanches

Although standard economics textbooks are seldom interested in production networks, modern economies are more and more based upon suppliers/customers interactions. One can consider entire sectors of the economy as generalised supply chains. We will take this view in the present paper and study under which conditions local failures to produce or simply to deliver can result in avalanches of shortage and bankruptcies across the network. We will show that a large class of models exhibit scale free distributions of production and wealth among firms and that metastable regions of high production are highly localised

Systemic risk in a network fragility model analyzed with probability density evolution of persistent random walks

We study the mean field approximation of a recent model of cascades on networks relevant to the investigation of systemic risk control in financial networks. In the model, the hypothesis of a trend reinforcement in the stochastic process describing the fragility of the nodes, induces a trade-off in the systemic risk with respect to the density of the network. Increasing the average link density, the network is first less exposed to systemic risk, while above an intermediate value the systemic risk increases. This result offers a simple explanation for the emergence of instabilities in financial systems that get increasingly interwoven. In this paper, we study the dynamics of the probability density function of the average fragility. This converges to a unique stable distribution which can be computed numerically and can be used to estimate the systemic risk as a function of the parameters of the model.Comment: 20 pages, 6 figure

The Community Structure of the Global Corporate Network

We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide the first quantitative assessment of the financial sector role in connecting the global economy

DebtRank: A microscopic foundation for shock propagation

The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008 - 2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks.Comment: 10 pages, 2 figure

A climate risk assessment of sovereign bonds' portfolio.

Aligning finance to sustainability requires metrics and methods to price forward-looking cli-mate risks and opportunities in financial contracts and in investors' portfolios. Traditionalapproaches to financial pricing cannot incorporate the nature of climate risks, i.e. deep uncertainty, non-linearity, complexity and endogeneity. To fill this gap, we develop a frameworkfor climate-financial risk assessment and management under uncertainty. We consider a riskaverse investor with an information set given by past market valuation, information on futureclimate economic shocks, and utility maximization based on the minimization of the ClimateValue at Risk (VaR) in presence of incomplete markets. We then consider a disorderly policy transition to 2°C scenarios that leads to unanticipated shocks in economic trajectories of fossil fuel and renewable energy sectors, estimated using Integrated Assessment Models. We model the shock transmission from the change in sectors' Gross Value Added to firms' profitability and to sovereign fiscal revenues. We then introduce the forward-looking climatepolicy shocks in sovereign bonds valuation introducing scenario- conditioned financial riskmetrics (Climate VaR, Climate Spread). We provide an application to OECD sovereignbonds of Austrian National Bank's portfolio. We find that investments' climate alignmentcan strengthen the sovereign fiscal and financial position by decreasing the climate spread. In contrast, misalignment can negatively affect countries' economic competitiveness and financial stability, and thus the performance of investors who own such bonds. Our analysissupports investors' portfolios risk management strategies in the low-carbon transition andand financial supervisors in the design of prudential risk measures

Two sides of the same coin: Green Taxonomy alignment versus transition risk in financial portfolios

We develop the first top-down method to estimate the greenness of financial portfolios, in terms of alignment to the EU Taxonomy for sustainable activities. We also develop a method to estimate, at the same time, the portfolio exposure to climate transition risk. We provide sector-level, standardized and transparent coefficients for both estimates, based on definitions of greenness and transition risk that are applicable across countries. We analyse the portfolios of Euro Area investors in 2022, based on the confidential Securities Holdings Statistics of the European Central Bank. We find that, overall, the greenness of Euro Area investors’ portfolios is lower than their exposure to transition risk (2.8% vs. 11.7%). Across financial institutions, we estimate greenness and exposure to transition risk, respectively, at 3.2% and 12% for investment funds, at 0.8% and 5% for banks and at 4.8% and 15.1% for insurers. Our analysis also shows that investors with large amounts invested in green activities can have at the same time large exposures to transition risk