Business Fluctuations and Bankruptcy Avalanches in an Evolving Network Economy

We analyze the properties of a three-sector network economy characterized by credit relationships connecting downstream and upstream firms (inside credit) and credit relationships connecting firms and banks (outside credit). The network topology changes over time due to an endogenous process of partner selection (the preferred-partner choice rule). The output of simulations shows that a business cycle at the macroeconomic level can develop as a consequence of the complex interaction of the heterogeneous financial conditions of the agents involved. In this paper, we focus on the emergence of bankruptcy crises: the bankruptcy of one agent can bring about the bankruptcy of one or more other agents in a snowball effect of more or less large size, depending on the network structure and the incidence of non-performing loans on balance sheets of agents involved

Credit Chains and Bankruptcy Propagation in Production Networks

We present a simple model of a production network in which firms are linked by supplier-customer relationships involving extension of trade-credit. Our aim is to identify the minimal set of mechanisms which reproduce qualitatively the main stylized facts of industrial demography, such as firms' size distribution, and, at the same time, the correlation, over time and across firms, of output, growth and bankruptcies. The behavior of aggregate variables can be traced back to the direct firm-firm interdependence. In this paper, we assume that the number of firms is constant and the network has a periodic static structure. But the framework allows further extensions to investigate which network structures are more robust against domino effects and, if the network is let to evolve in time, which structures emerge spontaneously, depending on the individual strategies for orders and delivery

Liaisons Dangereuses: Increasing Connectivity, Risk Sharing, and Systemic Risk

We characterize the evolution over time of a network of credit relations among financial agents as a system of coupled stochastic processes. Each process describes the dynamics of individual financial robustness, while the coupling results from a network of liabilities among agents. The average level of risk diversification of the agents coincides with the density of links in the network. In addition to a process of diffusion of financial distress, we also consider a discrete process of default cascade, due to the re-evaluation of agents’ assets. In this framework we investigate the probability of individual defaults as well as the probability of systemic default as a function of the network density. While it is usually thought that diversification of risk always leads to a more stable financial system, in our model a tension emerges between individual risk and systemic risk. As the number of counterparties in the credit network increases beyond a certain value, the default probability, both individual and systemic, starts to increase. This tension originates from the fact that agents are subject to a financial accelerator mechanism. In other words, individual financial fragility feeding back on itself may amplify the effect of an initial shock and lead to a full fledged systemic crisis. The results offer a simple possible explanation for the endogenous emergence of systemic risk in a credit network.

Financially Constrained Fluctuations in an Evolving Network Economy

We explore the properties of a credit network characterized by inside credit - i.e. credit relationships connecting downstream (D) and upstream (U) firms - and outside credit - i.e. credit relationships connecting firms and banks. The structure of the network changes over time due to the preferred-partner choice rule: each agent chooses the partner who charges the lowest price. The net worth of D firms turns out to be the driver of fluctuations. U production, in fact, is determined by demand of intermediate inputs on the part of D firms and production of the latter is financially constrained, i.e. determined by the availability of internal finance proxied by net worth. The output of simulations shows that at the macroeconomic level a business cycle can develop as a consequence of the complex interaction of the agents' financial conditions. We can also reproduce the main stylized facts of firms' demography, i.e. the power law distribution of firms' size and the Laplace distribution of firms' growth rates.

Seasonal variations in the incidence of cranial nerve paralysis.

The aim of the study was to verify whether there is a seasonal pattern in the occurrence of cranial nerve paralysis. All patients admitted to the Emergency Department of St Anna Hospital, Ferrara, Italy, from 1 January 1991 to 31 December 1997, were reviewed. Cranial nerve paralysis was diagnosed in 126 cases: the oculomotor nerve accounted for 46 cases, the trochlear nerve for 14, and the abducens nerve for 66. The frequencies of cases involving the oculomotor nerve and of all cases were significantly higher in winter than in the other seasons. Compared with other 2-month periods, the highest number of total cases occurred in November to December. Chronobiological analysis of the data for individual months showed a rhythmic 12-month pattern for the total population, with a weakly significant peak in January

Economic dynamics with financial fragility and mean-field interaction: a model

Following the statistical mechanics methodology, firstly introduced in macroeconomics by Aoki [1996,2002], we provide some insights to the well known works of Greenwald and Stiglitz [1990, 1993]. Specifically, we reach analytically a closed form solution of their models overcoming the aggregation problem. The key idea is to represent the economy as an evolving complex system, composed by heterogeneous interacting agents, that can partitioned into a space of macroscopic states. This meso level of aggregation permits to adopt mean field interaction modeling and master equation techniques.Comment: APFA6 proceeding

Self-organized model of cascade spreading

We study simultaneous price drops of real stocks and show that for high drop thresholds they follow a power-law distribution. To reproduce these collective downturns, we propose a minimal self-organized model of cascade spreading based on a probabilistic response of the system elements to stress conditions. This model is solvable using the theory of branching processes and the mean-field approximation. For a wide range of parameters, the system is in a critical state and displays a power-law cascade-size distribution similar to the empirically observed one. We further generalize the model to reproduce volatility clustering and other observed properties of real stocks.Comment: 8 pages, 6 figure

An agent based decentralized matching macroeconomic model

In this paper we present a macroeconomic microfounded framework with heterogeneous agents-individuals, firms, banks-which interact through a decentralized matching process presenting common features across four markets-goods, labor, credit and deposit. We study the dynamics of the model by means of computer simulation. Some macroeconomic properties emerge such as endogenous business cycles, nominal GDP growth, unemployment rate fluctuations, the Phillips curve, leverage cycles and credit constraints, bank defaults and financial instability, and the importance of government as an acyclical sector which stabilize the economy. The model highlights that even extended crises can endogenously emerge. In these cases, the system may remain trapped in a large unemployment status, without the possibility to quickly recover unless an exogenous intervention takes place

Global Systems Science and Policy

The vision of Global Systems Science (GSS) is to provide scientific evidence and means to engage into a reflective dialogue to support policy-making and public action and to enable civil society to collectively engage in societal action in response to global challenges like climate change, urbanisation, or social inclusion. GSS has four elements: policy and its implementation, the science of complex systems, policy informatics, and citizen engagement. It aims to give policy makers and citizens a better understanding of the possible behaviours of complex social systems. Policy informatics helps generate and evaluate policy options with computer-based tools and the abundance of data available today. The results they generate are made accessible to everybody—policymakers, citizens—through intuitive user interfaces, animations, visual analytics, gaming, social media, and so on. Examples of Global Systems include epidemics, finance, cities, the Internet, trade systems and more. GSS addresses the question of policies having desirable outcomes, not necessarily optimal outcomes. The underpinning idea of GSS is not to precisely predict but to establish possible and desirable futures and their likelihood. Solving policy problems is a process, often needing the requirements, constraints, and lines of action to be revisited and modified, until the problem is ‘satisficed’, i.e. an acceptable compromise is found between competing objectives and constraints. Thus policy problems and their solutions coevolve much as in a design process. Policy and societal action is as much about attempts to understand objective facts as it is about the narratives that guide our actions. GSS tries to reconcile these apparently contradictory modes of operations. GSS thus provides policy makers and society guidance on their course of action rather than proposing (illusionary) optimal solutions