Crisis Propagation Research Articles

Establishing the robustness of chip trade networks by dynamically considering topology and risk cascading propagation

Risk cascading propagation research mostly focuses on complex theoretical networks. Recently, the vulnerability of international chip supply has increased notably, and it is strategically important to explore how shortage risk affects the emergence dynamics of the real chip trade systems. This study abstracts the global chip trade relationship data for 2009–2021 into multiple asymmetrically weighted networks. Using macro-network and micro-node indicators, we explore the topological traits of international chip trade networks and their evolutionary laws. Accordingly, we propose risk cascading propagation models driven by node failure and edge restraint and further innovate to open up the research paradigm of focused-edge networks. Furthermore, a community infection-driven risk cascading propagation mechanism that incorporates community risk absorption capacity is introduced, considering both the propagation attenuation effects and the trade dependency degree. A multi-dimensional dynamic perspective reveals the hidden systemic risks in international chip trade. The main results are as follows: first, international chip trade networks are highly connected and cohesive, consistent with small-world characteristics. Second, the proportion of economies that collapse because of supply shortage risk shocks increases with the impact coefficient α/β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha /\\beta$$\\end{document}. The dominant power in chip crisis propagation has shifted from Europe and America to Asia, and mainland China’s risk penetration capacity has enhanced significantly. Third, focused-edge networks conform to a multi-hub radiation pattern. Before the COVID-19 pandemic, the degree of control and spillover effects of chip supply shortages in hub economies on the international trade was increasing progressively. Fourth, an increase in absorption capacity λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document} or attenuation factor γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document} consistently leads to a decline in avalanche scale, with λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document} exhibiting critical thresholds. These findings will help policymakers pursue efficient management strategies for chip trade, thereby improving supply stability and security.

Describing financial crisis propagation through epidemic modelling on multiplex networks

This paper proposes a novel framework for modelling the spread of financial crises in complex networks, combining financial data, Extreme Value Theory and an epidemiological transmission model. We accommodate two key aspects of contagion modelling: fundamentals-based contagion, where the transmission is due to direct financial linkages, and pure contagion, where a crisis might trigger additional crises due to global effects. We use stock price, geographical location and economic sector data for a set of 398 companies to construct multiplex networks of four layers, on which a susceptible-infected-recovered transmission model is defined, in order to model the spread of financial shocks between companies by accounting for their interconnected nature. By utilizing stock price data for the 2008 and 2020 financial crises, we investigate and assess the effectiveness of our model in forecasting the propagation of financial shocks through the network, where a shock is detected by measuring stock price volatility. The results suggest that the proposed framework is effective in predicting the spread of financial crises. Our findings demonstrate the significance of each layer of the multiplex network structure, which differentiates between various transmission pathways, for predicting the number of affected companies, as well as for company-, sector- or location-specific predictions.

Crisis spreading in multinational firms’ network: the dual influence of local interactions

This study investigates the characteristics of multinational firm’s interactions within and across activity sectors and the impact of intra-urban connections, during crisis propagation. By employing data that reflect ownership relations aggregated on the city level, we constructed the partial-multiplex, directed network of cities, divided into five layers by activity sector. The network was examined in two states: one excluding intra-urban interactions and one including them. The difference between these two states highlight the significant role of intra-urban networking processes in the global economy. The five layers differ both structurally and in terms of vulnerability during crisis propagation. The Knowledge Intensive Services (KIS) layer is the densest and most populous layer of all and its firms are more likely to be owners than subsidiaries. Using a simple stochastic Susceptible-Infected-Recovered (SIR) model, we simulated a crisis diffusion on the network of cities. Our results revealed that in the absence of intra-urban connections, KIS was both the most vulnerable and most influential layer in crisis propagation. The inclusion of intra-urban links sets off a complex interplay of factors that affect diffusion outcomes in nuanced ways: while it generally enhances the impact of the crisis and the influence across layers becomes rather homogeneous it can also have a protective effect, in cases of very dense and well-connected layers, such as KIS.

Research on the crisis propagation in the global coal trade under the Russia-Ukraine conflict

The outbreak of the 2022 Russia-Ukraine conflict exacerbated the natural gas supply shortage in European countries. European countries restarted coal-fired power plants to maintain economic and social operations. The uneven distribution of coal resources in the world makes coal international trade inevitable. The intricate trade relations between trading countries have formed a coal trade network. When a country’s coal exports are limited due to geopolitical factors, it will cause coal supply risks. The risk will spread to more countries along the trade network, eventually leading to the collapse of the trade network. This paper builds a crisis propagation model of the coal supply under the Russia-Ukraine conflict using the cascading failure model. The results showed that the Czech Republic, Ireland, Portugal, and Bulgaria become abnormal as the proportion of coal exports β increases. When the Russian Federation reduced its coal exports by 80% and countries maintained only 10% coal exports against crisis, 23 European countries were the worst. Iceland, Ireland, Turkey and other countries were spread by the indirect risk and became abnormal countries. The Czech Republic and Bulgaria were spread by multiple risk and became abnormal countries.

Retracted: Recognition and Modeling of Crisis Propagation Patterns Combined with Robot Simulation of Social Networks

Retracted: Recognition and Modeling of Crisis Propagation Patterns Combined with Robot Simulation of Social Networks

Correction: Crisis transmission degree measurement under crisis propagation model

Correction: Crisis transmission degree measurement under crisis propagation model

Crisis transmission degree measurement under crisis propagation model.

The online version contains supplementary material available at 10.1007/s43546-022-00361-9.

Recognition and Modeling of Crisis Propagation Patterns Combined with Robot Simulation of Social Networks

In order to improve the identification effect of a crisis propagation mode, this paper studies the crisis propagation mode of social networks and uses an intelligent method to identify the crisis propagation mode. Moreover, this paper analyzes and deduces the features of the modulated signal from the two aspects of spectrum and autocorrelation functions and extracts and simulates the features of signals of different modulation types. In addition, this paper verifies the proposed recognition method from two aspects through theoretical experiments and measured data and builds an intelligent model. Through the experimental research, it can be seen that the identification effect and the control effect of the crisis propagation model based on the social network proposed in this paper are relatively obvious.

Simulation Analysis of Supply Crisis Propagation Based on Global Nickel Industry Chain

Nickel is a key metal in the low-carbon transition. The industrial chain is a chain network organization system composed of various layers from the initial production of raw materials to the final product sales. The intensified contradiction between supply and demand can easily lead to the problem of resource supply security, and the occurrence of supply shortages will endanger the healthy and orderly development of the whole industrial chain. Therefore, from the perspective of the industrial chain and based on the trade data related to the nickel industrial chain, this study first constructs a multi-layer network model of the nickel industrial chain, and analyzes its trade structure characteristics and the correlation between different layers. It is found that the export policies of resource exporting countries may influence trade structure characteristics. On this basis, a multi-layer network crisis propagation model of the nickel industrial chain is constructed to simulate the impact and its propagation path of Indonesia supply shock on the entire industrial chain. With the increase of supply shock in Indonesia, the impact of crisis gradually concentrates to the downstream. Along the industrial chain, the number of affected countries gradually increases, but the difference in the impact degree gradually decreases. In addition, there are certain differences in countries affected by crisis at different layers of the industrial chain, and the crisis spreads mainly from China and Japan to the countries in midstream and downstream. The research results can provide corresponding policy suggestions for countries involved in the nickel trade.

Crisis propagation in a heterogeneous self-reflexive DSGE model.

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp transition between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for which cascading contagion effects are stronger. For the same reason, larger income inequalities tend to reduce, in our model, the probability of global crises. Finally, we are able to reproduce a perhaps counter-intuitive empirical finding: in countries with higher Gini coefficients, the consumption of the lowest income households tends to drop less than that of the highest incomes in crisis times.

Supply crisis propagation in the global cobalt trade network

Cobalt is widely recognized as a strategic mineral especially for current energy and low carbon revolution. Nonetheless, the geographically concentrated supply makes reliable access to cobalt more of a strategic concern. Understanding the systemic impacts of epicenter economies, and how crises propagate if these economies were hit by negative shocks, are thus important for policy makers. To explore this issue, we construct a global cobalt trade network using the data of 2019, upon which a cascading failure model is established. Accordingly, we simulate the avalanche process, and an avalanche network is derived to analyze the structural features of crisis propagation dynamics. Results show that (1) When the ratio r ≥ 8, avalanche sizes of major epicenter economies increase rapidly from 22 to 36; (2) Democratic Republic of Congo, Mainland of China, Germany, and United Kingdom have systemic impacts in the global cobalt trade network; (3) Out-degree, in-strength, out-strength, and betweenness show influences on the dynamics of supply crisis propagation, while in-degree and eigencentrality do not show clear influences on the propagation dynamics; (4) Indirect cascades account for a significant fraction of the avalanche sizes. These findings contribute to more efficient supply management of the strategic raw material for policy makers.

From dotcom to Covid-19: A convergence analysis of Islamic investments

This paper goes beyond the extant comparisons of Islamic and conventional investments by econometrically assessing their convergence dynamics, in a dataset spanning over 1996–2020, covering ten business sectors and five episodes of crisis. We use a dynamic multivariate framework to estimate time-varying correlations, which we submit to beta and sigma-convergence analysis. Subsequently we examine how convergence dynamics affect portfolio risk management and crisis propagation. Our results show strong convergence of Islamic and conventional investments. During crises conventional convergence rates double, but Islamic ones are less affected. Sectoral diversification works best for conventional investments; Islamic ones behave as a single entity. On average we document a 7% risk diversification benefit from Islamic investments, at a 64 basis points cost. Yet, at the epicentre of the Covid-19 financial crisis this rises to 466 basis points and highlights the resilience of these investments in an exogenous event. Islamic investments reduce volatility spillovers in the financial system, but they are progressively less insulated across time. Our findings withstand a battery of robustness checks and are primarily useful to policy makers and investors.

Global Versus Non-Global Banks: A Capital Ratios-Based Analysis

This paper examines the Leverage Ratio and Total Capital Ratio of global versus non-global banks, in both the pre- and the post crisis period. A panel data set of 165 global and non-global financial institutions from 38 countries is used for the period 1999-2015 and a random effects model is employed to examine whether global banks perform better or not compared to their non-global counterparts. This study comes up with two important findings. First, global banks do not exhibit heterogeneous behavior with respect to both ratios neither in the pre- and especially nor in the post-crisis period. Second, the Leverage Ratio is crisis-insensitive, but the Total Capital Ratio is not. Our findings encourage further research on the topic of the contribution of global banks to the financial crisis propagation (at least as far as leverage is concerned).

Global Versus Non-Global Banks: A Capital Ratios-Based Analysis

Abstract This paper examines the Leverage Ratio and Total Capital Ratio of global versus non-global banks in both the pre- and post-crisis periods. A panel data set of 165 global and non-global financial institutions from 38 countries is used for the period 1999-2015 and a random effects model is employed to examine whether global banks perform better or not compared to their non-global counterparts. This study comes up with two important findings. First, global banks do not exhibit heterogeneous behaviour with respect to both ratios neither in the pre- and especially nor in the post-crisis period. Second, the Leverage Ratio is crisis-insensitive, but the Total Capital Ratio is not. Our findings encourage further research on the topic of the contribution of global banks to the financial crisis propagation (at least as far as leverage is concerned).

Crisis Propagation in a Heterogeneous Self-Reflexive DSGE Model

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp crossover between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for which cascading contagion effects are stronger. For the same reason, larger income inequalities tend to reduce, in our model, the probability of global crises. Finally, we are able to reproduce a perhaps counter-intuitive empirical finding: in countries with higher Gini coefficients, the consumption of the lowest income households tends to drop less than that of the highest incomes in crisis times.

From stress testing to systemic stress testing: The importance of macroprudential regulation

Stability of the banking system and macroprudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing different bank assets. The importance of macroprudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system's entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common bank exposures to specific asset classes. We introduce the similarity in asset distribution among the banks as a measure of bank closeness. We link the closeness of asset distributions to the likelihood that banks will experience a similar level and type of distress in a given adverse scenario. We analyze the dynamics of tier 1 capital ratio after stressing the bank network and find that while the system is able to withstand shocks for a wide range of parameters, we identify a critical threshold for both asset risk and bank response to a shock beyond which the system transitions from stable to unstable.

International stock market co-movements following US financial globalization

In this paper, I propose a novel hypothesis to examine whether financial globalization was the economic cause of cross-market co-movement and crisis propagation before and after the global financial crisis; this has been an unsolved puzzle until today. The hypothesis suggests that it is the global outreach of the crisis-originating country, rather than the global outreach of the crisis-infected countries, that caused cross-country co-movement and crisis spread of 2008 crisis. Using data on 59 countries from 2003 to 2013, I present evidence consistent with the blast propagation hypothesis and find that foreign direct investment and foreign portfolio investment were two important channels for cross-market co-movement and global propagation of the crisis before and after crisis. These findings can help governments create international coordination programs to limit crisis propagation in the future.

Diffusion of crisis signals across the world: evidence from subprime crisis of 2008-2009

PurposeThe innovations in fundamentals coupled with noise traders induce co-movement in diverse markets. This co-movement in equity markets which is evidenced higher during the turmoil period influences economic fundamentals of a country dissimilar in nature. The purpose of this paper is to examine whether economic fundamentals or investors’ behavior attributable to disturbances across the world are the rationale behind the crisis transmission, and thereby distinguish fundamental-based contagion from investor-induced contagion.Design/methodology/approachInitially, the study investigates the role of macroeconomic fundamentals and stock returns on crisis occurrence using panel probit estimates. Additionally, ordinary least squares estimates controlling the influence of fundamentals on domestic return capture the discrete country effect measuring the influence of domestic as well as foreign economic fundamentals along with foreign returns on the domestic stock index.FindingsThe empirical results reveal that foreign country stock index returns are having a significant influence on domestic returns besides a prominent role in crisis occurrence. The binary probit model confirmed the influence of both macroeconomic factors and foreign returns in crisis occurrence. The OLS estimates found evidence for investor-induced contagion in the crisis period where the effects of economic fundamentals are small in comparison to foreign market returns that are mainly dominant in pre- and post-crisis period.Research limitations/implicationsThe propagation of crisis from one market to other would enable the policy makers to make clear regulations at right time to control for the crisis in future. The results can help the policy makers as well as investors in reducing the impact of the crisis in future by clearly monitoring the behavior of the factors under study.Originality/valueThe current study addresses the role of macro fundamentals and investors influence in crisis propagation. Adopting subprime crisis of 2008-2009 as a reference point and separating the sample period into pre-crisis, crisis and post-crisis period, the study explains how badly the other 30 markets impacted the crisis that emerged in the USA.

Systemic risk in the US: Interconnectedness as a circuit breaker

We measure systemic risk via the interconnections between the risks facing both financial and real economy firms. SIFIs are ranked by building on the Google PageRank algorithm for finding closest connections. For a panel of over 500 US firms over 2003–2011 we find evidence that intervention programs (such as TARP) act as circuit breakers in crisis propagation. The curve formed by the plot of firm average systemic risk against its variability clearly separates financial firms into three groups: (i) the consistently systemically risky (ii) those displaying the potential to become risky and (iii) those of little concern for macro-prudential regulators.

Systemic Risk and Vulnerabilities of Bank Networks

Stability of the banking system and macro-prudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing differ- ent bank assets. The importance of macro-prudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system’s entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common bank exposures to specific asset classes. We introduce the similarity in asset distribution among the banks as a measure of bank closeness. We link the closeness of asset distributions to the likelihood that banks will experience a similar level and type of distress in a given adverse scenario. We analyze the dynamics of tier 1 capital ratio after stressing the bank network and find that while the system is able to withstand shocks for a wide range of parameters, we identify a critical threshold for asset risk beyond which the system transitions from stable to unstable.