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Extreme natural hazards represent, together with crises and wars, the most disruptive phenomena for economic activity. Their economic impact has been shown to be remarkable, long-lasting, and growing over time, though the exact mechanisms at stake are challenging to isolate and quantify. As these trends are likely to endure as global warming becomes more severe, the need for appropriate modeling of both short and long-run impacts of natural disasters is becoming increasingly pressing. Building on a mounting number of empirical works, we here provide a critical review of the modeling approaches traditionally employed in the related literature. Although with notable exceptions, conventional methods are generally based on Input-Output or Computational General Equilibrium models. These approaches, while analytically sound, are structurally ill-suited to capture certain aspects of natural hazard consequences. Systemic responses to such extreme events are typically characterized by complex interactions among heterogeneous agents, adaptive behavior, and out-of-equilibrium dynamics. We here argue that complexity methods can represent a valid alternative to bridge this policy-relevant gap. In particular, Agent-Based Models offer a powerful toolkit to account for non-linear geographical and temporal interdependencies, the presence of hysteresis and path dependency, the impact of technology changes, and can be fruitfully employed as laboratories for adaptation and mitigation policies.

Complex bipartite systems are studied in Biology, Physics, Economics, and Social Sciences, and they can suitably be described as bipartite networks. The heterogeneity of elements in those systems makes it very difficult to perform a statistical analysis of similarity starting from empirical data. Though binary Pearson's correlation coefficient has proved effective to investigate the similarity structure of some real-world bipartite networks, here we show that both the usual sample covariance and correlation coefficient are affected by a bias, which is due to the aforementioned heterogeneity. Such a bias affects real bipartite systems, and, for example, we report its effects on empirical data from two bipartite systems. Therefore, we introduce weighted estimators of covariance and correlation in bipartite complex systems with a double layer of heterogeneity. The advantage provided by the weighted estimators is that they are unbiased and, therefore, better suited to investigate the similarity structure of bipartite systems with a double layer of heterogeneity. We apply the introduced estimators to two bipartite systems, one social and the other biological. Such an analysis shows that weighted estimators better reveal emergent properties of these systems than unweighted ones.

Spatial networks are networks where nodes are located in a space equipped with a metric. Typically, the space is two-dimensional and until recently and traditionally, the metric that was usually considered was the Euclidean distance. In spatial networks, the cost of a link depends on the edge length, i.e. the distance between the nodes that define the edge. Hypothesizing that there is pressure to reduce the length of the edges of a network requires a null model, e.g. a random layout of the vertices of the network. Here we investigate the properties of the distribution of the sum of edge lengths in random linear arrangement of vertices, that has many applications in different fields. A random linear arrangement consists of an ordering of the elements of the nodes of a network being all possible orderings equally likely. The distance between two vertices is one plus the number of intermediate vertices in the ordering. Compact formulae for the 1st and 2nd moments about zero as well as the variance of the sum of edge lengths are obtained for arbitrary graphs and trees. We also analyze the evolution of that variance in Erdos–Rényi graphs and its scaling in uniformly random trees. Various developments and applications for future research are suggested.

Governance of Local Productive Arrangements (LPAs), territorial networks and proximities in the Brazilian Amazon: The Case of the Goiaba LPA in Northeastern Pará : Proximities’ influence on the construction of socio-economic networks provokes many debates in the literature. The present contribution aims to study the functioning of coordination between actors in support systems for agricultural sectors and to highlight the impact of a public policy of territorial development on these devices, with the help of an approach in terms of networks and proximities. For that, we analyze the Local Productive Arrangements (LPAs) of an agricultural sector in the Brazilian Amazon, supported by a territorial governance mechanism. The mobilized analysis framework allows us to study and compare LPAs, to characterize the types of networks according to the types of proximities and to highlight the importance of the territorial governance mechanism for strengthening and sustaining LPAs.; L’influence des proximités sur la construction des réseaux socio-économiques suscite de nombreux débats dans la littérature. La présente contribution vise à étudier le fonctionnement des coordinations entre acteurs dans des dispositifs d’appui aux filières agricoles et à mettre en évidence l’impact d’une politique publique de développement territorial sur ces dispositifs, à l’aide d’une approche en termes de réseaux et de proximités. Dans cet esprit, à partir de données relationnelles collectée entre avril 2012 et mars 2013, nous analysons un Arrangement Productif Local (APL) d’une filière agricole en Amazonie brésilienne, soutenus par un dispositif de gouvernance territoriale. Le cadre d’analyse mobilisé nous permet d’étudier et de comparer des APL, de caractériser les types de réseaux selon les types de proximités et de mettre en avant l’importance du dispositif de gouvernance territoriale pour le renforcement et la pérennisation des APL.; A influência das proximidades na construção das redes socioeconômicas suscita inúmeros debates na literatura. A presente contribuição visa estudar o funcionamento das coordenações entre atores em dispositivos de apoio às cadeias produtivas agrícolas e evidenciar o impacto de uma política pública de desenvolvimento territorial sobre esses dispositivos, com a ajuda de uma abordagem em termos de redes e de proximidades. Com esse intuito, a partir de dados relacionais primários coletados entre abril de 2012 e março de 2013, analisamos um Arranjo Produtivo Local (APL) de uma cadeia produtiva agrícola na Amazônia brasileira, apoiados por um dispositivo de governança territorial. O quadro de análise mobilizado, nos permite estudar e comparar os APLs, caracterizar os tipos de redes segundo os tipos de proximidades e destacar a importância do dispositivo de governança territorial para o fortalecimento e a perenização dos APLs.

International audience; Proximities' influence on the construction of socio-economic networks provokes many debates in the literature. The present contribution aims to study the functioning of coordination between actors in support systems for agricultural sectors and to highlight the impact of a public policy of territorial development on these devices, with the help of an approach in terms of networks and proximities. For that, we analyze the Local Productive Arrangements (LPAs) of an agricultural sector in the Brazilian Amazon, supported by a territorial governance mechanism. The mobilized analysis framework allows us to study and compare LPAs, to characterize the types of networks according to the types of proximities and to highlight the importance of the territorial governance mechanism for strengthening and sustaining LPAs.

L’influence des proximités sur la construction des réseaux socio-économiques suscite de nombreux débats dans la littérature. La présente contribution vise à étudier le fonctionnement des coordinations entre acteurs dans des dispositifs d’appui aux filières agricoles et à mettre en évidence l’impact d’une politique publique de développement territorial sur ces dispositifs, à l’aide d’une approche en termes de réseaux et de proximités. Dans cet esprit, à partir de données relationnelles collectée entre avril 2012 et mars 2013, nous analysons un Arrangement Productif Local (APL) d’une filière agricole en Amazonie brésilienne, soutenus par un dispositif de gouvernance territoriale. Le cadre d’analyse mobilisé nous permet d’étudier et de comparer des APL, de caractériser les types de réseaux selon les types de proximités et de mettre en avant l’importance du dispositif de gouvernance territoriale pour le renforcement et la pérennisation des APL., A influência das proximidades na construção das redes socioeconômicas suscita inúmeros debates na literatura. A presente contribuição visa estudar o funcionamento das coordenações entre atores em dispositivos de apoio às cadeias produtivas agrícolas e evidenciar o impacto de uma política pública de desenvolvimento territorial sobre esses dispositivos, com a ajuda de uma abordagem em termos de redes e de proximidades. Com esse intuito, a partir de dados relacionais primários coletados entre abril de 2012 e março de 2013, analisamos um Arranjo Produtivo Local (APL) de uma cadeia produtiva agrícola na Amazônia brasileira, apoiados por um dispositivo de governança territorial. O quadro de análise mobilizado, nos permite estudar e comparar os APLs, caracterizar os tipos de redes segundo os tipos de proximidades e destacar a importância do dispositivo de governança territorial para o fortalecimento e a perenização dos APLs., Governance of Local Productive Arrangements (LPAs), territorial networks and proximities in the Brazilian Amazon: The Case of the Goiaba LPA in Northeastern Pará : Proximities’ influence on the construction of socio-economic networks provokes many debates in the literature. The present contribution aims to study the functioning of coordination between actors in support systems for agricultural sectors and to highlight the impact of a public policy of territorial development on these devices, with the help of an approach in terms of networks and proximities. For that, we analyze the Local Productive Arrangements (LPAs) of an agricultural sector in the Brazilian Amazon, supported by a territorial governance mechanism. The mobilized analysis framework allows us to study and compare LPAs, to characterize the types of networks according to the types of proximities and to highlight the importance of the territorial governance mechanism for strengthening and sustaining LPAs.

There exists a wide gap between the predictions of strategic models of network formation and empirical observations of the characteristics of socio-economic networks. Empirical observations underline a complex structure characterized by fat-tailed degree distribution, short average distance, large clustering coefficient and positive assortativity. Game theoretic models offer a detailed representation of individuals’ incentives but they predict the emergence of much simpler structures than these observed empirically. Random network formation processes, such as preferential attachment, provide a much better fit to empirical observations but generally lack micro-foundations. In order to bridge this gap, we propose to model network formation as extensive games and investigate under which conditions equilibria of these games are observationally equivalent with random network formation process. In particular, we introduce a class of games in which players compete with their predecessors and their successors for the utility induced by the links they form with other nodes in the network. Such sequential competition games can represent a number of strategic economic interactions such as oligopolistic competition in supply networks or diffusion of influence in opinion networks. We show that the focal equilibrium that emerges in this setting is one where players use probability distributions with full support and target the whole network with probabilities inversely proportional, to the utility of each node. Notably, when the utility of a node is inversely proportional to its degree, equilibrium play induces a preferential attachment process.

Climate change is one of the most daunting challenges human kind has ever faced. In the paper, we provide a survey of the micro and macro economics of climate change from a complexity science perspective and we discuss the challenges ahead for this line of research. We identify four areas of the literature where complex system models have already produced valuable insights: (i) coalition formation and climate negotiations, (ii) macroeconomic impacts of climate-related events, (iii) energy markets and (iv) diffusion of climatefriendly technologies. On each of these issues, accounting for heterogeneity, interactions and disequilibrium dynamics provides a complementary and novel perspective to the one of standard equilibrium models. Furthermore, it highlights the potential economic benefits of mitigation and adaptation policies and the risk of under-estimating systemic climate change-related risks.

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals' preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences., This work was partially supported by the EU through FET-Proactive Project DOLFINS (contract no. 640772) and FET-Open Project IBSEN (contract no. 662725), and by grant FIS2015-64349-P (MINECO, Spain / FEDER, UE).

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks' evolution: the individual's propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

We provide a survey of the micro and macro economics of climate change from a complexity science perspective and we discuss the challenges ahead for this line of research. We identify four areas of the literature where complex system models have already produced valuable insights: (i) coalition formation and climate negotiations, (ii) macroeconomic impacts of climate-related events, (iii) energy markets and (iv) diffusion of climate-friendly technologies. On each of these issues, accounting for heterogeneity, interactions and disequilibrium dynamics provides a complementary and novel perspective to the one of standard equilibrium models. Furthermore, it highlights the potential economic benefits of mitigation and adaptation policies and the risk of under-estimating systemic climate change-related risks.

In this paper, we show that a comprehensive analysis of temporal network evolution requires to consider measures of non-structural changes, in addition to classical topological indicators. We employ a recently proposed measure of non-structural dynamics, together with other structural indicators, to analyze the time evolution of three subnetworks, extracted from the Italian corporate board network. Consistently with recent literature, we show that, to different extent, both structural and non-structural changes are present and must be accounted for, in order to get a satisfactory description of their temporal evolution.

In the given research we analyse how an agent can move towards leadership in a socio-economic network. For the node’s (i.e., agent’s) importance measure we use the Shapley value (SV) concept from the area of cooperative games. We consider SV as the node’s centrality that corresponds to the significance of the agent within the socio-economic network. Using the polynomial algorithm developed by Aadithya, Ravindran, Michalak, & Jennings (2010) to compute SVs we analyze the way of creating new linkages to increase an agent’s significance (i.e., importance) in networks.

In the given research we analyse how an agent can move towards leadership in a socio-economic network. For the node’s (i.e., agent’s) importance measure we use the Shapley value (SV) concept from the area of cooperative games. We consider SV as the node’s centrality that corresponds to the significance of the agent within the socio-economic network. Using the polynomial algorithm developed by Aadithya, Ravindran, Michalak, & Jennings (2010) to compute SVs we analyze the way of creating new linkages to increase an agent’s significance (i.e., importance) in networks.

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new universal pattern for how the reactive dynamics of individuals is distributed across the set of each agent's contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this universal behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one's environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution., Comment: 15 pages, 7 figures

Recently, the study of evolutionary games on networks has attracted great interest, focused mainly on the problem of the emergence of cooperation. A well studied framework for this problem is the Prisoner's Dilemma game on fixed, evolving or growing networks. In this paper we present a complete picture of the behavior of another important social dilemma, the Stag Hunt game, under an evolutionary preferential attachment model, in which the network grows according to the dynamical states of the elements of the system. We observe the emergence of a scale-free and hierarchical organization of the strategies according to connectivity classes as a by-product of the diffusion of cooperation in the network. Depending on the parametrization of the game dynamics, we find a smooth transition from cooperation to defection and a polymorphic state with simultaneous presence of cooperator and defector hubs, which is very unusual in coordination games. AS was supported in part by grants MOSAICO and Complexity-NET RESINEE (Ministerio de Ciencia e Innovación, Spain) and MODELICO-CM (Comunidad de Madrid, Spain). YM is supported by the Spanish MICINN through projects FIS2008-01240 and FIS2009-13364-C02-01 and by the Government of Arag´on (DGA) through a grant to the FENOL group. Publicado

The aviation sector is profitable, but sensitive to economic fluctuations, geopolitical constraints and governmental regulations. As for other means of transportation, the relation between origin and destination results in a complex map of routes, which can be complemented by information associated to the routes themselves, for instance, frequency, traffic load or distance. The theory of networks provides a natural framework to investigate dynamics on the resulting structure. Here, we investigate the structure and evolution of the Brazilian Airport Network (BAN) for several quantities: routes, connections, passengers and cargo. Some structural features are in accordance with previous results of other airport networks. The analysis of the evolution of the BAN shows that its structure is dynamic, with changes in the relative relevance of some airports and routes. The results indicate that the connections converge to specific routes. The network shrinks at the route level but grows in number of passengers and amount of cargo, which more than doubled during the period studied., 10 pages, 8 figures, 2 tables. The analysis moved from an airport-based network to a city-based network. The conclusions were unaffected

Tourism destination networks are amongst the most complex dynamical systems, involving a myriad of human-made and natural resources. In this work we report a complex network-based systematic analysis of the Elba (Italy) tourism destination network, including the characterization of its structure in terms of several traditional measurements, the investigation of its modularity, as well as its comprehensive study in terms of the recently reported superedges approach. In particular, structural (the number of paths of distinct lengths between pairs of nodes, as well as the number of reachable companies) and dynamical features (transition probabilities and the inward/outward activations and accessibilities) are measured and analyzed, leading to a series of important findings related to the interactions between tourism companies. Among the several reported results, it is shown that the type and size of the companies influence strongly their respective activations and accessibilities, while their geographical position does not seem to matter. It is also shown that the Elba tourism network is largely fragmented and heterogeneous, so that it could benefit from increased integration.

We introduce an analytical statistical method to characterize the communities detected in heterogeneous complex systems. By posing a suitable null hypothesis, our method makes use of the hypergeometric distribution to assess the probability that a given property is over-expressed in the elements of a community with respect to all the elements of the investigated set. We apply our method to two specific complex networks, namely a network of world movies and a network of physics preprints. The characterization of the elements and of the communities is done in terms of languages and countries for the movie network and of journals and subject categories for papers. We find that our method is able to characterize clearly the identified communities. Moreover our method works well both for large and for small communities., 8 pages, 1 figure and 2 tables