nep-net New Economics Papers
on Network Economics
Issue of 2020‒02‒17
seven papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. An Interacting Agent Model of Economic Crisis By Yuichi Ikeda
  2. Peer Effects in Secondary Education: Evidence from the 2015 Trends in Mathematics and Science Study Based on Homophily By Bernhard C. Dannemann
  3. What difference do networks make to teachers’ knowledge?: Literature review and case descriptions By Nóra Révai
  4. Diffusion in countably infinite networks By Michel Grabisch; Agnieszka Rusinowska; Xavier Venel
  5. Financial linkages and sectoral business cycle synchronisation: Evidence from Europe By Böhm, Hannes; Schaumburg, Julia; Tonzer, Lena
  6. The role of key regions in spatial development By Becker, Raphael Niklas; Henkel, Marcel
  7. The Degree Ratio Ranking Method for Directed Networks By René van den Brink; Agnieszka Rusinowska

  1. By: Yuichi Ikeda
    Abstract: Most national economies are linked by international trade. Consequently, economic globalization forms a massive and complex economic network with strong links, that is, interactions arising from increasing trade. Various interesting collective motions are expected to emerge from strong economic interactions in a global economy under trade liberalization. Among the various economic collective motions, economic crises are our most intriguing problem. In our previous studies, we have revealed that the Kuramoto's coupled limit-cycle oscillator model and the Ising-like spin model on networks are invaluable tools for characterizing the economic crises. In this study, we develop a mathematical theory to describe an interacting agent model that derives the Kuramoto model and the Ising-like spin model by using appropriate approximations. Our interacting agent model suggests phase synchronization and spin ordering during economic crises. We confirm the emergence of the phase synchronization and spin ordering during economic crises by analyzing various economic time series data. We also develop a network reconstruction model based on entropy maximization that considers the sparsity of the network. Here network reconstruction means estimating a network's adjacency matrix from a node's local information. The interbank network is reconstructed using the developed model, and a comparison is made of the reconstructed network with the actual data. We successfully reproduce the interbank network and the known stylized facts. In addition, the exogenous shock acting on an industry community in a supply chain network and financial sector are estimated. Estimation of exogenous shocks acting on communities of in the real economy in the supply chain network provide evidence of the channels of distress propagating from the financial sector to the real economy through the supply chain network.
    Date: 2020–01
  2. By: Bernhard C. Dannemann (University of Oldenburg, Department of Economics)
    Abstract: In the research on peer effects, unweighted mean classroom performance is the predominant measure used in the estimation of education production functions. In this paper, based on the sociological concept of homophily, I introduce social network matrices that correspond to a weighting scheme for peers in the same class at school. Using spatial regression techniques, I confirm the presence of peer effects for the eighth grade population in the USA in the TIMSS 2015 student assessment. For students, the likelihood of cooperation increases conditionally on visible and non-visible characteristics, such as age, gender,migratory background, and attitudes towards scholastic achievement. This grouping behavior is found to affect the spillover effects of student variables, such as gender and language skills. The main findings are robust to various definitions of the social network matrix, as well as to the inclusion of teacher fixed effects.
    Keywords: Human Capital, Cognitive Skills, Peer Effects, Spatial Model, Class Heterogeneity, Education Production Function
    Date: 2020–02
  3. By: Nóra Révai (OECD)
    Abstract: The paper investigates two – often disconnected – policy questions: how can we scale the use of evidence in teaching practice, and how can we generate and scale innovation? Both questions necessitate understanding how teachers and schools connect with each other, and with other organisations and professionals. The paper thus explores the role of networks in scaling evidence and innovation through a review of literature and a number of short case descriptions. Through the lens of networks, the analysis shows how the mobilisation, construction and diffusion of knowledge are of central importance in both policy issues. It suggests that scaling evidence and innovation should be treated as one ecosystem, in which mechanisms that allow effectively blending research and practical knowledge are key. Further, the paper proposes a framework for studying knowledge dynamics in networks to better understand how their context, characteristics and devices can contribute to facilitate these dynamics.
    Date: 2020–02–19
  4. By: Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics, UP1 - Université Panthéon-Sorbonne); Agnieszka Rusinowska (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics, CNRS - Centre National de la Recherche Scientifique); Xavier Venel (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics, UP1 - Université Panthéon-Sorbonne)
    Abstract: We investigate the phenomenon of diffusion in a countably infinite society of individuals interacting with their neighbors. At a given time, each individual is either active (i.e., has the status or opinion 1) or inactive (i.e., has the status or opinion 0). The configuration of the society describes active and inactive individuals. The diffusion mechanism is based on an aggregation function, which leads to a Markov process with an uncountable set of states, requiring the involvement of σ-fields. We focus on two types of aggregation functions - strict, and Boolean. We determine absorbing, transient and irreducible sets under strict aggregation functions. We show that segregation of the society cannot happen and its state evolves towards a mixture of infinitely many active and infinitely many inactive agents. In our analysis, we mainly focus on the network structure. We distinguish networks with a blinker (periodic class of period 2) and those without. ø-irreducibility is obtained at the price of a richness assumption of the network, meaning that it should contain infinitely many complex stars and have enough space for storing local configurations. When considering Boolean aggregation functions, the diffusion process becomes deterministic and the contagion model of Morris (2000) can be seen as a particular case of our framework with aggregation functions. In this case, consensus and non trivial absorbing states as well as cycles can exist.
    Abstract: Nous étudions le phénomène de diffusion dans une société infinie dénombrable d'individus en interaction avec leurs voisins. A un moment donné, chaque individu est soit actif (c'est-à-dire a le statut ou l'opinion 1), soit inactif (c'est-à-dire a le statut ou l'opinion 0). La configuration de la société décrit les individus actifs et inactifs. Le mécanisme de diffusion est basé sur une fonction d'agrégation, qui conduit à un processus de Markov avec un ensemble indénombrable d'états nécessitant l'implication de σ-algèbres. Nous nous concentrons sur deux types de fonctions d'agrégation : stricte et booléenne. Nous déterminons des ensembles absorbants, transitoires et irréductibles dans le cadre de fonctions d'agrégation strictes. Nous montrons que la ségrégation de la société ne peut pas se produire et que son état évolue vers un mélange d'un nombre infini d'agents actifs et d'un nombre infini d'agents inactifs. Dans notre analyse, nous nous concentrons principalement sur la structure du réseau. Nous distinguons les réseaux avec un clignotant (classe périodique de période 2) et ceux sans clignotant. La ø-irréductibilité est obtenue au prix d'une hypothèse de richesse du réseau, ce qui signifie qu'il devrait contenir un nombre infini d'étoiles complexes et disposer de suffisamment d'espace pour stocker les configurations locales. Lorsque l'on considère les fonctions d'agrégation booléennes, le processus de diffusion devient déterministe et le modèle de contagion de Morris (2000) peut être considéré comme un cas particulier de notre cadre avec des fonctions d'agrégation. Dans ce cas, des états absorbants consensuels et non triviaux ainsi que des cycles peuvent exister.
    Keywords: Networks/graphs,Probability: diffusion,Markov processes,Réseaux/graphes,Probabilité : diffusion,Processus de Markov
    Date: 2019–07
  5. By: Böhm, Hannes; Schaumburg, Julia; Tonzer, Lena
    Abstract: We analyse whether financial integration between countries leads to converging or diverging business cycles using a dynamic spatial model. Our model allows for contemporaneous spillovers of shocks to GDP growth between countries that are financially integrated and delivers a scalar measure of the spillover intensity at each point in time. For a financial network of ten European countries from 1996-2017, we find that the spillover effects are positive on average but much larger during periods of financial stress, pointing towards stronger business cycle synchronisation. Dismantling GDP growth into value added growth of ten major industries, we observe that some sectors are strongly affected by positive spillovers (wholesale & retail trade, industrial production), others only to a weaker degree (agriculture, construction, finance), while more nationally influenced industries show no evidence for significant spillover effects (public administration, arts & entertainment, real estate).
    Keywords: financial integration,business cycle synchronisation,industry dynamics,spatial model
    JEL: E32 F44 G10
    Date: 2020
  6. By: Becker, Raphael Niklas; Henkel, Marcel
    Abstract: We discuss the role of key regions in spatial development. Local productivity shocks can affect the entire economy as they expand via tight connections in the domestic production network and in uence the geographical allocation of labor. In particular, we identify the set of key regions with the highest potential to affect aggregate productivity, output, and welfare. Key regions are central locations with strong spatial linkages in the production network but are not too large and congested so they can still attract additional labor in response to positive productivity shocks without local rents and input costs rising too much. Using a spatial equilibrium model and data from German districts, we find that a relatively modest development of productivity in key regions lowered German output and welfare growth by a factor of two from 2010 to 2015.
    Keywords: Regional trade,Input-output linkages,Labour mobility,Spatial economics,Economicgeography,Regional productivity,Sectoral productivity
    JEL: R10 R12 R15 F10 F1 F16 O4 O51
    Date: 2020
  7. By: René van den Brink (Department of Econometrics and Tinbergen Institute - VU University); Agnieszka Rusinowska (CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: One of the most famous ranking methods for digraphs is the ranking by Copeland score. The Copeland score of a node in a digraph is the difference between its outdegree (i.e. its number of outgoing arcs) and its indegree (i.e. its number of ingoing arcs). In the ranking by Copeland score, a node is ranked higher, the higher is its Copeland score. In this paper, we deal with an alternative to rank nodes according to their out– and indegree, namely ranking the nodes according to their degree ratio, i.e. the outdegree divided by the indegree. To avoid dividing by a zero indegree, we implicitly take the out– and indegree of the reflexive digraph. We provide an axiomatization of the ranking by degree ratio using a sibling neutrality axiom, which says that the entrance of a sibling (i.e. a node that is in some sense similar to the original node) does not change the ranking among the original nodes. We also provide a new axiomatization of the ranking by Copeland score using the same axioms except that this method satisfies a different sibling neutrality. Finally, we modify the ranking by degree ratio by not considering the reflexive digraph, but by definition assume nodes with indegree zero to be ranked higher than nodes with a positive indegree. We provide an axiomatization of this ranking by modified degree ratio using yet another sibling neutrality and a maximal property. In this way, we can compare the three ranking methods by their respective sibling neutrality.
    Abstract: L'une des méthodes de classement les plus connues pour les digraphes est le classement par score de Copeland. Le score de Copeland d'un nœud dans un digraphe est la différence entre sont out-degré (c'est-à-dire son nombre d'arcs sortants) et son in-degré (c'est-à-dire son nombre d'arcs entrants). Dans le classement par score de Copeland, un nœud est classé plus haut, plus son score de Copeland est élevé. Dans cet article, nous traitons d'une alternative pour classer les nœuds en fonction de leur degré, à savoir classer les nœuds en fonction de leur ratio de degrés, c'est-à-dire l'out-degré divisé par l'in-degré. Pour éviter de diviser par un zéro, nous prenons implicitement l'in-degré du digraphe réflexif. Nous fournissons une axiomatisation du classement par ratio de degré en utilisant un axiome de neutralité de sibling, qui indique que l'entrée d'un sibling (c'est-à-dire un nœud qui est en quelque sorte similaire au nœud d'origine) ne modifie pas le classement parmi les nœuds d'origine. Nous fournissons également une nouvelle axiomatisation du classement par score de Copeland en utilisant les mêmes axiomes, à la différence que cette méthode satisfait à une neutralité de sibling différente. Enfin, nous modifions le classement par ratio de degrés en ne considérant pas le digraphe réflexif, mais supposons, par définition, que les nœuds d'in-degré zéro sont mieux classés que les nœuds d'in-degré positifs. Nous fournissons une axiomatisation de ce classement par ratio de degré modifié en utilisant encore une autre neutralité de sibling et une propriété maximale. De cette manière, nous pouvons comparer les trois méthodes de classement par leur neutralité de sibling respective.
    Keywords: group decisions and negociations,directed graph,ranking method,degree ratio,Copeland score,décisions et négociations collectives,réseau orienté,méthode de classement,ratio de degré,score de Copeland
    Date: 2019–05

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