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on Network Economics |
| By: | Agnieszka Rusinowska (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I); Rudolf Berghammer (Institut für Informatik - Universitat Kiel); Harrie De Swart (Faculteit Wijsbegeerte-Logica en taalanalyse - Universiteit van Tilburg); Michel Grabisch (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I) |
| Abstract: | We deliver a short overview of di erent centrality measures and influence concepts in social networks, and present the relation-algebraic approach to the concepts of power and influence. First, we briefly discuss four kinds of measures of centrality: the ones based on degree, closeness, betweenness, and the eigenvector-related measures. We consider centrality of a node and of a network. Moreover, we give a classi cation of the centrality measures based on a topology of network flows. Furthermore, we present a certain model of influence in a social network and discuss some applications of relation algebra and RelView to this model. |
| Keywords: | social network ; centrality ; prestige ; influence ; relation algebra ; RelView |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:hal-00633859&r=net |
| By: | Siegried K. Berninghaus (Karlsruhe Institute of Technology (KIT), Institute for Economic Theory and Statistics); Thomas Neumann (Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, Empirical Economics); Bodo Vogt (Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, Empirical Economics) |
| Abstract: | Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008) and in the comment by Brunner, Camerer and Goeree (2009). Every participant played against four neighbors and could choose a different strategy against each of them. The games were played in two network structures: a attice and a circle. We compare our results with the predictions of different theories (Nash equilibrium, quantal response equilibrium, action-sampling equilibrium, payoff-sampling equilibrium, and impulse balance equilibrium) and the experimental results of Selten and Chmura (2008). One result is that the majority of players choose the same strategy against each neighbor. As another result we observe an order of predictive success for the stationary concepts that is different from the order shown by Selten and Chmura. This result supports our view that learning in networks is different from learning in random matching. |
| Keywords: | experimental economics, networks, learning |
| JEL: | C70 C73 C91 D83 D85 |
| Date: | 2011–10–19 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2011-048&r=net |
| By: | Thomas R. Hurd; James P. Gleeson |
| Abstract: | A probabilistic framework is introduced that represents stylized banking networks and aims to predict the size of contagion events. In contrast to previous work on random financial networks, which assumes independent connections between banks, the possibility of disassortative edge probabilities (an above average tendency for small banks to link to large banks) is explicitly incorporated. We give a probabilistic analysis of the default cascade triggered by shocking the network. We find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. A cascade condition is derived that characterizes whether or not an infinitesimal shock to the network can grow to a finite size cascade, in analogy to the basic reproduction number $R_0$ in epidemic modeling. It provides an easily computed measure of the systemic risk inherent in a given banking network topology. An analytic formula is given for the frequency of global cascades, derived from percolation theory on the random network. Two simple examples are used to demonstrate that edge-assortativity can have a strong effect on the level of systemic risk as measured by the cascade condition. Although the analytical methods are derived for infinite networks, large-scale Monte Carlo simulations are presented that demonstrate the applicability of the results to finite-sized networks. Finally, we propose a simple graph theoretic quantity, which we call "graph-assortativity", that seems to best capture systemic risk. |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1110.4312&r=net |
| By: | Michael D. Makowsky (Department of Economics, Towson University); Jared Rubin (Department of Economics, Chapman University) |
| Abstract: | Recent uprisings in the Arab world consist of individuals revealing vastly different preferences than were expressed prior to the uprisings. This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference revelation and falsification, social protest, and institutional change. We find that the amount of social and institutional change is decreasing with authority centralization in simulations with low network range but is increasing with authority centralization in simulations with greater network range. The relationship between institutional change and social shocks is not linear, but rather is characterized by sharp discontinuities. The threshold at which a shock can “tip” a system towards institutional change is decreasing with the geographic reach of citizen social networks. Farther reaching social networks reduce the robustness and resilience of central authorities to change. This helps explain why highly centralized regimes frequently attempt to restrict information flows via the media and Internet. More generally, our results highlight the role that information and communication technology can play in triggering cascades of preference revelation and revolutionary activity in varying institutional regimes. |
| Keywords: | preference falsification, revolution, protest, network technology, agent-based model. |
| JEL: | C63 Z13 D83 D85 D71 H11 |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:tow:wpaper:2011-05&r=net |
| By: | Piotr Berman; Bhaskar DasGupta; Lakshmi Kaligounder; Marek Karpinski |
| Abstract: | Threats on the stability of a financial system may severely affect the functioning of the entire economy, and thus considerable emphasis is placed on the analyzing the cause and effect of such threats. The financial crisis in the current and past decade has shown that one important cause of instability in global markets is the so-called financial contagion, namely the spreading of instabilities or failures of individual components of the network to other, perhaps healthier, components. This leads to a natural question of whether the regulatory authorities could have predicted and perhaps mitigated the current economic crisis by effective computations of some stability measure of the banking networks. Motivated by such observations, we consider the problem of defining and evaluating stabilities of both homogeneous and heterogeneous banking networks against propagation of synchronous idiosyncratic shocks given to a subset of banks. We formalize the homogeneous banking network model of Nier et al. and its corresponding heterogeneous version, formalize the synchronous shock propagation procedures outlined in that paper, define two appropriate stability measures and investigate the computational complexities of evaluating these measures for various network topologies and parameters of interest. Our results and proofs also shed some light on the properties of topologies and parameters of the network that may lead to higher or lower stabilities. |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1110.3546&r=net |
| By: | Flaminia Musella |
| Abstract: | Bayesian networks are graphical models that represent the joint distributionof a set of variables using directed acyclic graphs. When the dependence structure is unknown (or partially known) the network can be learnt from data. In this paper, we propose a constraint-based method to perform Bayesian networks structural learning in presence of ordinal variables. The new procedure, called OPC, represents a variation of the PC algorithm. A nonparametric test, appropriate for ordinal variables, has been used. It will be shown that, in some situation, the OPC algorithm is a solution more efficient than the PC algorithm. |
| Keywords: | Structural Learning, Monotone Association, Nonparametric Methods. |
| JEL: | C14 C51 |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:rtr:wpaper:139&r=net |
| By: | Massimo Riccaboni; Alessandro Rossi; Stefano Schiavo |
| Abstract: | Considerable efforts have been made in the recent years to produce detailed topolo- gies of the Internet. While Internet topology data have brought to the attention of a wide and somehow diverse audience of scholars they have been so far over- looked by economic analyses. In this paper we suggest that such data could be effectively treated as a proxy to characterize the size of the “digital economy” ac- tivities at national country level: we therefore analyze the topological structure of the network of trade in digital services (trade in bits) and compare it with that of the more traditional flow of manufactured goods across countries. To perform a meaningful comparison across networks with different characteristics we define a common null model for the number of connections among each country-pair, based on the hypergeometric distribution. Original data are thus filtered using different thresholds so that we focus our attention on the strongest links only, i.e., on links the represent a significant departure from the stochastic benchmark. We find that trade in bits displays a more sparse and less hierarchical network structure, which is more similar to trade in high-skill manufactured goods than total trade. Last, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services. |
| Keywords: | Internet, hypergeometric, international trade, network analysis, distance |
| JEL: | F14 L86 O33 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:trn:utwpde:1108&r=net |
| By: | Luca Antonio Ricci (Research Department, Development Macroeconomics Division - International Monetary Fund); Federico Trionfetti (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales (EHESS) - CNRS : UMR6579) |
| Abstract: | This paper uses a newly assembled multi-country multi-industry fi rm-level dataset to test the effect of productivity and networking on the export probability of firms. Results are in line with the new-new trade theory and with the literature on the information value of networks. Firms are more likely to export if they are more productive, larger, and if they bene fit from foreign networks (ownership and financial linkages), domestic networks (chamber of commerce, links to regulation), and communication networks (E-mail, internet). Firms bear a lower probability of exporting if they have state or labor networks. Overall, firms with better network connections by one standard deviation enjoy a 15% higher probability of exporting. |
| Keywords: | new-new trade theory; export probability |
| Date: | 2011–10–17 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00633033&r=net |
| By: | Estelle Cantillon; Pai-Ling Yin |
| Abstract: | This paper describes open research questions related to the competition and market structure of financial exchanges and argues that only a combination of industrial organization and finance can satisfactorily attack these questions. Two examples are discussed to illustrate how the combination of these two approaches can significantly enrich the analysis: the “network externality puzzle”, which refers to the question of why trading for the same security is often split across trading venues, and the impact of the multi-sided character of financial exchanges on pricing and profitability. |
| Keywords: | network effects; two-sided market; tipping; competition; market structure; market microstructure |
| JEL: | G29 L13 L40 L15 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:ulb:ulbeco:2013/99386&r=net |
| By: | Lindelauf, R. (Universiteit van Tilburg) |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ner:tilbur:urn:nbn:nl:ui:12-4960702&r=net |
| By: | Lalanne, Marie; Seabright, Paul |
| Abstract: | Using an original dataset describing the career history of some 16,000 senior executives and members of the non-executive board of US, UK, French and German companies, we investigate gender differences in the use of social networks and their impact on earnings. There is a large gender wage gap: women (who make up 8.8% of our sample) earned average salaries of $168,000 in 2008, only 70% of the average $241,000 earned by men. This is not due to differences in age, experience or education levels. Women are more likely than men to be non-executives, whose salaries are lower; nevertheless, a substantial gender gap still exists among executives. We construct measures of the number of currently influential people each individual has encountered previously in his or her career. We find that executive men's salaries are an increasing function of the number of such individuals they have encountered in the past while women's are not. Controlling for this discrepancy, there is no longer a significant gender gap among executives. These findings are robust to the use of different years, to the use of salaried versus non-salaried remuneration, and to the use of panel estimation to control rigorously for unobserved individual heterogeneity. In contrast to executives, the salaries of non-executive board members do not display a significant gender wage gap, nor any gender difference in the effectiveness with which men and women leverage their links into salaries. This suggests that adoption of gender quotas for board membership, as has been enacted or proposed recently in several European countries, is unlikely to reduce the gender gap in earnings so long as such quotas do not distinguish between executive and non-executive board members. |
| Keywords: | executive compensation; gender wage gap; social networks |
| JEL: | A14 J16 J31 J33 |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:8623&r=net |