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on Network Economics |
| By: | Christ, Julian P. |
| Abstract: | This paper contributes with empirical findings to European co-inventorship location and geographical coincidence of co-patenting networks. Based on EPO co-patenting information for the reference period 2000-2004, we analyze the spatial con figuration of 44 technology-specific co-inventorship networks. European co-inventorship (co-patenting) activity is spatially linked to 1259 European NUTS3 units (EU25+CH+NO) and their NUTS1 regions by inventor location. We extract 7.135.117 EPO co-patenting linkages from our own relational database that makes use of the OECD RegPAT (2009) files. The matching between International Patent Classification (IPC) subclasses and 44 technology fields is based on the ISI-SPRU-OST-concordance. We con firm the hypothesis that the 44 co-inventorship networks differ in their overall size (nodes, linkages, self-loops) and that they are dominated by similar groupings of regions. The paper offers statistical evidence for the presence of highly localized European co-inventorship networks for all 44 technology fields, as the majority of linkages between NUTS3 units (counties and districts) are within the same NUTS1 regions. Accordingly, our findings helps to understand general presence of positive spatial autocorrelation in regional patent data. Our analysis explicitly accounts for different network centrality measures (betweenness, degree, eigenvector). Spearman rank correlation coefficients for all 44 technology fields confirm that most co-patenting networks co-locate in those regions that are central in several technology-specific co-patenting networks. These findings support the hypothesis that leading European regions are indeed multi- filed network nodes and that most research collaboration is taking place in dense co-patenting networks. -- |
| Keywords: | Co-patenting,co-inventorship,networks,linkages,co-location,RegPAT |
| JEL: | C8 O31 O33 R12 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fziddp:142010&r=net |
| By: | Gai, Prasanna (Australian National University); Kapadia, Sujit (Bank of England) |
| Abstract: | This paper develops an analytical model of contagion in financial networks with arbitrary structure. We explore how the probability and potential impact of contagion is influenced by aggregate and idiosyncratic shocks, changes in network structure, and asset market liquidity. Our findings suggest that financial systems exhibit a robust-yet-fragile tendency: while the probability of contagion may be low, the effects can be extremely widespread when problems occur. And we suggest why the resilience of the system in withstanding fairly large shocks prior to 2007 should not have been taken as a reliable guide to its future robustness. |
| Keywords: | Contagion; network models; systemic risk; liquidity risk; financial crises |
| JEL: | D85 G21 |
| Date: | 2010–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0383&r=net |
| By: | Dev, Pritha |
| Abstract: | This paper introduces the choice of identity characteristics, and, commitments to these characteristics, in a network formation model where links costs are shared. Players want to link to the largest group given that linking costs are decreasing (increasing) in commitments for same (different) identity. We study conditions under which these choices allow for networks with multiple identities. We find that whether the choice of identity itself gives any utility or not, there will be Nash networks featuring multiple identities. Moreover, if the choice of identity directly adds utility, networks with multiple identities will be efficient and survive the dynamic process. |
| Keywords: | Identity; Network Formation; Cost Sharing Links |
| JEL: | Z13 D85 C72 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:21631&r=net |
| By: | Dev, Pritha |
| Abstract: | This paper looks at the role of identity in the fragmentation of networks by incorporating the choice of commitment to identity characteristics, into a noncooperative network formation game. The Nash network will feature divisions based on identity, moreover, it will have layers of such divisions. Using the renement of strictness, I get stars of highly committed players linked together by less committed players. Next, I propose an empirical methodology to deduce which dimensions of identity cause the fragmentation of a given network. I propose a practical algorithm for the estimation and apply this to data from villages in Ghana. |
| Keywords: | Identity; Network formation; Community Structure |
| JEL: | C45 Z13 D85 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:21632&r=net |