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on Network Economics |
| By: | Graef, Inge; Wahyuningtyas, Sih Yuliana; Valcke, Peggy |
| Abstract: | Online media platforms have the characteristics of a particular type of market known as 'multi-sided'. These businesses create value by bringing advertisers and users together. Access to user data is critical to this process. On the basis of economic literature, the features of multi-sided platforms will be discussed. It will be argued that the characteristics of multi-sided platforms increase the likelihood that successful companies become dominant due to the existence of indirect network effects. In these circumstances, dominant platforms may foreclose competition by raising barriers to entry in the large collections of user data. This may give rise to access problems for competitors and new entrants that need access to data gathered by dominant platforms in order to provide competing or complementary services. A comparative legal analysis will be used to assess the standards that apply in the United States (US) and the European Union (EU) for finding liability for refusals to deal under antitrust or competition law. The private antitrust cases that have already occurred regarding access to user data in the US show that the scope of applicability of the essential facilities doctrine is very limited after the judgment of the Supreme Court in Trinko. Although the European Commission and the Court of Justice seem to be willing to accept liability for a refusal to deal more easily than their US counterparts, high legal hurdles still have to be met under the essential facilities doctrine in the EU. Nevertheless, there are scenarios in which liability for refusals to give access to data will likely be accepted in the EU. -- |
| Keywords: | Multi-sided platforms,access regulation,user data,essential facilities,search engines,online social networks,e-commerce platforms |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itse13:98149&r=all |
| By: | Federica Cerina; Zhen Zhu; Alessandro Chessa; Massimo Riccaboni |
| Abstract: | Economic systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the multi-regional input-output (MRIO) tables at the global level. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we study the network properties of the so-called world input-output network (WION) and document its evolution over time. We are able to quantify not only some global network properties such as assortativity, clustering coefficient, and degree and strength distributions, but also its subgraph structure and dynamics by using community detection techniques. Over time, we detect a marked increase in cross-country connectivity of the production system, only temporarily interrupted by the 2008-2009 crisis. Moreover, we find a growing input-output regional community in Europe led by Germany and the rise of China in the global production system. Finally, we use the network-based PageRank centrality and community coreness measure to identify the key industries and economies in the WION and the results are different from the one obtained by the traditional final-demand-weighted backward linkage measure. |
| Date: | 2014–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1407.0225&r=all |
| By: | Dürnecker, Georg; Meyer, Moritz; Vega-Redondo, Fernando |
| Abstract: | In this paper, we propose a new approach to represent a country's outward orientation. Prior work mostly uses indicators of aggregate trade intensity, trade policy or trade restrictiveness. Our approach offers a broader perspective as it measures a country's level of integration not only by its set of direct trade connections with the rest of the world but also through the full architecture of its second, third, and all other higher-order connections. We apply our methodology to a sample of 167 countries spanning the period from 1962 to 2009 and perform a Bayesian modelaveraging analysis on the determinants of growth. We find a prominent positive effect of integration on a country's level of per capita income, while the aforementioned traditional measures of outward orientation display only a secondary, largely insignificant, weight. This, we argue, highlights the network basis of economic growth and adds a novel perspective to the notion of economic openness. We also perform several sensitivity checks and conclude that our baseline findings are extremely robust to different data input and alternative assumptions about the computation of country integration. |
| Keywords: | Globalization , Trade Integration , Economic Growth , Network Analysis , Dynamic Panel Model , Bayesian Model Averaging |
| JEL: | C11 D85 F15 O40 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:mnh:wpaper:35483&r=all |
| By: | Somayeh Koohborfardhaghighi (Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University); Jorn Altmann (Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University) |
| Abstract: | Dynamic processes in complex networks have received much attention. This attention reflects the fact that dynamic processes are the main source of changes in the structural properties of complex networks (e.g., clustering coefficient and average shortest-path length). In this paper, we develop an agent-based model to capture, compare, and explain the structural changes within a growing social network with respect to individuals’ social characteristics (e.g., their activities for expanding social relations beyond their social circles). According to our simulation results, the probability increases that the network’s average shortest-path length is between 3 and 4, if most of the dynamic processes are based on random link formations. That means, in Facebook, the existing average shortest path length of 4.7 can even shrink to smaller values. Another result is that, if the node increase is larger than the link increase when the network is formed, the probability increases that the average shortest-path length is between 4 and 8. |
| Keywords: | Network Properties, Network Growth Models, Small World Theory, Network Science, Simulation, Clustering Coefficient, Complex Networks. |
| JEL: | C02 C6 C15 D85 |
| Date: | 2014–06 |
| URL: | http://d.repec.org/n?u=RePEc:snv:dp2009:2014114&r=all |
| By: | Arun G. Chandrasekhar; Matthew O. Jackson |
| Abstract: | We define a general class of network formation models, Statistical Exponential Random Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as a special case. We provide the first general results on when these models' (including ERGMs) parameters estimated from the observation of a single network are consistent (i.e., become accurate as the number of nodes grows). Next, addressing the problem that standard techniques of estimating ERGMs have been shown to have exponentially slow mixing times for many specifications, we show that by reformulating network formation as a distribution over the space of sufficient statistics instead of the space of networks, the size of the space of estimation can be greatly reduced, making estimation practical and easy. We also develop a related, but distinct, class of models that we call subgraph generation models (SUGMs) that are useful for modeling sparse networks and whose parameter estimates are also directly and easily estimable, consistent, and asymptotically normally distributed. Finally, we show how choice-based (strategic) network formation models can be written as SERGMs and SUGMs, and apply our models and techniques to network data from rural Indian villages. |
| JEL: | C01 C51 D85 Z13 |
| Date: | 2014–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:20276&r=all |