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on Network Economics |
| By: | Byung-Cheol Kim (School of Economics, Georgia Institute of Technology); Jeongsik "Jay" Lee (Scheller College of Business, Georgia Institute of Business); Hyunwoo Park (School of Industrial and System Engineering) |
| Abstract: | We empirically investigate the platform competition in the online daily deals promotion market that is characterized by intense rivalry between two leading promotion sites, Groupon and LivingSocial, that broker between merchants and consumers. We find that deals offered through Groupon, the incumbent, sell more and generate higher revenues than those offered by LivingSocial, the entrant. We show that the greater network size in the consumer side entirely explains the incumbent's lead in the merchant side performance, indicating the existence of cross-side network effects at the aggregated market level. However, this performance advantage is dampened by the entrant's competitive chasing at local markets through offers of greater discounts and lower prices. Moreover, the incumbent advantage quickly attenuates as the merchants repeat promotions over time. These countering forces appear to prevent this market from achieving a tipping equilibrium. Our findings thus help explain why different market structures arise in two-sided markets with network externalities. |
| Keywords: | two-sided market, platform competition, cross-side network effects, online daily deals, reputation effect |
| JEL: | D40 L10 M20 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:1204&r=net |
| By: | Semyon Malamud (Swiss Finance Institute, EPF Lausanne); Marzena Rostek (Department of Economics, University of Wisconsin-Madison) |
| Abstract: | We develop a model of decentralized markets in which trading environment is determined by a general network structure. We study how the equilibrium allocation and liquidity depend on the network topology and how an agent’s risk exposure depends on other agents’ exposures. Agents hold several, position specific “local market portfolios,” that also determine the “local market clearing prices”. The impact of one trader on another decays exponentially in the distance in the network, at an explicitly given equilibrium rate. Decentralized trading may increase welfare. Liquidity may be higher for “less connected” networks. |
| Keywords: | Asset pricing, Decentralized Market, Trading Network, Over-the-counter, Welfare |
| JEL: | D53 G11 G12 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:1218&r=net |
| By: | Özge Öner; Viroj Jienwatcharamongkhol |
| Abstract: | Previous studies in regional science show that the size of a city has a scaling effect on many variables such as population, economic growth and number of creative employees. This type of relation can also be observed between the size of the networks that emerge between individuals and the cities that are hosting them. These networks are known to emerge within the same industry, as well as across different industries. Alternatively, we propose that the construct of these networks is dependent on the occupations and/or the skills of individuals. However, the city must have an optimal size in relation to the size of a network, taking various spatial and industry specific characteristics into account. Following the decreasing-returns-to-scale argument, we expect a sigmoid curve for different degrees of network-city size relationship. Hence this paper aims to determine the optimal size of a city where an individual would benefit most from a network he/she is a member of. Using geo-coded Swedish micro-data, the paper contributes to the existing literature by analyzing the research question from a micro departure point to draw a macro level conclusion. Keywords: network, city size, micro-data JEL: R12, D85 |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p963&r=net |
| By: | Balazs Lengyel; Akos Jakobi |
| Abstract: | This initial paper of our interest on geography of online social network is based on a literature in which geographers reformulated major concepts and hypotheses in the ‘90ies due to revolutionary development of internet (Cairncross, 1997). Cyberspace quickly became central issue in understanding human behaviour in the virtual world and cyber world has been always claimed to strongly twitted with physical world (Hayes, 1997). Parallel shift in economic geography research moved the focus of interest from distance to proximity, which is essential in our understanding for new knowledge creation and innovation in cities while the importance of distance is decreasing (Boschma, 2005). Economic geographers also claim that innovation and knowledge creation remained local in the era of internet because the need of face-to-face interactions (Feldman, 2002); internet-based communication seems to stimulate local offline communication (Storper and Venables, 2004). Social network sites are major fields of online communication and “enable users to articulate and make visible their social networks” (boyd and Ellison, 2007). Online social network (OSN) are large-scale networks and claimed to be supplemental forms of communication between people who have known each other primarily in real life (Ellison et al, 2006, 2007). We believe that studying these networks will give new insights to local learning and social capital issues by providing excellent data on online local learning and also proxies of offline local learning. According to recent findings on large scale OSNs (Facebook and Twitter), geographical location of users and their friends turns to be a determining factor for the structure of the network (Backstrom et al, 2011, Takhteyev et al, 2012, Ugander et al, 2011). However, more traditional geographical aspects are also needed to analyse spatial distribution of OSN activity. Our research questions address both the effects of distance and settlement size on population shares involved in online communities such as online social networks. Preliminary findings on iWiW, a leading online social network in Hungary with more than 4 million users, suggest that share of users is higher in bigger settlements and positively associated with geographical proximity of Budapest. On the other hand, the average number of friendship ties is independent from settlement size and is higher in peripheral regions of the country. In sum, settlement size and distance may play decisive role in shaping geographies of OSN. Keywords: online social network, geography, settlements, size effect, distance JEL codes: L86, R10, O18, O33 |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p1032&r=net |
| By: | Patacchini, Eleonora; Rainone, Edoardo; Zenou, Yves |
| Abstract: | The aim of this paper is to investigate and understand the effect of high-school friends on years of schooling. We develop a simple network model where students first choose their friends and then decide how much effort they put in education. The empirical salience of the model is tested using the four waves of the AddHealth data by looking at the impact of school peers nominated in the first two waves in 1994-1995 and in 1995-1996 on the educational outcome of teenagers reported in the fourth wave in 2007-2008 (when adult). We find that there are strong and persistent peer effects in education but peers tend to be influential only when they are strong ties (friends in both wave I and II) and not when they are weak ties (friend in one wave only). We also find that this is not true in the short run since both weak and strong ties tend to influence current grades. |
| Keywords: | education; long-term effects; peer effects; Social networks |
| JEL: | C21 I21 Z13 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:9149&r=net |
| By: | Marcus Berliant; Hiroki Watanabe |
| Abstract: | Zipf's law is one of the best-known empirical regularities of the city-size distribution. There is extensive research on the subject, where each city is treated symmetrically in terms of the cost of transactions with other cities. Recent developments in network theory facilitate the examination of an asymmetric transport network. Under the scale-free transport network framework, the chance of observing extremes becomes higher than the Gaussian distribution predicts and therefore it explains the emergence of large clusters. City-size distributions share the same pattern. This paper proposes a way to incorporate network structure into urban economic models and explains the city-size distribution as a result of transport cost between cities. Keywords: Zipf's law, city-size distribution, scale-free network JEL classification: R12, R40 |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p601&r=net |
| By: | Iris Wanzenböck; Thomas Scherngell; Rafael Lata |
| Abstract: | In the recent past, regional, national and supranational Science, Innovation and Technology (STI) policies have emphasized supporting interactions and networks between organisations of the innovation system. The policy instrument of the EU in this context are the European Framework Programmes (FPs) that support pre-competitive R&D projects, creating a pan-European network of actors performing joint R&D. In this study, we focus on the embeddedness of European regions in this network. By embeddedness we refer to the notion of centrality in the sense of the Social Network Analysis (SNA) literature. In network theory, vertices that have a more prominent and central network position will more likely benefit from network advantages than actors that have a more distant, peripheral position in the network. A higher network embeddedness of a region, i.e. of organisations located in that region, may increase information and knowledge access in the network, and, thus, create a competitive advantage when it comes to the formation of new collaborations and alliances. The objective of the study is to explain why some regions are able to obtain a better network embeddedness in the European network of R&D cooperation than other regions. For this reason we aim to identify determinants that influence a region´s embededdness, involving region-internal factors, such as regional characteristics on their innovation capability, their economic structure and technological specialisation, as well as region-external factors considering the influence of these variables in the neighbourhood of a specific region, referred to as spatial spillovers. To address this question we employ spatial panel modelling techniques, explicitly taking into account the time dimension in our data and the influence of spillovers by specifying a panel spatial durbin error model (SDEM). The dependent variable is the regions’ centrality in the FP network for the years 1998-2006, using a sample of 241 NUTS-regions of the EU-25 member states. We aggregate individual FP cooperations to the regional level leading to a network where the nodes are represented by regions and the edges by cross-region collaboration intensities. Using these matrices we calculate a region’s centrality relying on two different centrality concepts, namely betweeness- and eigenvector centrality. The independent variables involve regional characteristics related to a region’s knowledge production capacity and a region’s general economic structure. The results will significantly enrich our understanding of the relationship between a regions network embededdness and its internal and external characteristics. JEL Classification: C02, C49, L14, O39, O52 Keywords: R&D cooperation, European Framework Program, large-scale networks, network embeddedness, panel spatial Durbin model |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p451&r=net |
| By: | Cohen-Cole, Ethan; Liu, Xiaodong; Zenou, Yves |
| Abstract: | In this paper, we investigate the impact of peers on own outcomes where all agents embedded in a network choose more than one activity. We develop a simple network model that illustrates these issues. We differentiate between the ‘seemingly unrelated’ simultaneous equations model where people are influenced only by others within the same activity, the ‘triangular’ simultaneous equations model, where there is some asymmetry in the peers’ cross effects, and the ‘square’ simultaneous equations model, where all possible cross-choice effects are taken into account. We develop the conditions under which each model is identified, showing that the general ‘square’ simultaneous equations model with both simultaneity effect and cross-choice peer effect cannot be identified without any exclusion restrictions. We then study the impact of peer effects on education and screen activities and show that the estimated within- and cross-choice peer effects both have non-trivial impacts on adolescent behavior. We find, in particular, that, keeping peers’ grades and screen activities fixed, watching more TV could be beneficial to a student’s grade. |
| Keywords: | identification; peer effects; Social networks |
| JEL: | C21 C3 I21 Z13 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:9159&r=net |
| By: | Rafael Lata; Thomas Scherngell; Thomas Brenner |
| Abstract: | The focus of this study is on integration processes in European R&D by analyzing the spatio-temporal dimension of three different R&D collaboration networks across Europe. These networks cover different types of knowledge creation, namely co-patent networks, project based R&D networks within the EU Framework Programmes (FPs) and co-publication networks. Integration in European R&D – one of the main pillars of the EU Science Technology and Innovation (STI) policy – refers to the harmonization of fragmented national research systems across Europe and to the free movement of knowledge and researchers. The objective of this study is to describe and compare spatio-temporal patterns of the observed networks at a regional level, and to estimate the evolution of separation effects over the time period 1999-2006 that influence the probability of cross-region collaborations in the distinct networks under consideration. By separation effects we refer to geographical, technological, institutional and cultural barriers between the regions under consideration. The study adopts a spatial interaction modeling perspective, econometrically specifying a panel generalized linear model relationship taking into account spatial autocorrelation among flows by using Eigenfunction spatial filtering methods to address the research questions. The European coverage is achieved by using 255 NUTS-2 regions of the 25 pre-2007 EU member-states, as well as Norway and Switzerland. For the construction of the three dependent variables that describe collaboration intensities between all region pairs in the three different types of R&D networks, we use data from the OECD Regpat database to capture cross-region co-patent networks, the AIT EUPRO database to capture cross-region project based R&D networks in the FPs, and the Scopus database to capture cross-region co-publication networks. The independent variables consist of one origin measure, one destination measure and seven separation measures. The separation variables focus on barriers that may hamper cross-region collaboration probability, accounting for spatial effects, cultural and institutional hurdles and economic or technological barriers. The results will provide novel and valuable empirical insight into ongoing integration processes in different types of R&D, reflecting knowledge diffusion in form of R&D collaborations from a longitudinal and comparative perspective. By this, the study will produce important implications regarding past success or failure of European R&D integration policies, and, thus, for future STI policy design. JEL Classification: C23, O38, L14, R15 Keywords: R&D Networks, European Framework Program, Patents, Publications, Large-Scale Networks, Spatial Interaction Modelling, Panel Econometrics, Eigenvector Spatial Filtering, Social Network Analysis |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p836&r=net |
| By: | Timo Mitze; Falk Strotebeck |
| Abstract: | We analyse the determinants of network formation in German’s biotechnology sector combining elements from social network analysis (SNA) and a regression framework for count data. For the latter we adopt a regional innovation system perspective, we estimate the number of total and interregional R&D collaborations of local biotech actors in the year 2005 as a function of region’s innovation and economic context as well as a set of policy related variables. The inclusion of policy instruments in the regression approach allows us to answer the question to what extent R&D-based cluster policies such as the well-known BioRegio contest (BRC) shape the formation of the German biotech network. We use the region’s degree centrality, a standard measure in SNA, as outcome variable. Our results show that policy indicators such as the volume of public funding for collaborative R&D are positively correlated with the region’s total and interregional number of R&D cooperations. However, besides this direct funding effect no further advantages such as image effects etc. are found. Regarding the role of factors defining the regional innovation system, we observe that the number of biotech patent applications, the share of regional hightech start-ups and the population density are positively linked to the region’s degree centrality. |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p629&r=net |
| By: | Michael Barber; Thomas Scherngell |
| Abstract: | An overarching concern in regional science is the characterization of interactions—such as commuter flows, transport, migration, or knowledge flows—within and between subnational spatial units. In this work, we use techniques from social network analysis to address the quality, rather than the quantity, of such interactions. Given the great current interest in European R&D networks, in which organizations from the science and the industry sector distributed across European regions perform joint R&D, we focus on interactions constituting knowledge flows in the European R&D network, as inferred from Framework Programme (FP) data. To assess a specific quality of these region-to-region interactions, we make use of the concept of edge betweenness centrality, which assesses the power of a relation based on the load placed on the corresponding network edge. Betweenness centrality is calculated using the geodesic paths between all distinct pairs of network vertices. Those vertices and edges required by relatively many of the paths thus often lie between other vertices; the fraction of the shortest paths on which an edge occurs is defined as the edge betweenness centrality. Edges with high betweenness centrality have the greatest load, are strategically positioned, and potentially can act as bottlenecks for the flows. We use this idea to evaluate knowledge flows between organizations in the European R&D network, considering several ways to relate the betweenness centrality at the level of FP project participants to knowledge flows at the NUTS2 regional level. We do so by aggregating betweenness centrality values calculated using bipartite graphs linking organizations to the FP projects in which they participate, considering annual FP data between the years 1999 and 2006. We determine the most central inter-regional knowledge flows, describe how this changes over time, and consider the implications for knowledge flows in European R&D networks. We model the centrality of the flows by means of spatial interaction models, estimating how geographical, technological, and social factors influence which region pairs become bottlenecks in the flow of knowledge. The results have meaningful implications to European R&D policy, in particular concerning which region pairs constitute the core in European R&D networks and which mechanisms drive the formation of this regional core. Keywords: European R&D networks, social network analysis, betweenness centrality, Framework Programmes JEL codes: L14, O31, R12 |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa12p460&r=net |