nep-net New Economics Papers
on Network Economics
Issue of 2010‒06‒26
seven papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Behavioral Effects in Individual Decisions of Network Formation: Complexity Reduces Payoff Orientation and Social Preferences By Harmsen - van Hout, Marjolein J.W.; Dellaert, Benedict G.C.; Herings, P. Jean-Jacques
  2. Bank lending networks, experience, reputation, and borrowing costs By Christophe J. Godlewski; Bulat Sanditov; Thierry Burger-Helmchen
  3. Institutional communication revisited: Preferences, opportunity structures and scientific expertise in policy networks By Philip Leifeld; Volker Schneider
  4. Networks are Useful Description, Assemblages are Powerful Explanations By Haynes, Paul
  5. Influence Networks By Dunia López-Pintado
  6. Business fluctuations in a credit-network economy By Domenico Delli Gatti; Mauro Gallegati; Bruce Greenwald; Alberto Russo; Joseph E. Stiglitz
  7. Is it Live or is it Internet? Experimental Estimates of the Effects of Online Instruction on Student Learning By David N. Figlio; Mark Rush; Lu Yin

  1. By: Harmsen - van Hout, Marjolein J.W. (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)); Dellaert, Benedict G.C. (Department of Business Economics / Marketing Section, Erasmus School of Economics, Erasmus University Rotterdam); Herings, P. Jean-Jacques (Department of Economics, School of Business and Economics, Maastricht University)
    Abstract: Network formation constitutes an important part of many social and economic processes, but relatively little is known about how individuals make their linking decisions in networks. This article provides an experimental investigation of behavioral effects in individual decisions of network formation. Our findings demonstrate that the inherent complexity of the network setting makes individuals’ choices systematically less payoff-guided and also strongly reduces their social orientation. Furthermore, we show that specific network complexity features aggravate the former effect. These behavioral effects have important implications for researchers and managers working in areas that involve network formation.
    Keywords: network formation; individual decision making; behavioral effects; network complexity; payoff orientation; social preferences; choice experiments; mixed logit
    JEL: A14 C91 D85
    Date: 2010–05
  2. By: Christophe J. Godlewski (LaRGE Research Center, Université de Strasbourg); Bulat Sanditov (University of Maastricht); Thierry Burger-Helmchen (BETA Research Center, Université de Strasbourg)
    Abstract: We investigate the network structure of syndicated lending markets and evaluate the impact of lenders’ network centrality, considered as measures of their experience and reputation, on borrowing costs. We show that the market for syndicated loans is a “small world” characterized by large local density and short social distances between lenders. Such a network structure allows for better information and resources flows between banks thus enhancing their social capital. We then show that lenders’ experience and reputation play a significant role in reducing loan spreads and thus increasing borrower’s wealth.
    Keywords: Agency costs, bank syndicate, experience, loan syndication, reputation, small world, social network analysis.
    JEL: G21 G24 L14
    Date: 2010
  3. By: Philip Leifeld (Max Planck Institute for Research on Collective Goods, Bonn); Volker Schneider (University of Konstanz)
    Abstract: Information exchange in policy networks is usually attributed to preference similarity, influence reputation, social trust and institutional actor roles. We suggest that political opportunity structures and transaction costs play another crucial role and estimate a rich statistical network model on tie formation in the German toxic chemicals policy domain. The results indicate that the effect of preference similarity is absorbed by other determinants while opportunity structures indeed have to be taken into account. We also find that different types of information exchange operate in complementary, but not necessarily congruent, ways.
    Date: 2010–04
  4. By: Haynes, Paul
    Abstract: Network models are ubiquitous and offer useful descriptions of a range of a wide variety of phenomena. However, such models lack a consistent and robust ontological framework and, as a consequence, network models are often not models at all, but merely descriptions composed of fragmented and internally inconsistent models and theories that emerged over time and across a range of different perspectives, each with different underlying assumptions. To address this problem a more critical approach to network structures is required in order to move from a descriptive account to an explanatory account. This working paper addressing the topic of network ontology and introduces the notion of assemblages in order to give a clearer framework for network thinking. While this working paper serves merely to introduce the notion of assemblages, the concept is designed to be applied to actual network structures and, as such, has been operationalised in research undertaken in INGENIO between 2007-2010 examining the ceramics sector in Spain and Italy (see Haynes forthcoming).
    Date: 2010–03–02
  5. By: Dunia López-Pintado (Department of Economics, Universidad Pablo de Olavide and CORE, Université Catholique de Louvain)
    Abstract: Some behaviors, ideas or technologies spread and become persistent in society, whereas others vanish. This paper analyzes the role of social influence in determining such distinct collective outcomes. Agents are assumed to acquire information from others through a certain sampling process that generates an influence network and use simple rules to decide whether to adopt or not depending on the observed sample. The diffusion threshold (i.e., the spreading rate above which the behavior becomes persistent in the population) and the endemic state (i.e., the fraction of adopters in the stationary state of the dynamics) are characterized as a function of the primitives of the model. The results highlight the importance of the correlation between visibility and connectivity (or degree) for diffusion purposes.
    Keywords: social influence, networks, diffusion threshold, endemic state.
    JEL: C73 L14 O31 O33
    Date: 2010–06
  6. By: Domenico Delli Gatti; Mauro Gallegati; Bruce Greenwald; Alberto Russo; Joseph E. Stiglitz
    Abstract: We model a network economy with three sectors: downstream firms, upstream firms, and banks. Agents are linked by productive and credit relationships so that the behavior of one agent influences the behavior of the others through network connections. Credit interlinkages among agents are a source of bankruptcy diffusion: in fact, failure of fulfilling debt commitments would lead to bankruptcy chains. All in all, the bankruptcy in one sector can diffuse to other sectors through linkages creating a vicious cycle and bankruptcy avalanches in the network economy. Our analysis show how the choices of credit supply by both banks and firms are interrelated. While the initial impact of monetary policy is on bank behaviour, we show the interactive play between the choices made by banks, the choices made by firms in their role as providers of credit, and the choices made by firms in their role as producers.
    Date: 2010–06
  7. By: David N. Figlio; Mark Rush; Lu Yin
    Abstract: This paper presents the first experimental evidence on the effects of live versus internet media of instruction. Students in a large introductory microeconomics course at a major research university were randomly assigned to live lectures versus watching these same lectures in an internet setting, where all other factors (e.g., instruction, supplemental materials) were the same. Counter to the conclusions drawn by a recent U.S. Department of Education meta-analysis of non-experimental analyses of internet instruction in higher education, we find modest evidence that live-only instruction dominates internet instruction. These results are particularly strong for Hispanic students, male students, and lower-achieving students. We also provide suggestions for future experimentation in other settings.
    JEL: I20 I23
    Date: 2010–06

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