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on Network Economics |
| By: | Valeria Ivaniushina (National Research University Higher School of Economics); Daniel Alexandrov (National Research University Higher School of Economics) |
| Abstract: | In this study we focus on the influence of peers on adolescents academic achievement. Specifically, how the learning motivation of peers is related to a student's school grades. We use multilevel regression to analyze the influence of peers on different levels of social circles: school, class, personal network, and compare the effects of "assigned friends" and "chosen friends". The methods of social network analysis are used to define the personal network of a student in different ways: cliques, complete ego networks, and mutual ego networks. We demonstrate that the model improves considerably when the level of personal networks is included between individual and class levels. The learning motivation of a student's friends (defined as a clique or ego network) has an important influence on the student’s school performance, net of student’s personal characteristics. |
| Keywords: | social network analysis, schools, peer influence, ego networks, cliques |
| JEL: | Z |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:43/soc/2014&r=net |
| By: | Sabatini, Fabio; Sarracino, Francesco |
| Abstract: | Does Facebook make people lonely and unhappy? Empirical studies have produced conflicting results about the effect of social networking sites (SNS) use on individual welfare. We use a representative sample of the Italian population to investigate how actual and virtual networks of social relationships influence subjective well-being (SWB). We find a significantly negative correlation between online networking and self-reported happiness. We address endogeneity in online networking by exploiting technological characteristics of the pre-existing voice telecommunication infrastructures that exogenously determined the availability of broadband for high-speed Internet. We try to further disentangle the direct effect of SNS use on well-being from the indirect effect possibly caused by the impact of SNS’s on trust and sociability in a SEM analysis. We find that online networking plays a positive role in SWB through its impact on physical interactions. On the other hand, SNS use is associated with lower social trust, which is in turn positively correlated with SWB. The overall effect of networking on individual welfare is significantly negative. |
| Keywords: | social participation; online networks; Facebook; social trust; social capital; subjective well-being; hate speech; broadband; digital divide. |
| JEL: | C36 D85 O33 Z1 Z13 |
| Date: | 2014–06–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:56436&r=net |
| By: | Azomahou T.T.; Opolot D. (UNU-MERIT) |
| Abstract: | Learning and stochastic evolutionary models provide a useful framework for analyzing repeated interactions and experimentation among economic agents over time. They also provide sharp predictions about equilibrium selection when multiplicity exists. This paper defines three convergence measures, diffusion rate, expected waiting time and convergence rate, for characterizing the short-run, medium-run and long-run behavior of a typical model of stochastic evolution. We provide tighter bounds for each without making restrictive assumptions on the model and amount of noise as well as interaction structure. We demonstrate how they can be employed to characterize evolutionary dynamics for coordination games and strategic diffusion in networks. Application of our results to strategic diffusion gives insights on the role played by the network topology. For example we show how networks made up of cohesive subgroups speed up evolution between quasi-stable states while sparsely connected networks have the opposite effect of favoring almost global stability. Keywords Learning and evolution, networks, diffusion rate, convergence rate, expected waiting time |
| Keywords: | Stochastic and Dynamic Games; Evolutionary Games; Repeated Games; Information, Knowledge, and Uncertainty: General; |
| JEL: | C73 D80 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2014035&r=net |
| By: | Spiros Bougheas; Alan Kirman |
| Abstract: | In this paper we review recent advances in financial economics in relation to the measurement of systemic risk. We start by reviewing studies that apply traditional measures of risk to financial institutions. However, the main focus of the review is on studies that use network analysis paying special attention to those that apply complex analysis techniques. Applications of these techniques for the analysis and pricing of systemic risk has already provided significant benefits at least at the conceptual level but it also looks very promising from a practical point of view. |
| Keywords: | Comlex Financial Systems, Networks, Systemic Risk |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:not:notcfc:14/04&r=net |
| By: | Azomahou T.T.; Opolot D. (UNU-MERIT) |
| Abstract: | We study the dynamics of individual beliefs and information aggregation when agents communicate via a social network. We provide a general framework of social learning that captures the interactive effects of three main factors on the structure of individual beliefs resulting from such a dynamic process; that is historical factorsprior beliefs, learning mechanismsrational and bounded rational learning, and the topology of communication structure governing information exchange. More specifically, we provide conditions under which heterogeneity and consensus prevail. We then establish conditions on the structures of the communication network, prior beliefs and private information for public beliefs to correctly aggregate decentralized information. The speed of learning is also established, but most importantly, its implications on efficient information aggregation. Keywords Learning, social networks, public beliefs, speed of learning, information aggregation. |
| Keywords: | Game Theory and Bargaining Theory: General; Search; Learning; Information and Knowledge; Communication; Belief; Network Formation and Analysis: Theory; |
| JEL: | C70 D83 D85 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2014034&r=net |
| By: | Azomahou T.T.; Opolot D. (UNU-MERIT) |
| Abstract: | This paper introduces epsilon-stability as a generalization of the concept of stochastic stability in learning and evolutionary game dynamics. An outcome of a model of stochastic evolutionary dynamics is said to be epsilon-stable in the long-run if for a given model of mistakes it maximizes its invariant distribution. We construct an efficient algorithm for computing epsilon-stable outcomes and provide conditions under which epsilon-stability can be approximated by stochastic stability. We also define and provide tighter bounds for contagion rate and metastability as measures for characterizing the short-run and medium-run behaviour of a typical stochastic evolutionary model. Keywords Stochastic evolution, network games, epsilon-stable sets, expected waiting time, metastability, contagion rate. |
| Keywords: | Stochastic and Dynamic Games; Evolutionary Games; Repeated Games; Information, Knowledge, and Uncertainty: General; |
| JEL: | C73 D80 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2014036&r=net |