nep-net New Economics Papers
on Network Economics
Issue of 2012‒10‒20
eleven papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Exclusionary Pricing in a Two-Sided Market By Motta, Massimo; Vasconcelos, Helder
  2. Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information By Christian Matthes; Francesca Rondina
  3. The Role of Coordination Bias in Platform Competition By Hanna Halaburda; Yaron Yehezkel
  4. Peers' influence on political choices: Evidence from random classroom assignments in college By Camila Campos; Fernanda L L de Leon
  5. The role of distances in the World Trade Web By Francesco Picciolo; Tiziano Squartini; Franco Ruzzenenti; Riccardo Basosi; Diego Garlaschelli
  6. Peer Effects in Risk Aversion By Ana I. Balsa; Néstor Gandelman; Nicolás Gonzalez
  8. Prosocial norms and degree heterogeneity in social networks By Espinosa Alejos, María Paz; Kovarik, Jaromir; Brañas-Garza, Pablo; Cobo-Reyes, Ramón; Jiménez, Natalia; Ponti, Giovanni
  10. Collaborative Learning is Better By Hélène Le Cadre; Bedo Jean-Sébastien
  11. Strong random correlations in networks of heterogeneous agents By Imre Kondor; Istv\'an Csabai; G\'abor Papp; Enys Mones; G\'abor Czimbalmos; M\'at\'e Csaba S\'andor

  1. By: Motta, Massimo; Vasconcelos, Helder
    Abstract: In this paper we provide a new way of modelling two-sided markets, and we then use this model to study anti-competitive conduct in an asymmetric two-sided market which captures the main features of some recent antitrust cases. We show that below-cost pricing on one market side can allow an incumbent firm to exclude a more efficient rival which does not have a customer base yet. This exclusionary behaviour is the more likely to occur the more mature the market and the stronger the established customer base of the incumbent.
    Keywords: Demand externalities; Predation; Two-sided markets
    JEL: L11 L13 L41
    Date: 2012–10
  2. By: Christian Matthes; Francesca Rondina
    Abstract: This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a significant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified.
    Keywords: asymmetric information, learning, monetary policy
    JEL: E52
    Date: 2012–09
  3. By: Hanna Halaburda (Strategy Unit, Harvard Business School); Yaron Yehezkel (Faculty of Management, Tel-Aviv University)
    Abstract: This paper considers platform competition in a two-sided market that includes buyers and sellers. One of the platforms benefits from a favorable coordination bias in the market, in that the two sides are more likely to join the advantaged platform. We find that the degree of the coordination bias affects the platform's decision regarding the business model (i.e., whether to subsidize buyers or sellers), the access fees and the size of the platform. A slight increase in the coordination bias may induce the advantaged platform to switch from subsidizing sellers to subsidizing buyers, or induce the disadvantaged platform to switch from subsidizing buyers to subsidizing sellers. Moreover, in the former case the advantaged platform switches from oversupplying to undersupplying sellers, while in the latter case the disadvantaged platform switches from undersupplying to oversupplying sellers.
    Keywords: platform competition, two-sided markets, coordination bias
    JEL: L11 L14
    Date: 2012–08
  4. By: Camila Campos (Insper); Fernanda L L de Leon (University of East Anglia)
    Abstract: Social networks are believed to a§ect individuals’ political views; however, quantifying this e§ect and understanding the channels behind this influence are empirically challenging. This study investigates peer e§ects on political behavior, using a self-collected survey among freshmen from the largest university in Brazil. The identification relies on the random assignment of freshmen to classrooms. We found that a relevant peer influence occurs through classmates’ political involve- ment, increasing students’ political participation, knowledge and moving their ideologies toward the center. Other mechanisms of influence, such as social pres- sure to adopt certain views or reinforcement of one’s own preferences, were not observed in the data.
    Date: 2012–10–07
  5. By: Francesco Picciolo; Tiziano Squartini; Franco Ruzzenenti; Riccardo Basosi; Diego Garlaschelli
    Abstract: In the economic literature, geographic distances are considered fundamental factors to be included in any theoretical model whose aim is the quantification of the trade between countries. Quantitatively, distances enter into the so-called gravity models that successfully predict the weight of non-zero trade flows. However, it has been recently shown that gravity models fail to reproduce the binary topology of the World Trade Web. In this paper a different approach is presented: the formalism of exponential random graphs is used and the distances are treated as constraints, to be imposed on a previously chosen ensemble of graphs. Then, the information encoded in the geographical distances is used to explain the binary structure of the World Trade Web, by testing it on the degree-degree correlations and the reciprocity structure. This leads to the definition of a novel null model that combines spatial and non-spatial effects. The effectiveness of spatial constraints is compared to that of nonspatial ones by means of the Akaike Information Criterion and the Bayesian Information Criterion. Even if it is commonly believed that the World Trade Web is strongly dependent on the distances, what emerges from our analysis is that distances do not play a crucial role in shaping the World Trade Web binary structure and that the information encoded into the reciprocity is far more useful in explaining the observed patterns.
    Date: 2012–10
  6. By: Ana I. Balsa; Néstor Gandelman; Nicolás Gonzalez
    Abstract: Using data on Uruguayan adolescents, we estimate peer effects in risk attitudes. Relative risk aversion is elicited in an experimental setting. Identification is based on parents not being able to choose the class within the school of their choice. After controlling for school-grade fixed effect and addressing endogeneity due to simultaneity, we find a significant and quantitative large impact of peers on individuals risk aversion. An increase in one standard deviation of the group risk aversion produces an increase in 44-64% on an individual risk aversion. These findings enhance the importance of multiplicative effects related to risk behavior.
    Keywords: risk aversion; peer effects; instrumental variables
    JEL: I12 D1
    Date: 2012
  7. By: Nicola Lacetera (Rotman School of Management, University of Toronto); Mario Macis (Carey Business School, Johns Hopkins University); Angelo Mele (Carey Business School, Johns Hopkins University)
    Abstract: We present preliminary results from a small-scale natural field experiment aimed at exploring online social contagion, with an application to charitable giving. We worked in partnership with Heifer International, a non-profit organization aimed at fighting poverty in developing countries, and HelpAttack!, the developer of a Facebook application that facilitates donations to charities while broadcasting such activities to the donors’ Facebook contacts. We ran a series of marketing campaigns, and randomized the broadcasting of users’ pledges, thereby creating exogenous variation in the information that users’ contacts were receiving. Although our campaigns reached as many as about 13 million Facebook users, 6,000 users clicked on the ad and only 18 pledges were made, without any subsequent pledge from these users’ contacts. We offer potential explanations for this finding on the absence of network effects, and outline our plans for future developments of this on-going project.
    Keywords: Online networks, diffusion, pro-social behavior, network effects
    JEL: C93 D64 O33 M31
    Date: 2012–09
  8. By: Espinosa Alejos, María Paz; Kovarik, Jaromir; Brañas-Garza, Pablo; Cobo-Reyes, Ramón; Jiménez, Natalia; Ponti, Giovanni
    Abstract: We provide empirical evidence to support the claims that social diversity promotes prosocial behavior. We elicit a real-life social network and its members’ adherence to a social norm, namely inequity aversion. The data reveal a positive relationship between subjects’ prosociality and several measures of centrality. This result is in line with the theoretical literature that relates the evolution of social norms to the structure of social interactions and argues that central individuals are crucial for the emergence of prosocial behavior.
    Keywords: social diversity, social norms, prosocial behavior
    Date: 2012
    Abstract: This study investigates the advantage of social network mining in a customer retention context. A company that is able to identify likely churners in an early stage can take appropriate steps to prevent these potential churners from actually churning and subsequently increase profit. Academics and practitioners are constantly trying to optimize their predictive-analytics models by searching for better predictors. The aim of this study is to investigate if, in addition to the conventional sets of variables (socio-demographics, purchase history, etc.), kinship network based variables improve the predictive power of customer retention models. Results show that the predictive power of the churn model can indeed be improved by adding the social network (SNA-) based variables. Including network structure measures (i.e. degree, betweenness centrality and density) increase predictive accuracy, but contextual network based variables turn out to have the highest impact on discriminating churners from non-churners. For the majority of the latter type of network variables, the importance in the model is even higher than the individual level counterpart variable.
    Keywords: network based marketing, CRM, predictive analystics, social network analysis (SNA), kinship network, financial services, random forests
    Date: 2012–05
  10. By: Hélène Le Cadre (LIMA - CEA, LIST, Laboratory of Information, Models and Learning - CEA : SACLAY); Bedo Jean-Sébastien (Orange/France-Télécom - Telecom Orange)
    Abstract: In this article, we focus on the identification of emerging economic organizations while agents are learning hidden individual sequences modeling renewable energy production and microgrid instantaneous needs in a decentralized hierarchical network. The network is made of 3 categories of agents: producers, providers and end users belonging to microgrids. In this uncertain context, providers are penalized in case where they cannot satisfy the entire demand of the associated microgrid. Identically, producers are penalized in case where they cannot deliver the quantity of energy booked by the providers. Service providers need to make efficient forecasts about the hidden individual sequences to optimize their decisions concerning the quantities of energy to book and the prices of the energy. We prove that there exists prices that provide to the producers a guarantee to avoid penalties. Additionally, under external regret minimization, collaborative learning through a grand coalition where the providers share their information and align their forecasts, enables them to minimize their average loss. As an illustration, we compare the convergence rates of the collaborative learning strategy with rates resulting from selfish learning based on external and internal regret minimization in a 2 producers, 3 providers network. The results confirm the theory: collaboration is better for the providers.
    Keywords: Distributed Learning; Regret; Algorithmic Game Theory; Coalition
    Date: 2012–07–07
  11. By: Imre Kondor; Istv\'an Csabai; G\'abor Papp; Enys Mones; G\'abor Czimbalmos; M\'at\'e Csaba S\'andor
    Abstract: Correlations and other collective phenomena in a schematic model of heterogeneous binary agents (individual spin-glass samples) are considered on the complete graph and also on 2d and 3d regular lattices. The system's stochastic dynamics is studied by numerical simulations. The dynamics is so slow that one can meaningfully speak of quasi-equilibrium states. Performing measurements of correlations in such a quasi-equilibrium state we find that they are random both as to their sign and absolute value, but on average they fall off very slowly with distance in all instances that we have studied. This means that the system is essentially non-local, small changes at one end may have a strong impact at the other. Correlations and other local quantities are extremely sensitive to the boundary conditions all across the system, although this sensitivity disappears upon averaging over the samples or partially averaging over the agents. The strong, random correlations tend to organize a large fraction of the agents into strongly correlated clusters that act together. If we think about this model as a distant metaphor of economic agents or bank networks, the systemic risk implications of this tendency are clear: any impact on even a single strongly correlated agent will spread, in an unforeseeable manner, to the whole system via the strong random correlations.
    Date: 2012–10

This nep-net issue is ©2012 by Yi-Nung Yang. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.