5,064 research outputs found

    Partner Heterogeneity Increases the Set of Strict Nash Networks

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    Galeotti et al. (2006, [2]) show that all minimal networks can be strict Nash in two-way flow models with full parameter heterogeneity while only inward pointing stars and the empty network can be strict Nash in the homogeneous parameter model of Bala and Goyal (2000, [1]). In this note we show that the introduction of partner heterogeneity plays a major role in substantially increasing the set of strict Nash equilibria.

    On the Interaction between Player Heterogeneity and Partner Heterogeneity in Two-way Flow Strict Nash Networks

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    This paper brings together analyses of two-way flow Strict Nash networks under exclusive player heterogeneity assumption and exclusive partner heterogeneity assumption. This is achieved through examining how the interactions between these two assumptions influence important properties of Strict Nash networks. Built upon the findings of Billand et al (2011) and Galeotti et al (2006), which assume exclusive partner heterogeneity and exclusive player heterogeneity respectively, I provide a proposition that generalizes the results of these two models by stating that: (i) Strict Nash network consists of multiple non-empty components as in Galleotti et al (2006), and (ii) each non-empty component is a branching or Bi network as in Billand et al (2011). This proposition requires that a certain restriction on link formation cost (called Uniform Partner Ranking), which encloses exclusive partner heterogeneity and exclusive player heterogeneity as a specific case, is satisfied. In addition, this paper shows that value heterogeneity plays a relatively less important role in changing the shapes of Strict Nash networks

    On the Interaction between Player Heterogeneity and Partner Heterogeneity in Strict Nash Networks

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    This paper brings together analyses of Strict Nash networks under exclusive player heterogeneity assumption and exclusive partner heterogeneity assumption. This is achieved through examining how the interactions between these two assumptions influence important properties of Strict Nash networks. Built upon the findings of Billand et al (2011) and Galleotti et al (2006), which assume exclusive partner hetero- geneity and exclusive player heterogeneity respectively, I provide a proposition that generalizes the results of these two models by stating that: (i) Strict Nash network consists of multiple non-empty components as in Galleotti et al (2006), and (ii) each non-empty component is a branching or Bi network as in Billand et al (2011). This proposition requires that a certain restriction on link formation cost (called Uniform Partner Rankng), which encloses exclusive partner heterogeneity and exclusive player heterogeneity as a specific case, is satisfied. In addition, this paper shows that value heterogeneity plays a relatively less important role in changing the shapes of Strict Nash networks

    Resources Flows Asymmetries in Strict Nash Networks with Partner Heterogeneity

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    Working paper GATE 2011-08This paper introduces a partner heterogeneity assumption in the one-way flow model of Bala and Goyal (2000, [1]). Our goal consists in the characterization of strict Nash networks with regard to the set of resources obtained by players. We use the notion of condensation network which allows us to divide the population in sets of players who obtain the same resources and we order these sets according to the resources obtained. Accordingly, we can examine the relationship between heterogeneity and asymmetries in networks. We establish that the nature of heterogeneity plays a crucial role on asymmetries observed in equilibrium networks

    Modeling Resource Flow Asymmetries using Condensation Networks

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    This paper analyzes the asymmetries with regard to the resources obtained by groups of players in equilibrium networks. We use the notion of condensation networks which allows us to partition the population into sets of players who obtain the same resources and we order these sets according to the resources obtained. We establish that the nature of heterogeneity plays a crucial role on asymmetries observed in equilibrium networks. Our approach is illustrated by introducing the partner heterogeneity assumption into the one-way ow model of Bala and Goyal[1].

    Efficient Networks in Models of Player and Partner Heterogeneity

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    This paper contributes to the literature on centrality measures in economics by defining a team game and identifying the key players in the game. As an illustration of the theory we create a unique data set from the UEFA Euro 2008 tournament. To capture the interaction between players we create the passing network of each team. This all allows us to identify the key player and key groups of players for both teams in each game. We then use our measure to explain player ratings by experts and their market values. Our measure is significant in explaining expert ratings. We also find that players having higher intercentrality measures, regardless of their field position have significantly higher market values.

    Existence of Nash Networks and Partner Heterogeneity

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    In this paper, we pursue the work of H. Haller and al. (2005, [10]) and examine the existence of equilibrium networks, called Nash networks, in the noncooperative two-way flow model (Bala and Goyal, 2000, [1]) with partner heterogeneous agents. We show through an example that Nash networks do not always exist in such a context. We then restrict the payoff function, in order to find conditions under which Nash networks always exist. We give two properties : increasing differences and convexity in the first argument of the payoff function, that ensure the existence of Nash networks. It is worth noting that linear payoff functions satisfy the previous properties.Nash networks; two-way flow models; partner heterogeneity

    Essays on social networks

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    The first chapter provides a way of evaluating a player\u27s contribution to their team and relates their effort to their market values. We extend the work of Ballester et al. (2006) by incorporating a network outcome component in the players\u27 payoff functions. As an illustration of the theory, we create a unique data set from the UEFA Euro 2008 tournament. To capture the interaction between players, we create the passing network of each team. This all allows us to identify the key player and key groups of players for both teams in each game. We then use our measure to explain player ratings by experts and their market values. Our measure is significant in explaining expert ratings. We also find that players having higher intercentrality measures, regardless of their field position have significantly higher market values. The second chapter characterizes efficient networks in player and partner heterogeneity models for both the one-way flow and the two-way flow models. Player (partner) dependent network formation allows benefits and costs to be player (partner) heterogeneous which is an important extension for modeling social networks in the real world. Employing widely used assumptions, I show that efficient networks in the two-way flow model are minimally connected and have star or derivative of star type architectures, whereas efficient networks in the one way flow model have wheel architectures. The third chapter considers a non-cooperative network formation game where identity is introduced as a single dimension to capture the player characteristics. Each player is allowed to choose their commitment level to their identities. The cost of link formation decreases as the players forming the link share the same identity and higher commitment levels. We then introduce link and node imperfections to the model. Each existing link in the network successfully transmits information with a probability. We consider two cases for reliability probability of existing links: a homogenous probability, p and heterogeneous probability. We characterize the Nash networks and we find that the set of Nash networks are either singletons with no links formed or separated blocks or components with mixed blocks or connected
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