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on Network Economics |
| By: | Weiergräber, Stefan |
| Abstract: | I develop an empirical framework to disentangle different sources of consumer inertia in the US wireless industry. The use of a detailed data set allows me to identify preference heterogeneity from consumer type-specific market shares and switching costs from churn rates. Identification of a localized network effect comes from comparing the dynamics of distinct local markets. The central condition for identification is that neither the characteristics defining consumer heterogeneity nor the characteristics defining reference groups are a (weak) subset of the other. Being able to separate switching costs and network effects is important as both can lead to inefficient consumer inertia, but depending on its sources policy implications may be very different. Estimates of switching costs range from US-$ 316 to US-$ 630. The willingness to pay for a 20%-point increase in an operator’s market share is on average US-$ 22 per month. My counterfactuals illustrate that both effects are important determinants of consumers’ price elasticities potentially translating into market power that helps large carriers in defending their dominant position. |
| Date: | 2014–11–17 |
| URL: | http://d.repec.org/n?u=RePEc:lmu:muenec:25094&r=net |
| By: | Simpson Zhang; Mihaela van der Schaar |
| Abstract: | In many real world networks agents are initially unsure of each other's qualities and learn about each other over time via repeated interactions. This paper is the first to provide a methodology for studying the formation of such networks, taking into account that agents differ from each other, that they begin with incomplete information, and that they must learn through observations which connections/links to form and which to break. The network dynamics in our model vary drastically from the dynamics emerging in models of complete information. With incomplete information and learning, agents who provide high benefits will develop high reputations and remain in the network, while agents who provide low benefits will drop in reputation and become ostracized. We show, among many other things, that the information to which agents have access and the speed at which they learn and act can have tremendous impact on the resulting network dynamics. Using our model, we can also compute the \textit{ex ante} social welfare given an arbitrary initial network, which allows us to characterize the socially optimal network structures for different sets of agents. Importantly, we show through examples that the optimal network structure depends sharply on both the initial beliefs of the agents, as well as the rate of learning by the agents. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1507.04065&r=net |
| By: | Stefan Lyocsa; Tomas Vyrost; Eduard Baumohl |
| Abstract: | The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 40 stock markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. By conducting a rolling window spatial probit analysis on the set of edges of Granger causality networks, we confirm the significance of temporal proximity and preferential attachment on edge creation. We extend the analysis by incorporating market specific factors, such as market capitalization, turnover and volatility. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1507.06242&r=net |
| By: | Thiago Christiano Silva; Sergio Rubens Stancato de Souza; Benjamin Miranda Tabak |
| Abstract: | In this paper, we propose novel risk-related network measurements to identify the roles that financial institutions play as potential targets or sources of contagion. We derive theoretical properties and provide a clear systemic risk interpretation for the proposed measures. Devised upon the notion of communicability in networks, we introduce the impact susceptibility index, which indicates whether market participants are locally or remotely vulnerable. We show that this index can be used as a financial stability monitoring tool and apply it to analyze the Brazilian financial market. We find that non-banking institutions are potentially remote vulnerable in certain periods, while banking institutions are not susceptible to indirect impacts. To address the perspective of market participants as sources of contagion, we propose the impact diffusion influence index, which captures the potential influence of financial institutions on propagating impacts in the network. We unveil the presence of a portion of non-large banking institutions that is consistently more influential than large banks in potentially diffusing impacts throughout the network. Regarding financial system stability, regulators should identify the entities that play these two roles, as they can render the system more risky |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:bcb:wpaper:392&r=net |
| By: | Diffo Lambo, Lawrence; Pongou, Roland; Tchantcho, Bertrand; Wambo, Pierre |
| Abstract: | Media, opinion leaders, co-ethnics, family members, and friends influence our political decisions. The ways in which these influences affect political cycles and (in)stability has been understudied. We propose a model of a networked political economy, where agents' choices are partly determined by the opinions of the individuals with whom they are connected in a fixed influence network. The model features two types of individuals: ideological individuals who never change their views and who seek to influence the rest of the society; and non-ideological individuals who have no political allegiance and do not influence anybody, but who can be influenced by ideological individuals with whom they are connected. We show that influence networks increase political turnout and cause non-ideological individuals who are subject to antagonistic influences to keep changing their political views. This in turn increases political cycles and instability in two ways: (1) by reducing the number of stable and popular political leaders; and (2) by worsening the tradeoff between political competition and the existence of a stable leader. We uncover a necessary and sufficient condition that characterizes all of the political technologies and network structures that guarantee political stability. This condition introduces a preference-blind stability index, which maps each pair of a constitution and an influence network into the maximum number of competing political leaders that a society can afford while remaining stable regardless of the extent of preference heterogeneity in its population. Our findings have testable implications for different societies. They shed light on the network origins of political cycles in two-party systems. They also imply that individualist societies are more politically stable than collectivist societies and societies organized around ethnic groups or characterized by a high level of homophilous behavior and influences. For ethnic democracies, we quantify the exact tradeoff between political competition and stability, and show that ethnic fragmentation increases stability. The findings further provide a rationale for using the "divide and rule" strategy to maintain political power. Finally, we find that cliques and multi-layer cliques maximize the competition-stability tradeoff, whereas star networks, lines and rings minimize it. |
| Keywords: | Political cycles, instability, influence networks, homophily, ethnic democracy, competition-stability tradeoff. |
| JEL: | C0 C7 D7 D8 D85 H0 O1 |
| Date: | 2015–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:65641&r=net |
| By: | Emilio Calvo (Universidad de Valencia. ERI-CES); Esther Gutiérrez-López (Departamento de Economía Aplicada IV. Universidad del País Vasco U.P.V./E.H.U.) |
| Abstract: | We consider cooperative games in which the cooperation among players is restricted by a set system, which outlines the set of feasible coalitions that actually can be formed by players in the game. In our setting, the structure of this set system is completely free, and the only restriction is that the empty set belongs to it. An extension of the Shapley value is provided as the sum of the dividends that players obtain in the game. In this general setting, we offer two axiomatic characterizations for the value: one by means of component efficiency and fairness, and the other one with efficiency and balanced contributions. |
| Keywords: | TU-games; Restricted cooperation; Shapley value. |
| JEL: | C71 |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:dbe:wpaper:0115&r=net |
| By: | Chen, Ying-Ju; Zenou, Yves; Zhou, Junjie |
| Abstract: | We consider a network model where individuals exert efforts in two types of activities that are interdependent. These activities can be either substitutes or complements. We focus on criminals that either exert efforts in crime and education (substitutable activities) or crime and drug consumption (complementary activities). We provide a full characterization of the Nash equilibrium of this game for any network structure and show under which condition it exists and is unique. We then derive some comparative statics results that offer strong empirical predictions on the effect of own productivity on both efforts and how network density affects equilibrium outcomes. Finally, we re-examine the key-player policy that consists in determining the criminal who, once removed, reduces total crime the most. We show that, if the planner ignores the fact that criminals have multiple activities, then she can wrongly determine who the key player is. |
| Keywords: | criminal networks; key player; multiple activities |
| JEL: | A14 D85 K42 Z13 |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:10709&r=net |
| By: | Matthew Elliott (Caltech); Arun Chandrasekhar (Stanford); Attila Ambrus (Duke University) |
| Abstract: | This paper studies costly network formation in the context of risk sharing. Neighboring agents negotiate agreements as in Stole and Zwiebel (1996), which results in the social surplus being allocated according to the Myerson value. We uncover two types of inefficiency: overinvestment in social relationships within group (e.g., caste, ethnicity), but underinvestment across group. We find a novel tradeoff between efficiency and equality. Both within and across groups, inefficiencies are minimized by increasing social inequality, which results in financial inequality and increasing the centrality of the most central agents. Evidence from 75 Indian village networks is congruent with our model. |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed015:189&r=net |
| By: | Thiago Christiano Silva; Sergio Rubens Stancato de Souza; Benjamin Miranda Tabak |
| Abstract: | In this paper, we provide a detailed analysis of the roles FIs play within the interbank market using a network-based approach. We investigate how the interbank network evolves with respect to different types of market participants. For this analysis, we employ several well-known complex network measures that extract topological characteristics of the interbank network. We use the weighted clustering coefficient to assess the substitutability of FIs for the lending and borrowing perspectives and find that large banking institutions are counterparties that are easily substitutable. In addition, we verify that the interbank network presents a high disassortative mixing pattern, suggesting that highly connected FIs are frequently connected to others with very few connections. This finding is in line with the fact that interbank networks often show a core-periphery structure. We also investigate the presence of the ``rich-club'' effect on the network and find that it is strongly present in the community comprising the large banking institutions, as they normally form near-clique structures. Since they often play the role of liquidity providers in the interbank market, this interconnectedness effectively endows the network with robustness, as participants that are with liquidity issues can easily substitute counterparties that are liquidity suppliers |
| Date: | 2015–06 |
| URL: | http://d.repec.org/n?u=RePEc:bcb:wpaper:391&r=net |