nep-net New Economics Papers
on Network Economics
Issue of 2020‒08‒17
seventeen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Integration and Diversity By Sanjeev Goyal; Penelope Hernandez; Guillem Martinez-Canovas; Frederic Moisan; Manuel Munoz-Herrera; Angel Sanchez
  2. Large Scale Experiments on Networks: A New Platform with Applications By Choi, S.; Goyal, G.; Moisan, F.
  3. Social Interaction Methods By Hsieh, Chih-Sheng; Lin, Xu; Patacchini, Eleonora
  4. Invention and Collaboration Networks in Latin America: Evidence from Patent Data By Carlos Bianchi; Pablo Galaso; Sergio Palomeque
  5. Inference and Influence of Large-Scale Social Networks Using Snapshot Population Behaviour without Network Data By Godoy-Lorite, Antonia; Jones, Nick S.
  6. Trouble Comes in Threes: Core stability in Minimum Cost Connection Networks By Jens Leth Hougaard; Mich Tvede
  7. Efficient Incentives in Social Networks: Gamification and the Coase Theorem By Daske, Thomas
  8. Peer Effects on the United States Supreme Court By Richard Holden; Michael Keane; Matthew Lilley
  9. Implementation of Optimal Connection Networks By Jens Leth Hougaard; Mich Tvede
  10. Investments in Social Ties, Risk Sharing and Inequality By Ambrus, A.; Elliott, M.
  11. Spatial Production Economics By Orea, Luis; Álvarez, Inmaculada C.
  12. Collaborative production networks among unequal actors By Manuel Munoz-Herrera; Jacob Dijkstra; Andreas Flache; Rafael Wittek
  13. Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity By Mohammad Ghaderi
  14. Altruism, Insurance, And Costly Solidarity Commitments By Barrett, Chris; Nourani, Vesall; Patacchini, Eleonora; Walker, Thomas
  15. Long Memory and Correlation Structures of Select Stock Returns Using Novel Wavelet and Fractal Connectivity Networks By BHANDARI, AVISHEK
  16. Systemic Risk-Shifting in Financial Networks By Elliott, M.; Georg, C-P.; Hazell, J.
  17. Peer Effects in Central Banking By Roman Horvath

  1. By: Sanjeev Goyal; Penelope Hernandez; Guillem Martinez-Canovas; Frederic Moisan; Manuel Munoz-Herrera; Angel Sanchez (Division of Social Science)
    Abstract: We study a setting where individuals prefer to coordinate with others but they di er on their preferred action. Our interest is understanding the role of linking in shaping behavior. So we consider the situation in which interactions are exogenous and a situation where individuals choose links that determine the interactions. Theory is permissive in both settings: conformism (on either of the actions) and diversity (with di erent groups choosing their preferred actions) are both sustainable in equilibrium. Our experiments reveal that, in an exogenous complete network, subjects choose to conform to the majority's preferred action. By contrast, when linking is free and endogenous, subjects form dense networks (biased in favour of linking within same preferences type) but choose diverse actions. The convergence to diverse actions is faster under endogenous linking as compared to the convergence to conformity on the majority's preferred action under the exogenous complete network. Thus, our experiment suggests that individuals use links selectively to swiftly solve the coordination problem.
    Date: 2019–03
  2. By: Choi, S.; Goyal, G.; Moisan, F.
    Abstract: This paper presents a new platform for large scale networks experiments in continuous time. The versatility of the platform is illustrated through three experiments: a game of linking, a linking game with public goods, and a linking game with trading and intermediation. Group size ranges from 8 to 100 subjects. These experiments reveal that subjects create sparse networks that are almost always highly efficient. In some experiments the networks are centralized and unequal, while in others they are dispersed and equal. These network structures are in line with theoretical predictions, suggesting that continuous time asynchronous choice facilitates a good match between experimental outcomes and theory. The size of the group has powerful effects on individual investments in linking and effort, on network structure, and on the nature of payoff inequality. Researchers should therefore exercise caution in drawing inferences about behaviour in large scale networks based on data from small group experiments.
    JEL: C92 D83 D85 Z13
    Date: 2020–07–15
  3. By: Hsieh, Chih-Sheng; Lin, Xu; Patacchini, Eleonora
    Abstract: This paper is concerned with methods for analyzing social interaction effects. The attention is focused on how to estimate endogenous effects, where an individual's choice may depend on those of his/her contacts about the same activity. The analysis is guided by the data structure that is available to measure social interactions, an intuitive aspect that allows empirical researchers to understand whether and how they could study social interaction effects in their own data. First, the case where the information on social interaction patterns is limited to membership to a given group is considered, then the discussion moves to the case where the data contain information on specific relationships among pairs of individuals within each group, and the availability of data on the co-evolution of social structures and outcomes. This paper also discusses some basic methods to deal with online social network data, and the novel literature estimating social interaction effects relying only on outcome data. For each data structure, the challenges and the main methods proposed in the literature to tackle them are reviewed.
    Date: 2019–11
  4. By: Carlos Bianchi (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Pablo Galaso (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Sergio Palomeque (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración)
    Abstract: This research aims to analyze the collaboration networks associated with the processes of invention and patenting in Latin American countries between 1970 and 2017. To do so, we apply social network analysis techniques to a rich database containing information from patents developed by Latin American inventors and registered in the USPTO during such period. We build and analyze three types of collaboration networks: networks of inventors, networks of innovators (i.e. patent owners) and networks of countries in the region. The study of the structural properties and the evolution of such networks allow us to present unprecedented empirical evidence on the forms of interaction and collaboration to invent in Latin America. This evidence shows that collaboration networks in Latin America are highly fragmented and disconnected. Moreover, networks are notoriously foreign-oriented, i.e. the linkages with external nodes are critical compared to the low presence of local connections. Major differences among the countries of the region can be observed, which allow us to identify different behaviors according to how much they use the patent system and the relative development of the national networks. In a region which has been historically characterized by high heterogeneity, this research allows recognizing specific patterns of innovation at the national level. In sum, the contributions of the paper are three fold. First, it presents novel empirical findings with unique information on interaction patterns at the Latin American level. Second, it allows analyzing the whole region and the main trends in the light of the large research background on invention and development from this region. Finally, it discusses some stylized facts in national cases, with the aim of encouraging new research questions for further research agenda.
    Keywords: patents, invention, social network analysis, collaboration networks, Latin America
    JEL: O31 O54 P48
    Date: 2020–04
  5. By: Godoy-Lorite, Antonia; Jones, Nick S.
    Abstract: Population behaviours, such as voting and vaccination, depend on social networks. Social networks can differ depending on behaviour type and are typically hidden. However, we do often have large-scale behavioural data, albeit only snapshots taken at one timepoint. We present a method that jointly infers large-scale network structure and a networked model of human behaviour using only snapshot population behavioural data. This exploits the simplicity of a few-parameter, geometric socio-demographic network model and a spin-based model of behaviour. We illustrate, for the EU Referendum and two London Mayoral elections, how the model offers both prediction and the interpretation of our homophilic inclinations. Beyond offering the extraction of behaviour-specific network-structure from large-scale behavioural datasets, our approach yields a crude calculus linking inequalities and social preferences to behavioural outcomes. We give examples of potential network-sensitive policies: how changes to income inequality, a social temperature and homophilic preferences might have reduced polarisation in a recent election.
    Date: 2020–07–17
  6. By: Jens Leth Hougaard (NYU-Shanghai, China; Department of Food and Resource Economics, University of Copenhagen); Mich Tvede (University of East Anglia)
    Abstract: We consider a generalization of the Minimum Cost Spanning Tree (MCST) model dubbed the Minimum Cost Connection Network (MCCN) model, where network users have connection demands in the form of a pair of target nodes they want connected directly, or indirectly. Given a network which satisfies all connection demands at min-imum cost, the problem consists of allocating the total cost of the efficient network among its users. As such, every MCCN problem induces a cooperative cost game where the cost of each each coalition of users is given by the cost of an efficient net-work satisfying the demand of the users in the coalition. Unlike in the MCST model we show that the core of the induced cost game in the MCCN model can be empty (without introducing Steiner nodes). We therefore consider sufficient conditions for non-empty core. Theorem 1 shows that when the efficient network and the demand graph consist of the same components, the induced cost game has non-empty core. Theorem 2 shows that when the demand graph has at most two components the induced cost game has non-empty core.
    Keywords: Minimum Cost Connection Network; Minimum Cost Spanning Tree; Cost Sharing; Fair allocation; The core; Balanced games
    JEL: C70 C72 D71 D85
    Date: 2020–07
  7. By: Daske, Thomas
    Abstract: This study explores mechanism design for networks of interpersonal relationships. Agents' social (more or less altruistic or spiteful) preferences and private payoffs are all subject to asymmetric information. Remarkably, the asymmetry of information about agents' social preferences can be operationalized to satisfy agents' participation constraints. The main result is a constructive proof of the Coase theorem, in its typical mechanism-design interpretation, for networks of at least three agents: If endowments are sufficiently large, any such network can resolve any given allocation problem with an ex-post budget-balanced mechanism that is Bayesian incentive-compatible, interim individually rational, and ex-post Pareto-efficient. The endogenously derived solution concept is interpreted as gamification: Resolve the agents' allocation problem with an efficient social-preference robust mechanism; attract agents' participation by complementing this mechanism with a budget-balanced game that operates on their social preferences and provides them with a platform to live out their propensities to cooperate or compete.
    Keywords: mechanism design,social preferences,gamification,joyful games,Coase theorem
    JEL: C72 C78 D62 D82
    Date: 2020
  8. By: Richard Holden (UNSW Business School); Michael Keane (UNSW Business School); Matthew Lilley (Harvard University)
    Abstract: Using data on essentially every US Supreme Court decision since 1946, we estimate a model of peer effects on the Court. We consider both the impact of justice ideology and justice votes on the votes of their peers. To identify these peer effects we use two instruments that generate plausibly exogenous variation in the peer group itself, or in the votes of peers. The first instrument utilizes the fact that the composition of the Court varies from case to case due to recusals or absences for health reasons. The second utilizes the fact that many justices previously sat on Federal Circuit Courts. Those who served on the Circuit Courts for short (long) periods of time are empirically much more (less) likely to affirm decisions from their “home” court. We find large peer effects. Replacing a single justice with one who votes in a conservative direction 10 percentage points more frequently increases the probability that each other justice votes conservative by 1.6 percentage points. Further, a 10% increase in the probability that a given justice votes conservative leads to a 1.1 percentage point increase in the probability that each other justice votes conservative. This indirect effect increases the share of cases with a conservative outcome by 3.6 percentage points (excluding the direct effect of the new justice). In general, we find indirect effects are large relative to the direct mechanical effect of a justice’s own vote.
    Keywords: Supreme Court, Peer Effects, Recusal
    JEL: K00
    Date: 2020–08
  9. By: Jens Leth Hougaard (NYU-Shanghai, China; Department of Food and Resource Economics, University of Copenhagen); Mich Tvede (University of East Anglia)
    Abstract: We consider a connection networks model. Every agent has a demand in the form of pairs of locations she wants connected, and a willingness to pay for connectivity. A planner aims at implementing a welfare maximizing network and allocating the resulting cost, but information is asymmetric: agents are fully informed, the planner is ignorant. The options for full implementation in Nash and strong Nash equilibria are studied. We simplify strategy sets without changing the set of Nash implementable correspondences. We show the correspondence of consisting of welfare maximizing networks and individually rational cost allocations is implementable. We construct a minimal Nash implementable desirable solution in the set of upper hemi-continuous and Nash implementable solutions. It is not possible to implement solutions such a the Shapley value unless we settle for partial implementation.
    Keywords: Connection networks; Welfare maximization; Nash Implementation; Strong Nash Implementation
    JEL: C70 C72 D71 D85
    Date: 2020–07
  10. By: Ambrus, A.; Elliott, M.
    Abstract: This paper investigates stable and efficient networks in the context of risk-sharing, when it is costly to establish and maintain relationships that facilitate risk-sharing. We find a novel trade-off between efficiency and equality. The most stable efficient networks also generate the most inequality. The result extends to correlated income structures with individuals split into groups, such that incomes across groups are less correlated but these relationships are more costly. We find that more central agents have better incentives to form across-group links, reaffirming the efficiency benefits of having highly central agents and thus the efficiency inequality trade-off. Our results are robust to many extensions. In general, endogenously formed networks in the risk sharing context tend to exhibit highly asymmetric structures, and stark inequalities in consumption levels.
    Date: 2020–07–20
  11. By: Orea, Luis; Álvarez, Inmaculada C.
    Abstract: This chapter summarizes the empirical literature that uses a spatial analysis framework in production economics. This literature takes advantage of the spatial dimension of the data to capture the spillover effects of neighboring production units. In the first three sections, we outline standard spatial extensions of the neoclassical production models aiming to measure knowledge spillovers, the effect of network inputs and economies of agglomeration. The next three sections outline the literature that on one hand examines returns to scale and productivity growth from both internal and external inputs, and on the other hand summarize the spatial econometric techniques used in frontier analyses of firms’ production. The last section includes a set of final remarks regarding the application of spatial econometric techniques in production analyses.
    Date: 2019
  12. By: Manuel Munoz-Herrera; Jacob Dijkstra; Andreas Flache; Rafael Wittek (Division of Social Science)
    Abstract: We develop a model of strategic network formation in productive exchanges to analyze the consequences of an understudied but consequential form of heterogeneity: differences between actors in the form of their production functions. We also address how this interacts with resource heterogeneity. Some actors (e.g. start-up firms) may exhibit accelerating returns to investment in joint projects, while others (e.g. established firms) may face decelerating returns. We show that if there is a direct relation between acceleration and resources, actors form exchange networks segregated by type of production function. On the other hand, if there is an inverse relation between acceleration and resources, networks emerge allowing all types of actors to collaborate, especially high-resource decelerating actors with multiple low-resource accelerating actors.
    Date: 2019–10
  13. By: Mohammad Ghaderi
    Abstract: Complexity, resulting from interactions among many components, is a characterizing property of healthcare systems and related decisions. Such complexity scales up quickly in the face of pandemics, where multiple sources of uncertainty are involved and various contextual factors interacting with policy parameters yield outcome distribution. This paper presents a uni ed framework to assist and inform policy decisions in confronting pandemics. The general framework consists of a model of contagion that makes the policy- relevant variables explicit and exogenous, establishes links between them and the main features of the environment in which the policy is going to be implemented, and treats various sources of uncertainty at different layers of the system. At the macro level, special attention is devoted to the network structure, for which we provide a simple characterization based on two constructive factors. Our results show that by conditioning on these two factors, a large proportion of the stochasticity resulted from the inherent randomness in the network can be captured. Components of the model are synthesized in a broader agent-based model that enables accounting for heterogeneous individual-level attributes that collectively yield the macro-level outcomes. Using several stylized examples and a comprehensive controlled experiment, insights on the overall tendency of the complex system in terms of multidimensional outputs are derived across a range of scenarios and under various types of policy conditions.
    Keywords: Public health interventions, social contagion, random networks, social distancing, simulation
    JEL: C6 C54 C32 I1
    Date: 2020–06
  14. By: Barrett, Chris; Nourani, Vesall; Patacchini, Eleonora; Walker, Thomas
    Abstract: Inter-household transfers play a central role in village economies. Whether understood as informal insurance, credit, or social taxation, the dominant conceptual models used to explain transfers rest on a foundation of self-interested dynamic behavior. Using experimental data from households in rural Ghana, where we randomized private and publicly observable cash payouts repeated every other month for a year, we reject two core predictions of the dominant models. We then add impure altruism and social taxation to a model of limited commitment informal insurance networks. The data support this new model's predictions, including that unobservable income shocks may facilitate altruistic giving that better targets less-well-off individuals within one's network, and that too large a network can overwhelm even an altruistic agent, inducing her to cease giving.
    Date: 2019–11
    Abstract: This study investigates the long range dependence and correlation structures of some select stock markets. Using novel wavelet methods of long range dependence, we show presence of long memory in the stock returns of some emerging economies and the lack of it in developed markets of Europe and the United States. Moreover, we conduct a wavelet based fractal connectivity analysis, which is the first application in economics and financial studies, to segregate markets into fractally similar groups and find that developed markets have similar fractal structures. Similarly stock returns of emerging markets exhibiting long-memory tend to follow similar fractal structures. Furthermore, network analyses of fractal connectivity support our findings on market efficiency which has theoretical roots in both fractal and adaptive market hypothesis.
    Keywords: Long memory, Fractal connectivity, Wavelets, Hurst, Complex networks
    JEL: C13 C14 C22 C32 C38 G15
    Date: 2020–06–01
  16. By: Elliott, M.; Georg, C-P.; Hazell, J.
    Abstract: Banks face different but potentially correlated risks from outside the financial system. Financial connections can share these risks, but also create the means by which shocks can propagate. We examine this tradeoff in the context of a new stylised fact we present: German banks are more likely to have financial connections when they face more similar risks—potentially undermining the risk sharing role of financial connections and contributing to systemic risk. We find that such patterns are socially suboptimal, but can be explained by risk-shifting. Risk-shifting motivates banks to correlate their failures with their counterparties, even though it creates systemic risk.
    Keywords: financial networks, asset correlation, contagion
    JEL: G21 G11 D85
    Date: 2020–07–20
  17. By: Roman Horvath (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Opletalova 26, 110 00, Prague, Czech Republic)
    Abstract: We provide a new explanation for why central banks have become transparent over the last three decades. We apply recently developed social interaction panel regression models for the observational data, which allow the identification of peer effects. The identification is based on variations in the past monetary policy régime exogenously determined with respect to transparency. Previous literature has argued that domestic factors such as macroeconomic stability were behind the trend toward greater transparency. In contrast, our results indicate that transparency primarily increased because of a favorable global environment and, importantly, because of the peer effects among central bankers. Central bankers thus learned from each other's experiences regarding transparency. To our knowledge, our paper is the first econometric analysis of peer effects among public institutions or in the macroeconomic literature. Despite being the best available, existing data is still imperfect, and we therefore call for better data in the form of MNCs’ unconsolidated, public country-by-country reporting data.
    Keywords: peer effects, central banks, transparency
    JEL: C31 D83 E58
    Date: 2020–08

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