nep-net New Economics Papers
on Network Economics
Issue of 2020‒12‒07
twelve papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. On social networks that support learning By Itai Arieli; Fedor Sandomirskiy; Rann Smorodinsky
  2. An Economic Model of Health-vs-Wealth Prioritization During COVID-19: Optimal Lockdown, Network Centrality, and Segregation By Roland Pongou; Guy Tchuente; Jean-Baptiste Tondji
  3. Searching with Friends By Caria, Stefano; Franklin, Simon; Witte, Marc
  4. Text-Based Linkages and Local Risk Spillovers in the Equity Market By Ge, S.
  5. Collateralized networks By Ghamami, Samim; Glasserman, Paul; Young, Hobart
  6. Financial Constraints and propagation of shocks in production network By Banu Demir; Beata Javorcik; Tomasz K. Michalski; Evren Ors
  7. Common ownership in the US pharmaceutical industry: A network analysis By Albert Banal-Estanol; Melissa Newham; Jo Seldeslachts
  8. Causal motifs and existence of endogenous cascades in directed networks with application to company defaults By Irena Barja\v{s}i\'c; Hrvoje \v{S}tefan\v{c}i\'c; Vedrana Pribi\v{c}evi\'c; Vinko Zlati\'c
  9. Sequential Defaulting in Financial Networks By P\'al Andr\'as Papp; Roger Wattenhofer
  10. Own Motivation, Peer Motivation, and Educational Success By Bietenbeck, Jan
  12. Nowcasting business cycle turning points with stock networks and machine learning By Azqueta-Gavaldon, Andres; Hirschbühl, Dominik; Onorante, Luca; Saiz, Lorena

  1. By: Itai Arieli; Fedor Sandomirskiy; Rann Smorodinsky
    Abstract: It is well understood that the structure of a social network is critical to whether or not agents can aggregate information correctly. In this paper, we study social networks that support information aggregation when rational agents act sequentially and irrevocably. Whether or not information is aggregated depends, inter alia, on the order in which agents decide. Thus, to decouple the order and the topology, our model studies a random arrival order. Unlike the case of a fixed arrival order, in our model, the decision of an agent is unlikely to be affected by those who are far from him in the network. This observation allows us to identify a local learning requirement, a natural condition on the agent's neighborhood that guarantees that this agent makes the correct decision (with high probability) no matter how well other agents perform. Roughly speaking, the agent should belong to a multitude of mutually exclusive social circles. We illustrate the power of the local learning requirement by constructing a family of social networks that guarantee information aggregation despite that no agent is a social hub (in other words, there are no opinion leaders). Although the common wisdom of the social learning literature suggests that information aggregation is very fragile, another application of the local learning requirement demonstrates the existence of networks where learning prevails even if a substantial fraction of the agents are not involved in the learning process. On a technical level, the networks we construct rely on the theory of expander graphs, i.e., highly connected sparse graphs with a wide range of applications from pure mathematics to error-correcting codes.
    Date: 2020–11
  2. By: Roland Pongou; Guy Tchuente; Jean-Baptiste Tondji
    Abstract: We address the problem of ï¬ nding the optimal lockdown and reopening policy during a pandemic like COVID-19, for a social planner who prioritizes health over short-term wealth accumulation. Agents are connected through a fuzzy network of contacts, and the planner’s objective is to determine the policy that contains the spread of infection below a tolerable incidence level, and that maximizes the present discounted value of real income, in that order of priority. We show theoretically that the planner’s problem has a unique solution. The optimal policy depends both on the conï¬ guration of the contact network and the tolerated infection incidence. Using simulations, we apply these theoretical ï¬ ndings to: (i) quantify the tradeoff between the economic cost of the pandemic and the infection incidence allowed by the social planner, and show how this tradeoff depends on network conï¬ guration; (ii) understand the correlation between different measures of network centrality and individual lockdown probability, and derive implications for the optimal design of surveys on social distancing behavior and network structure; and (iii) analyze how segregation induces differential health and economic dynamics in minority and majority populations, also illustrating the crucial role of patient zero in these dynamics.
    Keywords: COVID-19, health-vs-wealth prioritization, economic cost, fuzzy networks, net-work centrality, segregation, patient zero, optimally targeted lockdown policy
    JEL: E61 H12 I18 J15 D85
    Date: 2020–11
  3. By: Caria, Stefano (University of Bristol); Franklin, Simon (Queen Mary, University of London); Witte, Marc (IZA)
    Abstract: We study how active labor market policies affect the exchange of information and support among jobseekers. Leveraging a unique social network survey in Ethiopia, we find that a randomized job-search assistance intervention reduces information sharing and support between treated jobseekers and their active job-search partners. Due to lower job-search support, untreated individuals search less and, suggestively, have worse employment outcomes. These results are explained by a model of networks where unemployed individuals form job-search partnerships to exploit the complementarities of job search. These partnerships are broken if policy creates inequality in the access to information about job vacancies.
    Keywords: job search, social networks, RCT, active labor market policies
    JEL: D85 L14 O12 J64 D8
    Date: 2020–11
  4. By: Ge, S.
    Abstract: This paper uses extensive text data to construct firms' links via which local shocks transmit. Using the novel text-based linkages, I estimate a heterogeneous spatial-temporal model which accommodates the contemporaneous and dynamic spillover effects at the same time. I document a considerable degree of local risk spillovers in the market plus sector hierarchical factor model residuals of S&P 500 stocks. The method is found to outperform various previously studied methods in terms of out-of-sample fit. Network analysis of the spatial-temporal model identifies the major systemic risk contributors and receivers, which are of particular interest to microprudential policies. From a macroprudential perspective, a rolling-window analysis reveals that the strength of local risk spillovers increases during periods of crisis, when, on the other hand, the market factor loses its importance.
    Keywords: Excess co-movement, weak and strong cross-sectional dependence, local risk spillovers, networks, textual analysis, big data, systemic risk, heterogeneous spatial auto-regressive model (HSAR)
    JEL: C33 C58 G10 G12
    Date: 2020–11–26
  5. By: Ghamami, Samim; Glasserman, Paul; Young, Hobart
    Abstract: This paper studies the spread of losses and defaults in financial networks with two interrelated features: collateral requirements and alternative contract termination rules. When collateral is committed to a firm’s counterparties, a solvent firm may default if it lacks sufficient liquid assets to meet its payment obligations. Collateral requirements can thus increase defaults and payment shortfalls. Moreover, one firm may benefit from the failure of another if the failure frees collateral committed by the surviving firm, giving it additional resources to make other payments. Contract termination at default may also improve the ability of other firms to meet their obligations through access to collateral. As a consequence of these features, the timing of payments and collateral liquidation must be carefully specified to establish the existence of payments that clear the network. Using this framework, we show that dedicated collateral may lead to more defaults than pooled collateral; we study the consequences of illiquid collateral for the spread of losses through fire sales; we compare networks with and without selective contract termination; and we analyze the impact of alternative resolution and bankruptcy stay rules that limit the seizure of collateral at default. Under an upper bound on derivatives leverage, full termination reduces payment shortfalls compared with selective termination.
    Keywords: contagion; OTC markets; financial regulation; network; fire sales; collateral; automatic stays for qualified financial contracts; forthcoming
    JEL: J50
    Date: 2020–11–03
  6. By: Banu Demir; Beata Javorcik; Tomasz K. Michalski; Evren Ors
    Abstract: This study finds that even small unexpected supply shocks propagate downstream through production networks and are amplified by firms with short-term financial constraints. The unexpected 2011 increase in the tax on imports purchased with foreign-sourced trade credit is examined using data capturing almost all Turkish supplier-customer links. The identification strategy exploits the heterogeneous impact of the shock on importers. The results indicate that this relatively minor, non-localized shock had a non-trivial economic impact on exposed firms and propagated downstream through affected suppliers. Additional empirical tests, motivated by a simple theory, demonstrate that low-liquidity firms amplified its transmission.
    Keywords: production networks; shock transmission; financing constraints; liquidity
    Date: 2020
  7. By: Albert Banal-Estanol; Melissa Newham; Jo Seldeslachts
    Abstract: We investigate patterns in common ownership networks between firms that are active in the US pharmaceutical industry for the period 2004-2014. Our main findings are that “brand firms” —i.e. firms that have R&D capabilities and launch new drugs—exhibit relatively dense common ownership networks with each other that further increase significantly in density over time, whereas the network of “generic firms” —i.e. firms that primarily specialize in developing and launching generic drugs— is much sparser and stays that way over the span of our sample. Finally, when considering the common ownership links between brands firms, on the one hand, and generic firms, on the other, we find that brand firms have become more connected to generic firms over time. We discuss the potential antitrust implications of these findings.
    Keywords: Common ownership networks, pharmaceutical companies, competition, innovation
    Date: 2020–11–16
  8. By: Irena Barja\v{s}i\'c; Hrvoje \v{S}tefan\v{c}i\'c; Vedrana Pribi\v{c}evi\'c; Vinko Zlati\'c
    Abstract: Motivated by detection of cascades of defaults in economy, we developed a detection framework for endogenous spreading based on causal motifs we define in this paper. We assume that vertex change of state can be triggered by endogenous or exogenous event, that underlying network is directed and that times when vertices changed their states are available. In addition to data of company defaults we use, we simulate cascades driven by different stochastic processes on different synthetic networks. We also extended an approximate master equation method to directed networks with temporal stamps in order to understand in which cases detection is possible. We show that some of the smallest motifs can robustly detect cascades.
    Date: 2020–11
  9. By: P\'al Andr\'as Papp; Roger Wattenhofer
    Abstract: We consider financial networks, where banks are connected by contracts such as debts or credit default swaps. We study the clearing problem in these systems: we want to know which banks end up in a default, and what portion of their liabilities can these defaulting banks fulfill. We analyze these networks in a sequential model where banks announce their default one at a time, and the system evolves in a step-by-step manner. We first consider the reversible model of these systems, where banks may return from a default. We show that the stabilization time in this model can heavily depend on the ordering of announcements. However, we also show that there are systems where for any choice of ordering, the process lasts for an exponential number of steps before an eventual stabilization. We also show that finding the ordering with the smallest (or largest) number of banks ending up in default is an NP-hard problem. Furthermore, we prove that defaulting early can be an advantageous strategy for banks in some cases, and in general, finding the best time for a default announcement is NP-hard. Finally, we discuss how changing some properties of this setting affects the stabilization time of the process, and then use these techniques to devise a monotone model of the systems, which ensures that every network stabilizes eventually.
    Date: 2020–11
  10. By: Bietenbeck, Jan (Lund University)
    Abstract: I study how motivation shapes own and peers' educational success. Using data from Project STAR, I find that academic motivation in early elementary school, as measured by a standardized psychological test, predicts contemporaneous and future test scores, high school GPA, and college-test taking over and above cognitive skills. Exploiting random assignment of students to classes, I find that exposure to motivated classmates causally affects contemporaneous reading achievement, a peer effect that operates over and above spillovers from classmates' past achievement and socio-demographic composition. However, peer motivation does not affect longer-term educational success, likely because it does not change own motivation.
    Keywords: motivation, personality, peer effects, Project STAR
    JEL: I21 J13 J24
    Date: 2020–11
  11. By: Alexandra P. Bocharova (National Research University Higher School of Economics)
    Abstract: State information policy becomes especially important in times of political crises. The government has not only to solve the problem efficiently, but also preserve its positive image for the audience to restore order, retain its legitimacy and prevent citizens from any harmful collective actions. Media as the main link between the state and the citizens become, thus, one of the main means to solve this political crisis. In this study, the author takes the case of Hong Kong protests in summer-fall 2019 as the example of how state media work in order to resolve the crisis. By creating the network of Chinese media with the SNA method, we analyze how government controls the main information flows and what role local prodemocratic Hong Kong newspapers play in the information network of China. The results of the study show the decisive role of state media in creating the information agenda around Hong Kong protests. Moreover, there is close interconnectivity between Hong Kong media and government newspapers and between Hong Kong media and foreign sources of information, which makes local newspapers an important bridge between Eastern and mainland Chinese political views.
    Keywords: SNA, information policy, crisis management, Chinese media, Hong Kong protests
    JEL: D85
    Date: 2020
  12. By: Azqueta-Gavaldon, Andres; Hirschbühl, Dominik; Onorante, Luca; Saiz, Lorena
    Abstract: We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through the economy and identify node positions (firms) whose connectedness provides a signal for economic growth. The nowcasting exercise, with both the in-sample and the out-of-sample consistent feature selection, highlights which firms are contemporaneously exposed to aggregate downturns and provides a more complete narrative than is usually provided by more aggregate data. The two-state model for predicting periods of negative growth can remarkably well predict future states by using information derived from the node-positions of manufacturing, transportation and financial (particularly insurance) firms. The three-states model, which identifies high, low and negative growth, successfully predicts economic regimes by making use of information from the financial, insurance, and retail sectors. JEL Classification: C45, C51, D85, E32, N1
    Keywords: early warning signal, Granger-causality networks, real-time, turning point prediction
    Date: 2020–11

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