nep-net New Economics Papers
on Network Economics
Issue of 2023‒07‒17
eight papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Layered networks, equilibrium dynamics, and stable coalitions By Fu, Jing; Page, Frank; Zigrand, Jean-Pierre
  2. The Matching Function: A Unified Look into the Black Box By Georgios Angelis; Yann Bramoullé
  3. Testing for Peer Effects without Specifying the Network Structure By Hyunseok Jung; Xiaodong Liu
  4. Structural Change in Production Networks and Economic Growth By Paul Gaggl; Aspen Gorry; Christian vom Lehn
  5. Quantifying Hierarchy and Prestige in US Ballet Academies as Social Predictors of Career Success By Herrera-Guzmán, Yessica; Gates, Alexander; Candia, Cristian; Barabasi, Albert Laszlo
  6. Identifying key players in dark web marketplaces By Elohim Fonseca dos Reis; Alexander Teytelboym; Abeer ElBahraw; Ignacio De Loizaga; Andrea Baronchelli
  7. Quantitative Impact Analysis of the Centralization of Firms in the Tokyo Metropolitan Area Considering Firm-to-Firm Trade Networks By Kono, Tatsuhito; Nakajima, Kentaro; Ozane, Kanta
  8. Centrality in Production Networks and International Technology Diffusion By Rinki Ito

  1. By: Fu, Jing; Page, Frank; Zigrand, Jean-Pierre
    Abstract: An important aspect of network dynamics that has been missing from our understanding of network dynamics in various applied settings is the influence of strategic behavior in determining equilibrium network dynamics. Our main objective hear to say what we can regarding the emergence of stable club networks - and therefore, stable coalition structures - based on the stability properties of strategically determined equilibrium network formation dynamics. Because club networks are layered networks, our work here can be thought of as a first work on the dynamics of layered networks. In addition to constructing a discounted stochastic game model (i.e., a DSG model) of club network formation, we show that (1) our DSG of network formation possesses a stationary Markov perfect equilibrium in players' membership action strategies and (2) we identify the assumptions on primitives which ensure that the induced equilibrium Markov process of layered club network formation satisfies the Tweedie Stability Conditions (2001) and that (3) as a consequence, the equilibrium Markov network formation processes generates a unique decomposition of the set of state-network pairs into a transient set together with finitely many basins of attraction. Moreover, we show that if there is a basin containing a vio set (a visited infinitely often set) of club networks sufficiently close together, then the coalition structures across club networks in the vio set will be the same (i.e., closeness across networks in a vio set leads to invariance in coalition structure across networks in a vio set).
    Keywords: club networks; stable coalition structures; networks as partial functions; Harris recurrent sets; basins of attraction; discounted stochastic games; stationary Markov perfect equilibria; equilibrium
    JEL: C70
    Date: 2022–03–25
  2. By: Georgios Angelis (Bocconi University, IGIER); Yann Bramoullé (Aix Marseille Univ, CNRS, AMSE, Marseille, France.)
    Abstract: In this paper, we use tools from network theory to trace the properties of the matching function to the structure of granular connections between applicants and firms. We link seemingly disparate parts of the literature and recover existing functional forms as special cases. Our overarching message is that structure counts. For rich structures, captured by non-random networks, the matching function depends on whole sets rather than just the sizes of the two sides of the market. For less rich-random network-structures it depends on the sizes of the two sides and a few structural parameters. Structures characterized by greater asymmetries reduce the matching function's efficacy, while denser structures can have ambiguous effects on it. For the special case of the Erdös-Rényi network, we show that the way the network varies with the sizes of the two sides of the market determines if the matching function exhibits constant returns to scale, or even if it is of a specific functional form, such as CES.
    Date: 2023–06
  3. By: Hyunseok Jung; Xiaodong Liu
    Abstract: This paper proposes an Anderson-Rubin (AR) test for the presence of peer effects in panel data without the need to specify the network structure. The unrestricted model of our test is a linear panel data model of social interactions with dyad-specific peer effects. The proposed AR test evaluates if the peer effect coefficients are all zero. As the number of peer effect coefficients increases with the sample size, so does the number of instrumental variables (IVs) employed to estimate the unrestricted model, rendering Bekker's many-IV environment. By extending existing many-IV asymptotic results to panel data, we show that the proposed AR test is asymptotically valid under the presence of both individual and time fixed effects. We conduct Monte Carlo simulations to investigate the finite sample performance of the AR test and provide two applications to demonstrate its empirical relevance.
    Date: 2023–06
  4. By: Paul Gaggl; Aspen Gorry; Christian vom Lehn
    Abstract: This paper studies structural change in production networks for intermediate inputs (input-output network) and new capital (investment network). For each network, we document a declining fraction of production by goods sectors and a rising fraction of production by services sectors. We develop a multisector growth model that admits structural change in production networks along the balanced growth path to study these trends. Disaggregated final expenditure data reveal that inputs to investment production are substitutes, rather than strong complements as suggested by existing work. Hence, resources endogenously reallocate toward the fastest growing producers of investment. Growth accounting exercises demonstrate that investment-specific technical change has risen in importance for aggregate U.S. growth over time, with 20-25% of aggregate growth after 2000 stemming from reallocation induced by structural change. At the same time, productivity growth within the input-output network has stagnated, contributing to the recent slowdown in aggregate growth.
    Keywords: structural change, input-output network, investment network, economic growth, technical change, balanced growth
    JEL: E23 O14 O40 O41
    Date: 2023
  5. By: Herrera-Guzmán, Yessica; Gates, Alexander; Candia, Cristian; Barabasi, Albert Laszlo
    Abstract: In the recent decade, we have seen major progress in quantifying the behaviors and the impact of scientists, resulting in a quantitative toolset capable of monitoring and predicting the career patterns of the profession. It is unclear, however, if this toolset applies to other creative domains beyond the sciences. In particular, while performance in the arts has long been difficult to quantify objectively, research suggests that professional networks and prestige of affiliations play a similar role to those observed in science, hence they can reveal patterns underlying successful careers. To test this hypothesis, here we focus on ballet, as it allows us to investigate in a quantitative fashion the interplay of individual performance, institutional prestige, and network effects. We analyze data on competition outcomes from 6, 363 ballet students affiliated with 1, 603 schools in the United States, who participated in the Youth America Grand Prix (YAGP) between 2000 and 2021. Through multiple logit models and matching experiments, we provide evidence that schools' strategic network position bridging between communities captures social prestige and predicts the placement of students into jobs in ballet companies. This work reveals the importance of institutional prestige on career success in ballet and showcases the potential of network science approaches to provide quantitative viewpoints for the professional development of careers beyond science.
    Date: 2023–06–17
  6. By: Elohim Fonseca dos Reis; Alexander Teytelboym; Abeer ElBahraw; Ignacio De Loizaga; Andrea Baronchelli
    Abstract: Dark web marketplaces have been a significant outlet for illicit trade, serving millions of users worldwide for over a decade. However, not all users are the same. This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets and assess their role by analysing a dataset of 40 million Bitcoin transactions involving 31 markets in the period 2011-2021. First, we propose an algorithm that categorizes users either as buyers or sellers and shows that a large fraction of the traded volume is concentrated in a small group of elite market participants. Then, we investigate both market star-graphs and user-to-user networks and highlight the importance of a new class of users, namely `multihomers' who operate on multiple marketplaces concurrently. Specifically, we show how the networks of multihomers and seller-to-seller interactions can shed light on the resilience of the dark market ecosystem against external shocks. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities.
    Date: 2023–06
  7. By: Kono, Tatsuhito; Nakajima, Kentaro; Ozane, Kanta
    Abstract: When a firm makes a location decision, it considers only its own transportation costs and ignores the transportation costs of its trading partners, resulting in inefficient sparce locations of firms. Since Beckmann (1976), it has been known that such inefficient sparse locations occur in the canonical land use models with interactions between agents, and this externality is referred to as locational externality by Kanamoto (1990). We quantitatively analyze the scale of locational externalities using micro data of the listed firms located in the Tokyo metropolitan area and firm-to-firm trade network data. We show (1) which trade patterns involve locational externalities, (2) the ratio of trade generating locational externalities as a percentage of total trade is about 24%, (3) the transfer of a randomly-chosen 5% of firms to two business centers, Marunouchi and Shibuya, generates median external benefits of 1.9% and 1.3% in the total industry in terms of value-added, respectively, (4) benefits vary according to industry and location (e.g., about 10% in the case of firms located far from the centers, and about 5% in the case of firms in the information and communications industry).
    Keywords: locational externalities; productivity; trade network
    JEL: L1 L14 R30
    Date: 2023–06
  8. By: Rinki Ito
    Abstract: This study examines whether the structure of global value chains (GVCs) affects international spillovers of research and development (R&D). Although the presence of ``hub'' countries in GVCs has been confirmed by previous studies, the role of these hub countries in the diffusion of the technology has not been analyzed. Using a sample of 21 countries and 14 manufacturing industries during the period 1995-2007, I explore the role of hubs as the mediator of knowledge by classifying countries and industries based on a ``centrality'' measure. I find that R&D spillovers from exporters with High centrality are the largest, suggesting that hub countries play an important role in both gathering and diffusing knowledge. I also find that countries with Middle centrality are getting important in the diffusion of knowledge. Finally, positive spillover effects from own are observed only in the G5 countries.
    Date: 2023–06

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