nep-net New Economics Papers
on Network Economics
Issue of 2023‒01‒16
fifteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Business transactions and ownership ties between firms By László Lõrincz; Sándor Juhász; Rebeka O. Szabó
  2. Estimating Social Network Models with Missing Links By Arthur Lewbel; Xi Qu; Xun Tang
  3. Fire Sales and Ex Ante Valuation of Systemic Risk: A Financial Equilibrium Networks Approach By Spiros Bougheas; Adam Hal Spencer
  4. The network structure of global tax evasion Evidence from the Panama Papers By Garcia Alvarado Fernando; Mandel Antoine
  5. Diffusion in large networks By Michel Grabisch; Agnieszka Rusinowska; Xavier Venel
  6. On the design of public debate in social networks Michel Grabisch (a)(b) , Antoine Mandel (a)(b) * , Agnieszka Rusinowska (a)(c) By Michel Grabisch; Antoine Mandel; Agnieszka Rusinowska
  7. Blockchain Network Analysis: A Comparative Study of Decentralized Banks By Yufan Zhang; Zichao Chen; Yutong Sun; Yulin Liu; Luyao Zhang
  8. Peer Effects in Academic Research: Senders and Receivers By Clément Bosquet; Pierre-Philippe Combes; Emeric Henry; Thierry Mayer
  9. Firm-level Study on the Global Connection through Stock Ownership Relations By KICHIKAWA Yuichi; IINO Takahiro; IKEDA Yuichi; IYETOMI Hiroshi
  10. Financial Connectedness and Risk Transmission Among MENA Countries: Evidence from Connectedness Network and Clustering Analysis By Mehmet Balcilar; Shawkat Hammoudeh
  11. Community Networks and Trade By Böken, Johannes; Gadenne, Lucie; Nandi, Tushar; Santamaria, Marta
  12. Estimating Time-Varying Networks for High-Dimensional Time Series By Chen, J.; Li, D.; Li, Y.; Linton, O. B.
  13. Consensus formation in nonprofit and philanthropic studies: Networks, reputation, and gender By Ma, Ji; Bekkers, Rene
  14. NETpred: Network-based modeling and prediction of multiple connected market indices By Alireza Jafari; Saman Haratizadeh
  15. Fitness in the light of Sinkhorn By Dario Mazzilli; Manuel Sebastian Mariani; Flaviano Morone; Aurelio Patelli

  1. By: László Lõrincz (Centre for Economic and Regional Studies, Corvinus University of Budapest, Corvinus Institute for Advanced Studies); Sándor Juhász (Corvinus University of Budapest, Corvinus Institute for Advanced Studies, Centre for Economic and Regional Studies); Rebeka O. Szabó (Corvinus University of Budapest, Corvinus Institute for Advanced Studies)
    Abstract: In this study we investigate the creation and persistence of interfirm ties in a large-scale business transaction network. Transaction ties, firms buying or selling products or services can be the outcome of pure business motivations, but the social connections of owners or the geographical location of companies may also influence their development. We build the transaction and the ownership networks of firms in Hungary for 2016 and 2017 from two administrative datasets and identify multi-layer network motifs to predict the creation and persistence of business transactions. We show that direct or indirect relationships in this two-layered network contribute to both the creation and persistence of business transaction ties. We find a positive, but smaller impact of geographic proximity and industrial similarity of firms. For our estimations, we utilize loglinear models and emphasize their efficiency in predicting links in such large networks. We contribute to the literature by illustrating business connection patterns in a nationwide multilayer interfirm network.
    Keywords: transaction network, ownership network, multilayer network, network motifs, tie creation, tie persistence
    JEL: L14
    Date: 2022–06
  2. By: Arthur Lewbel (Boston College); Xi Qu (Shanghai Jiao Tong University); Xun Tang (Rice University)
    Abstract: We propose an adjusted 2SLS estimator for social network models when some existing network links are missing from the sample (due, e.g., to recall errors by survey respondents, or lapses in data input). In the feasible structural form, missing links make all covariates endogenous and add a new source of correlation between the structural errors and endogenous peer outcomes (in addition to simultaneity), thus invalidating conventional estimators used in the literature. We resolve these issues by rescaling peer outcomes with estimates of missing rates and constructing instruments that exploit properties of the noisy network measures. We apply our method to study peer effects in household decisions to participate in a microfinance program in Indian villages. We find that ignoring missing links and applying conventional instruments would result in a sizeable upward bias in peer effect estimates.
    Keywords: social networks, 2SLS, missing links
    Date: 2022–12–20
  3. By: Spiros Bougheas; Adam Hal Spencer
    Abstract: We introduce endogenous fire sales into a simple network model. For any given initial distribution of shocks across the network, we develop a clearing algorithm to solve for the financial equilibrium. We then utilise the results to perform ex ante risk assessment and derive risk premia for every balance sheet item where liabilities are differentiated according to priority rights. We find that risk premia reflect both idiosyncratic risk and risk of contagion (network risk). Moreover, we show that network risk magnifies the gap between the risk premia of equity and debt. We also perform comparative statics, showing that changes to the distribution of shocks and network structure can have substantial effects on the level of systemic losses.
    Keywords: networks, fire sales, systemic risk premia, risk assessment
    JEL: G33 G32 D85
    Date: 2022
  4. By: Garcia Alvarado Fernando; Mandel Antoine (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper builds on recent insights from network theory and on the rich dataset made available by the Panama Papers in order to investigate the micro-economic dynamics of tax-evasion. We model offshore financial entities documented in the Panama Papers as links between jurisdictions in the global network of tax evasion. A quantitative analysis shows that the resulting network, far from being a random collection of bilateral links, has key features of complex networks such as a core-periphery structure and a fat-tail degree distribution. We argue that these structural features imply that policy must adopt a systemic perspective to mitigate tax evasion. We offer three sets of insights from this perspective. First, we identify through centrality measures tax havens that ought to be priority policy targets. Second, we show that efficient tax treaties must contain exchange information clauses and link tax-havens to non-haven jurisdictions. Third, we show that the optimal deterrence strategies for a social-planner facing a strategic tax-evader in a Stackelberg competition can be characterized using the notion of Bonacich centrality.
    Keywords: H26 H87 D85 C54 Tax Evasion Socio-economic Networks Game Theory,H26,H87,D85,C54 Tax Evasion,Socio-economic Networks,Game Theory
    Date: 2022–05
  5. By: Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Agnieszka Rusinowska; Xavier Venel
    Abstract: We investigate the phenomenon of diffusion in a countably infinite society of individuals interacting with their neighbors in a network. At a given time, each individual is either active or inactive. The diffusion is driven by two characteristics: the network structure and the diffusion mechanism represented by an aggregation function. We distinguish between two diffusion mechanisms (probabilistic, deterministic) and focus on two types of aggregation functions (strict, Boolean). Under strict aggregation functions, polarization of the society cannot happen, and its state evolves towards a mixture of infinitely many active and infinitely many inactive agents, or towards a homogeneous society. Under Boolean aggregation functions, the diffusion process becomes deterministic and the contagion model of Morris (2000) becomes a particular case of our framework. Polarization can then happen. Our dynamics also allows for cycles in both cases. The network structure is not relevant for these questions, but is important for establishing irreducibility, at the price of a richness assumption: the network should contain at least one complex star and have enough space for storing local configurations. Our model can be given a game-theoretic interpretation via a local coordination game, where each player would apply a best-response strategy in a random neighborhood.
    Keywords: diffusion, countable network, aggregation function, polarization, convergence, bestresponse
    Date: 2022
  6. By: Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Antoine Mandel; Agnieszka Rusinowska
    Abstract: We propose a model of the joint evolution of opinions and social relationships in a setting where social influence decays over time. The dynamics are based on bounded confidence: social connections between individuals with distant opinions are severed while new connections are formed between individuals with similar opinions. Our model naturally gives raise to strong diversity, i.e., the persistence of heterogeneous opinions in connected societies, a phenomenon that most existing models fail to capture. The intensity of social interactions is the key parameter that governs the dynamics. First, it determines the asymptotic distribution of opinions. In particular, increasing the intensity of social interactions brings society closer to consensus. Second, it determines the risk of polarization, which is shown to increase with the intensity of social interactions. Our results allow to frame the problem of the design of public debates in a formal setting. We hence characterize the optimal strategy for a social planner who controls the intensity of the public debate and thus faces a trade-off between the pursuit of social consensus and the risk of polarization. We also consider applications to political campaigning and show that both minority and majority candidates can have incentives to lead society towards polarization.
    Keywords: opinion dynamics, network formation, network fragility, polarization, institution design, political campaign
    Date: 2022
  7. By: Yufan Zhang; Zichao Chen; Yutong Sun; Yulin Liu; Luyao Zhang
    Abstract: Decentralized finance (DeFi) is known for its unique mechanism design, which applies smart contracts to facilitate peer-to-peer transactions. The decentralized bank is a typical DeFi application. Ideally, a decentralized bank should be decentralized in the transaction. However, many recent studies have found that decentralized banks have not achieved a significant degree of decentralization. This research conducts a comparative study among mainstream decentralized banks. We apply core-periphery network features analysis using the transaction data from four decentralized banks, Liquity, Aave, MakerDao, and Compound. We extract six features and compare the banks' levels of decentralization cross-sectionally. According to the analysis results, we find that: 1) MakerDao and Compound are more decentralized in the transactions than Aave and Liquity. 2) Although decentralized banking transactions are supposed to be decentralized, the data show that four banks have primary external transaction core addresses such as Huobi, Coinbase, Binance, etc. We also discuss four design features that might affect network decentralization. Our research contributes to the literature at the interface of decentralized finance, financial technology (Fintech), and social network analysis and inspires future protocol designs to live up to the promise of decentralized finance for a truly peer-to-peer transaction network.
    Date: 2022–12
  8. By: Clément Bosquet (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Pierre-Philippe Combes (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR); Emeric Henry (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR); Thierry Mayer (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR)
    Abstract: Using an instrument based on a national contest in France determining researchers' location, we find evidence of peer effects in academia, when focusing on precise groups of senders (producing the spillovers) and receivers (benefiting from the spillovers), defined based on field of specialisation, gender and age. These peer effects are present even outside formal co-authorship relationships. Furthermore, the match between the characteristics of senders and receivers plays a critical role. In particular, men benefit a lot from peer effects provided by other men, while all other types of gender combinations produce spillovers twice as small. Part of the peer effects results from researchers switching research fields.
    Keywords: Economics of science, Peer effects, Research productivity, Gender publication gap
    Date: 2022–11
  9. By: KICHIKAWA Yuichi; IINO Takahiro; IKEDA Yuichi; IYETOMI Hiroshi
    Abstract: The progress of globalization has made economic relations around the world ever more complex, including stock ownership. Here we analyze the Global Equity Ownership database compiled by Thomson Reuters Corporation for the period from 1997 to 2020, currently known as the Refinitiv Ownership and Profiles database. The comprehensive database enables us to construct a stock ownership network for every year that classifies firms and shareholders as nodes and stock ownership relationships as directed links. By adopting network-theoretic methods, we elucidate how firms and investors are connected globally through their stock ownership relations. We pay special attention to the role of Japan in the network. We find that the Japanese firms are discriminated from those in the other countries by strong correlation between their in-degree and out-degree. Such peculiarity in the node properties leads to a loosely coupled cluster constituted dominantly by most Japanese firms with multilateral cross shareholdings. This fact is confirmed by the theory for random directed networks and by randomization simulations. We also address the current issue of publicly listed parent/subsidiary pairs of firms by simulating what would happen to the cooperative ownership structure in Japan if those pairs of firms are combined into one.
    Date: 2022–12
  10. By: Mehmet Balcilar (Eastern Mediterranean UniversityAuthor-Name: Ahmed Elsayed; Zagazig University); Shawkat Hammoudeh (University of Economics HCMC)
    Abstract: This study examines the financial connectedness and risk transmission among MENA economies by accounting for financial connectedness in the short and long run as well dependency under extreme market conditions and network graph analysis. To this end, Composite Financial Stress Indices are constructed for 11 MENA countries. In addition, a battery of econometric models is applied including the standard spillover approach, the frequency domain method, the quantile connectedness technique, and connectedness networks analysis. Using daily data over the period from June 30, 2006 to June 30, 2021, the empirical results show a positive and strong association between financial stress co-movements and spillovers in those MENA countries, particularly during the long run and high extreme stress periods. Furthermore, the five Gulf countries are strongly financially connected among themselves than with the other countries. Contrary, to Tunisia, Saudi Arabia is the main financial stress and risk transmitter to other MENA economies whereas, the North African countries are relatively mild receivers of risk. Finally, the more open countries in terms of capital controls, particularly Kuwait, Oman, Qatar, and UAE seem to play a more central role in financial connectedness and risk spillovers
    Date: 2022–11–20
  11. By: Böken, Johannes (University of Warwick); Gadenne, Lucie (Queen Mary University of London, Institute for Fiscal Studies and CEPR); Nandi, Tushar (IISER Kolkata); Santamaria, Marta (University of Warwick)
    Abstract: Do community networks shape firm-to-firm trade in emerging economies? We study the role of communities in facilitating firm-to-firm trade and firm outcomes using data on firm-to-firm transactions and firm owners’ community (castes) affiliations for the universe of medium- and large- sized firms in West Bengal, India. We find that firms are substantially more likely to trade, and trade more, with firms from their own caste. Studying the mechanisms underlying this effect, we find evidence consistent both with castes alleviating trade frictions and taste-based discrimination by firms against those outside their community. Guided by these stylized facts, we develop a model of firm to-firm trade in which communities affect pair productivity and matching costs and estimate the model using our reduced-form estimates. A counterfactual extending the positive effects of castes on trade to all potential supplier-client pairs would increase the number of network links by 60% and increase average firm-to-firm sales by 20%.
    Keywords: JEL Codes:
    Date: 2022
  12. By: Chen, J.; Li, D.; Li, Y.; Linton, O. B.
    Abstract: We explore time-varying networks for high-dimensional locally stationary time series, using the large VAR model framework with both the transition and (error) precision matrices evolving smoothly over time. Two types of time-varying graphs are investigated: one containing directed edges of Granger causality linkages, and the other containing undirected edges of partial correlation linkages. Under the sparse structural assumption, we propose a penalised local linear method with time-varying weighted group LASSO to jointly estimate the transition matrices and identify their significant entries, and a time-varying CLIME method to estimate the precision matrices. The estimated transition and precision matrices are then used to determine the time-varying network structures. Under some mild conditions, we derive the theoretical properties of the proposed estimates including the consistency and oracle properties. In addition, we extend the methodology and theory to cover highly-correlated large-scale time series, for which the sparsity assumption becomes invalid and we allow for common factors before estimating the factor-adjusted time-varying networks. We provide extensive simulation studies and an empirical application to a large U.S. macroeconomic dataset to illustrate the finite-sample performance of our methods.
    Keywords: CLIME, Factor model, Granger causality, lasso, local linear smoothing, partial correlation, time-varying network, VAR
    JEL: C13 C14 C32 C38
    Date: 2022–12–14
  13. By: Ma, Ji (The University of Texas at Austin); Bekkers, Rene (VU Amsterdam)
    Abstract: The research field of nonprofits and philanthropy has grown exponentially. To what extent do nonprofit scholars share a common language? Answering this question is crucial to assessing the field's intellectual cohesiveness. We studied how coauthor networks, scholarly reputation, and the prevalence of female authors influence consensus formation. We found that the degree of consensus for all major research topics in the field has increased over time---for every 10% growth in the volume of literature, shared language increased by 1.4%. A cohesive research community on nonprofits and philanthropy has been forming since the early 2000s. Female scholars are fewer in number and less cited than males; their presence did not exceeded 40% for most topics. The citation counts of scholars and small-world property of networks are positively associated with consensus, suggesting that star researchers and knowledge brokers bridging different intellectual communities are key to sharing research interests and language.
    Date: 2022–12–07
  14. By: Alireza Jafari; Saman Haratizadeh
    Abstract: Market prediction plays a major role in supporting financial decisions. An emerging approach in this domain is to use graphical modeling and analysis to for prediction of next market index fluctuations. One important question in this domain is how to construct an appropriate graphical model of the data that can be effectively used by a semi-supervised GNN to predict index fluctuations. In this paper, we introduce a framework called NETpred that generates a novel heterogeneous graph representing multiple related indices and their stocks by using several stock-stock and stock-index relation measures. It then thoroughly selects a diverse set of representative nodes that cover different parts of the state space and whose price movements are accurately predictable. By assigning initial predicted labels to such a set of nodes, NETpred makes sure that the subsequent GCN model can be successfully trained using a semi-supervised learning process. The resulting model is then used to predict the stock labels which are finally aggregated to infer the labels for all the index nodes in the graph. Our comprehensive set of experiments shows that NETpred improves the performance of the state-of-the-art baselines by 3%-5% in terms of F-score measure on different well-known data sets.
    Date: 2022–12
  15. By: Dario Mazzilli; Manuel Sebastian Mariani; Flaviano Morone; Aurelio Patelli
    Abstract: We uncover the connection between the Fitness-Complexity algorithm, developed in the economic complexity field, and the Sinkhorn-Knopp algorithm, widely used in diverse domains ranging from computer science and mathematics to economics. Despite minor formal differences between the two methods, both converge to the same fixed-point solution up to normalization. The discovered connection allows us to derive a rigorous interpretation of the Fitness and the Complexity metrics as the potentials of a suitable energy function. Under this interpretation, high-energy products are unfeasible for low-fitness countries, which explains why the algorithm is effective at displaying nested patterns in bipartite networks. We also show that the proposed interpretation reveals the scale invariance of the Fitness-Complexity algorithm, which has practical implications for the algorithm's implementation in different datasets. Further, analysis of empirical trade data under the new perspective reveals three categories of countries that might benefit from different development strategies.
    Date: 2022–12

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