nep-net New Economics Papers
on Network Economics
Issue of 2022‒09‒12
eighteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Good peers, good apples? Peer effects in portfolio quality By Balakina, Olga; Bäckman, Claes; Hackethal, Andreas; Hanspal, Tobin; Lammer, Dominique Marcel
  2. The spatial determinants of innovation diffusion: Evidence from global shipping networks By César Ducruet; Hidekazu Itoh
  3. Factor Network Autoregressions By Matteo Barigozzi; Giuseppe Cavaliere; Graziano Moramarco
  4. Systemic-risk and evolutionary stable strategies in a financial network By Indrajit Saha; Veeraruna Kavitha
  5. Origins of International Factor Structures By Zhengyang Jiang; Robert J. Richmond
  6. Is there cross-fertilization in macroeconomics? . Version 2 By Muriel Dal-Pont Legrand; Martina Cioni; Eugenio Petrovich; Alberto Baccini
  7. Anatomy of a Stablecoin's failure: the Terra-Luna case By Antonio Briola; David Vidal-Tom\'as; Yuanrong Wang; Tomaso Aste
  8. Planning ride-sharing services with detour restrictions for spatially heterogeneous demand: A multi-zone queuing network approach By Yining Liu; Yanfeng Ouyang
  9. The propagation of worldwide sector-specific shocks By Elvira Prades; Javier Quintana
  10. The Export of Medium and High-Tech Products Manufactured in Europe By Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
  11. The Determinants of Lifelong Learning in Europe By Costantiello, Alberto; Laureti, Lucio; Leogrande, Angelo
  12. k-Means Clusterization and Machine Learning Prediction of European Most Cited Scientific Publications By Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
  13. The sociology of cartels By Haucap, Justus; Heldman, Christina
  14. Multinominal choice with social interactions: occupations in Victorian London By Guerra, José Alberto; Mohnen, Myra
  15. Information transmission between banks and the market for corporate control By Bittner, Christian; Fecht, Falko; Pala, Melissa; Saidi, Farzad
  16. Ireland: Financial Sector Assessment Program-Technical Note on Financial Interconnectedness of the Market-Based Finance Sector By International Monetary Fund
  17. When formal and informal networks promote agroecology: a case study of Martinique Island By Magali Aubert; Laurent Parrot; Paula Fernandès Ce; Eric Roux; Jean-Pierre Devin; Geoffroy Enjolras; Isabelle Jean-Baptiste
  18. How did COVID-19 shape co-creation?: Insights and policy lessons from international initiatives By Muthu de Silva; Nikolas Schmidt; Caroline Paunov; Orlagh Lavelle

  1. By: Balakina, Olga; Bäckman, Claes; Hackethal, Andreas; Hanspal, Tobin; Lammer, Dominique Marcel
    Abstract: Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
    Keywords: Household finance,investment decisions,investment behavior,peer effects,social networks
    JEL: D14 G11 G4
    Date: 2022
  2. By: César Ducruet (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique); Hidekazu Itoh (Kwansei Gakuin University)
    Abstract: Based on untapped shipping and urban data, this article compares the diffusion of steam and container shipping at the port city level and at the global scale between 1880 and 2008. A temporal and multi-layered network is constructed, including the pre-existing technologies of sailing and breakbulk. The goal is to check the differences a) between innovations and their predecessors and b) between innovations, from an urban network perspective. Main results show that despite certain differences, such as historical context, voyage length, speed of diffusion, and geographical spread, the two innovations share a large quantity of similarities. They both fostered port concentration, were boosted by city size and port connectivity, bypassed upstream port sites, and diverged gradually from older technologies. This research thus contributes to the literature on cities, networks, innovation, and maritime transport.
    Keywords: Containerization,Maritime transport,Port cities,Regional disparity,Spatial networks,Steam shipping,Technological change
    Date: 2022
  3. By: Matteo Barigozzi; Giuseppe Cavaliere; Graziano Moramarco
    Abstract: We propose a factor network autoregressive (FNAR) model for time series with complex network structures. The coefficients of the model reflect many different types of connections between economic agents ("multilayer network"), which are summarized into a smaller number of network matrices ("network factors") through a novel tensor-based principal component approach. We provide consistency results for the estimation of the factors and the coefficients of the FNAR. Our approach combines two different dimension-reduction techniques and can be applied to ultra-high dimensional datasets. In an empirical application, we use the FNAR to investigate the cross-country interdependence of GDP growth rates based on a variety of international trade and financial linkages. The model provides a rich characterization of macroeconomic network effects and exhibits good forecast performance compared to popular dimension-reduction methods.
    Date: 2022–08
  4. By: Indrajit Saha; Veeraruna Kavitha
    Abstract: We consider a financial network represented at any time instance by a random liability graph which evolves over time. The agents connect through credit instruments borrowed from each other or through direct lending, and these create the liability edges. These random edges are modified (locally) by the agents over time, as they learn from their experiences and (possibly imperfect) observations. The settlement of the liabilities of various agents at the end of the contract period (at any time instance) can be expressed as solutions of random fixed point equations. Our first step is to derive the solutions of these equations (asymptotically and one for each time instance), using a recent result on random fixed point equations. The agents, at any time instance, adopt one of the two available strategies, risky or risk-free investments, with an aim to maximize their returns. We aim to study the emerging strategies of such replicator dynamics that drives the financial network. We theoretically reduce the analysis of the complex system to that of an appropriate ordinary differential equation (ODE). Using the attractors of the resulting ODE we showed that the replicator dynamics converges to one of the two pure evolutionary stable strategies (all risky or all risk-free agents); one can have mixed limit only when the observations are imperfect. We verified our theoretical findings using exhaustive Monte Carlo simulations. We established that the dynamics avoid the emergence of the systemic-risk regime (where majority default).
    Date: 2022–06
  5. By: Zhengyang Jiang; Robert J. Richmond
    Abstract: We show that exchange rate correlations tend to be explained by the global trade network while consumption correlations tend to be explained by productivity correlations. Sharing common trade linkages with other countries increases exchange rate correlations beyond bilateral linkages. We explain these findings using a model of the global trade network with market segmentation. Interdependent global production generates international comovements, while market segmentation disconnects the drivers of exchange rate correlations from the drivers of consumption correlations. Moreover, we show that the trade network generates common factors found in exchange rates. Our findings offer a trade-based account of the origins of international comovements and shed light on important frictions in international markets.
    JEL: F31 G15
    Date: 2022–08
  6. By: Muriel Dal-Pont Legrand; Martina Cioni (University of Sienna); Eugenio Petrovich (University of Sienna); Alberto Baccini (University of Sienna)
    Abstract: This paper compares Dynamic Stochastic General Equilibrium (DSGE) and Macro Agent-Based Models (MABMs) by adopting mainly a distant reading perspective. A set of 2,299 papers is retrieved from Scopus by using keywords related to MABM and DSGE domains. The interactions between the two streams of DSGE and MABM literature are explored by considering a social axis (co-authorship network), and an intellectual axis (cited references and bibliographic coupling). The analysis gave results that are neither consistent with a unitary structure of macroeconomics, nor with a simple dichotomic structure of alternative paradigms and separated academics communities. Indeed, the co-authorship network shows that DSGE and MABM form fragmented communities still belonging to two different larger MABM and DSGE communities rather neatly separated. Collaboration insists mainly inside the smaller groups and inside each of the two larger DSGE and MABM communities. Moreover, the co-authorship network analysis does not show evidence of systematic collaboration between MABM and DSGE authors. From an intellectual point of view, data show that DSGE and MABM articles refer to two different sets of bibliographic references. When a measure of paper-similarity is adopted, it appears that DSGE literature is fragmented in 4 groups while the MABM articles are clustered together in a unique group. Hence, DSGE approach is less monolithic than at the time of the New Synthesis: indeed, a large and a growing literature has developed at the margins of the core DSGE approach which includes elements of heterogeneous agent modelling, social interactions, experiments, expectations formation, learning etc.. The analysis gave no evidence of cross-fertilization between DSGE and MABM literature whilst it rather suggests a totally dissymmetric influence of DSGE over MABM literature, i.e. only MABM modelers look at DSGE but not vice-versa. The paper questions the capacity of the current dominant approach to benefit from cross-fertilization.
    Keywords: Macroeconomics,DSGE,macro agent-based models,heterogeneity,New Synthesis,crossfertilization,hybrid models,co-authorship network,co-citation analysis,bibliographic coupling,paper similarity
    Date: 2022–07–01
  7. By: Antonio Briola; David Vidal-Tom\'as; Yuanrong Wang; Tomaso Aste
    Abstract: We quantitatively describe the main events that led to the Terra project's failure in May 2022. We first review, in a systematic way, news from heterogeneous social media sources; we discuss the fragility of the Terra project and its vicious dependence on the Anchor protocol. We hence identify the crash's trigger events, analysing hourly and transaction data for Bitcoin, Luna, and TerraUSD. Finally, using state-of-the-art techniques from network science, we study the evolution of dependency structures for 61 highly capitalised cryptocurrencies during the down-market and highlight the absence of herding behaviour.
    Date: 2022–07
  8. By: Yining Liu; Yanfeng Ouyang
    Abstract: This study presents a multi-zone queuing network model for steady-state ride-sharing operations that serve heterogeneous demand, and then builds upon this model to optimize the design of ride-sharing services. Spatial heterogeneity is addressed by partitioning the study region into a set of relatively homogeneous zones, and a set of criteria are imposed to avoid significant detours among matched passengers. A generalized multi-zone queuing network model is then developed to describe how vehicles' states transition within each zone and across neighboring zones, and how passengers are served by idle or partially occupied vehicles. A large system of equations is constructed based on the queuing network model to analytically evaluate steady-state system performance. Then, we formulate a constrained nonlinear program to optimize the design of ride-sharing services, such as zone-level vehicle deployment, vehicle routing paths, and vehicle rebalancing operations. A customized solution approach is also proposed to decompose and solve the optimization problem. The proposed model and solution approach are applied to a hypothetical case and a real-world Chicago case study, so as to demonstrate their applicability and to draw insights. These numerical examples not only reveal interesting insights on how ride-sharing services serve heterogeneous demand, but also highlight the importance of addressing demand heterogeneity when designing ride-sharing services.
    Date: 2022–08
  9. By: Elvira Prades (Banco de España); Javier Quintana (Banco de España)
    Abstract: This paper analyses the aggregate impact of industry-specific shocks and their propagation through global production networks. We focus on the case in which a common shock affects simultaneously the same industry across different countries. Thus, our analysis can be a useful tool for several policy-relevant scenarios, such as changes in environmental regulations or the implementation of new technologies. For that purpose, we highlight the importance of departing from standard linear models that assume unitary elasticities of substitution. We combine a theoretical framework of production networks with arbitrary elasticities of substitution (Baqaee & Farhi, 2019) and we make use of World Input-Output Database to account for international linkages. This setting illustrates how, in the presence of production input complementarities, the interaction between simultaneous shocks has significant non-linear effects on sectoral composition and aggregate output. The aggregate impact of negative (positive) shocks gets significantly amplified (mitigated) when they affect simultaneously industries with strong production linkages. Our results show that ignoring production complementarities leads to vastly underestimating the aggregate consequences of regulatory or technological shocks in industries like chemicals or vehicle manufacturing. In contrast, simultaneous shocks to services industries are well accounted for by standard measures.
    Keywords: input-output tables, networks, shock propagation
    JEL: F14 F15
    Date: 2022–03
  10. By: Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
    Abstract: In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.
    Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation
    JEL: O30 O31 O32 O33 O34
    Date: 2022–08–16
  11. By: Costantiello, Alberto; Laureti, Lucio; Leogrande, Angelo
    Abstract: The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.
    Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation.
    JEL: O30 O31 O32 O33 O34
    Date: 2022–08–07
  12. By: Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio
    Abstract: In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.
    Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation.
    JEL: O3 O30 O31 O32 O33
    Date: 2022–08–20
  13. By: Haucap, Justus; Heldman, Christina
    Abstract: Traditional economic theory of collusion assumed that cartels are inherently unstable, and yet some manage to operate for years or even decades. While the literature has presented several determinants of cartel stability, the vast majority focuses on firms as entities, even though cartels are typically formed between individuals who need to develop structures that allow them to establish trust and ensure cooperation. We analyze 15 German cartels, focusing on the individual participants, the communication and internal structures within the cartels as well as their breakup. Our results indicate that cartel members are highly homogeneous and often rely on existing networks within the industry. Most impressively, only two of the 156 individuals involved in these 15 cartels were female, suggesting that gender also plays a role for cartel formation. We further identify various forms of communication and divisions of responsibilities and show that leniency programs are a powerful tool in breaking up cartels. Based on these results we discuss implications for competition policy and further research.
    Keywords: Cartels,Collusion,Social Networks,Trust,Antitrust
    Date: 2022
  14. By: Guerra, José Alberto; Mohnen, Myra
    Abstract: We study the importance of social interactions on occupational choice in Victorian London using a multinomial choice model within an incomplete social network. Individuals form heterogeneous rational expectations about their peers’ behaviors, taking into account their characteristics and the strength of their ties. We show the conditions under which the endogenous, exogenous, and correlated effects can be identified and a unique equilibrium can be established, Using a novel data set, we proxy social groups by parish boundaries and strength of ties by geographic distances, Our results show the importance of the endogenous effects and reveal distinct effects by occupation.
    JEL: J1 N0
    Date: 2022–07–01
  15. By: Bittner, Christian; Fecht, Falko; Pala, Melissa; Saidi, Farzad
    Abstract: This paper provides evidence of deliberate private-information disclosure within banks' international business networks. Using supervisory trade-level data, we show that banks with closer ties to a target advisor in a takeover buy more stocks of the target firm prior to the deal announcement, enabling them to benefit from the positive announcement return. We do not find such effects for bank connections to acquirer advisors or for trades in acquirer stocks. Target advisors benefit from leaking information about takeover bids to connected banks, as it drives up the final offer price without compromising the probability of bid success.
    Keywords: bank networks,trading,information spillovers,mergers and acquisitions,syndicated lending
    JEL: G11 G15 G21 G24
    Date: 2022
  16. By: International Monetary Fund
    Abstract: This technical note1 investigates the interconnectedness between the market-based finance (MBF) sector in Ireland and the rest of the financial system, with a view to assessing potential financial stability risks. The MBF sector, the largest component of the financial system, totals over 14 times GDP and is comprised of the funds sector—both money-market (170 percent of GDP) and investment funds (850 percent of GDP)— as well as other financial institutions (OFIs), which comprise of special purpose entities (SPEs, 240 percent of GDP) and a catch-all category entitled “OFI residual” (160 percent of GDP). Chapter I provides an overview of the potential financial stability risks associated with the MBF sector, with a focus on the funds sector, and places it in its domestic and global context. Chapter II maps out the interlinkages between the non-banks, banks, and the real sector using network analysis to assess the strength and direction of interconnectedness. Chapter III delves into the balance sheet exposures of major categories of Irish funds, the largest component of the MBF sector, to further assess channels of risk transmission. The analysis focuses on a network of complex inter-sectoral financial relationships, based on a range of lending and borrowing instruments, and several findings emerge.
    Date: 2022–07–27
  17. By: Magali Aubert (UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Laurent Parrot (Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, UPR HORTSYS - Fonctionnement agroécologique et performances des systèmes de cultures horticoles - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement); Paula Fernandès Ce; Eric Roux (Ministère de l'agriculture, de l'agroalimentaire et de la forêt); Jean-Pierre Devin (DRAAF Bretagne - Direction Régionale de l'Alimentation, de l'Agriculture et de la Forêt de Bretagne, Service Régional de l'Information Statistique et Economique (SRISE) - DRAAF - Direction Régionale de l’Agriculture, de l’Alimentation et de la Forêt); Geoffroy Enjolras (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes); Isabelle Jean-Baptiste (Chambre d'Agriculture de la Martinique)
    Abstract: Martinique, a French island and overseas department, faces many environmental challenges including a humid tropical climate prone to the development of pests, the decline of its agricultural sector and a deterioration of its environment. Despite these constraints, Martinique has to meet both national and European environmental requirements. In order to understand the main drivers of agroecological transition on the island, our study considers the role of both formal and informal networks in addition to individual and structural characteristics of farms. Based on a representative database of Martinican farms, our study highlights two main results. First, the individual characteristics of farmers influence their productive practices, while the structural characteristics of their farms have no impact. For farmer-owners, a farm has a value in terms of transmission translating into a desire to protect soil quality and hence to implement agroecological principles. Second, networks play an important role in the implementation of more environmentally-friendly practices. In Martinique, the main drivers are informal networks as Martinican farmers observe at the neighbourhood level both positive and negative impacts of the implementation of alternative practices.
    Keywords: Agroecological transition,Formal and informal networks,Martinique
    Date: 2022
  18. By: Muthu de Silva (Birkbeck, University of London); Nikolas Schmidt (OECD); Caroline Paunov (OECD); Orlagh Lavelle (OECD)
    Abstract: Co-creation – the joint production of innovation between combinations of industry, research, government and civil society – was widely used to respond to COVID-19 challenges. This paper analyses 30 international co-creation initiatives that were implemented to address COVID-19 challenges. Evidence on these initiatives was gathered based on structured interviews with initiative leaders. Existing co-creation networks enabled the rapid emergence of new initiatives to address urgent needs, while digital technologies enabled establishing new – and, where necessary, socially distanced – collaborations. Aside from funding initiatives, governments engaged actively in co-creation by granting access to their networks, advising on initiative goals and offering support to improve quick delivery. The role of civil society was important as well, and the socially impactful nature of research and innovation was a motivating factor for engagement. Harnessing a similarly strong motivation is an important driver of effective future co-creation endeavours also to address the challenges of the green transition.
    Keywords: Civil Society, Digitalisation, Industry-science Linkages, Innovation
    JEL: O36 O38 I18
    Date: 2022–08–19

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