nep-net New Economics Papers
on Network Economics
Issue of 2022‒06‒13
seven papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Topology-dependence of propagation mechanisms in the production network By Eszter Moln\'ar; D\'enes Csala
  2. A Dynamic Analysis of Criminal Networks By Luca Colombo; Paola Labrecciosa; Agnieszka Rusinowska
  3. Organizing Crime: an Empirical Analysis of the Sicilian Mafia By Michele Battisti; Andrea Mario Lavezzi; Roberto Musotto
  4. Control of Dynamic Financial Networks (The Extended Version) By Giuseppe Calafiore; Giulia Fracastoro; Anton V. Proskurnikov
  5. Trade persistence and trader identity - evidence from the demise of the Hanseatic League By Max Marczinek; Stephan E. Maurer; Ferdinand Rauch
  6. A Tale of Two Networks: Common Ownership and Product Market Rivalry By Florian Ederer; Bruno Pellegrino
  7. Cross-Sector Interactions in Western Europe: Lessons From Trade Credit Data By Melina London

  1. By: Eszter Moln\'ar; D\'enes Csala
    Abstract: The topology of production networks determines the propagation mechanisms of local shocks and thus the co-movement of industries. As a result, we need a more precisely defined production network to model economic growth accurately. In this study, we analyse Leontief's input-output model from a network theory perspective, aiming to construct a production network in such a way that it allows the most accurate modelling of the propagation mechanisms of changes that generate industry growth. We do this by revisiting a prevalent threshold in the literature that determines industry-industry interdependence. Our hypothesis is that changing the threshold changes the topological structure of the network and the core industries to a large extent. This is significant, because if the production network topology is not precisely defined, the resulting internal propagation mechanisms will be distorted, and thus industry growth modelling will not be accurate. We prove our hypothesis by examining the network topology, and centrality metrics under different thresholds on a network derived from the US input-output accounts data for 2007 and 2012.
    Date: 2022–05
  2. By: Luca Colombo (Deakin Business School - Department of Economics, Australia); Paola Labrecciosa (Monash Business School - Department of Economics, Australia); Agnieszka Rusinowska (CNRS, Paris School of Economics, Centre d'Economie de la Sorbonne)
    Abstract: The paper presents a novel approach based on differential games to the study of criminal networks. We extend the static crime network game (Ballester et al., 2004, 2006) to a dynamic setting. First, we determine the relationship between the Markov Perfect Equilibrium (MPE) and the vector of Bonacich centralities. The established proportionality between the Nash equilibrium and the Bonacich centrality in the static game does not hold in general in the dynamic setting. Next, focusing on regular networks, we provide an explicit characterization of equilibrium strategies, and conduct comparative dynamic analysis with respect to the network size, network density, and implicit growth rate of total wealth in the economy. Contrary to the static game, where aggregate equilibrium increases with network size and density, in the dynamic setting, more criminals or more connected criminals can lead to a decrease in total crime, both in the short run and at the steady state. We also examine another novel issue in the network theory literature, i.e., the existence of a voracity effect, occuring when an increase in the implicit growth rate of total wealth in the economy lowers economic growth. We do identify the presence of such a voracity effect in our setting
    Keywords: differential games; Markov Perfect Equilibrium; social networks; criminal networks; Bonacich centrality
    JEL: C73 D85 K42
    Date: 2022–02
  3. By: Michele Battisti; Andrea Mario Lavezzi; Roberto Musotto
    Abstract: In this article we study the organizational structure of a large group of members of the Sicilian Mafia by means of social network analysis and an econometric analysis of link formation. Our mains results are the following. i) The Mafia network is a small-world network adjusted by its criminal nature, and is strongly disassortative. ii) Mafia bosses are not always central in the network. In particular, consistent with a prediction of Baccara and Bar-Isaac, we identify a "cell-dominated hierarchy" in the network: a key member is not central, but is connected to a relative with a central position. iii) The probability of link formation between two agents is higher if the two agents belong to the same Mandamento, if they share a high number of similar tasks, while being a "boss" reduces the probability of link formation between them. iv) The probability of link formation for an individual agent is higher if he is in charge of keeping connections outside his Mandamento, of collecting protection money and or having a directive role, while age has modest role. These results are interpreted in the light of the efficiency/security trade-off faced by the Mafia and of its known hierarchical structure.
    Date: 2022–05
  4. By: Giuseppe Calafiore; Giulia Fracastoro; Anton V. Proskurnikov
    Abstract: The current global financial system forms a highly interconnected network where a default in one of its nodes can propagate to many other nodes, causing a catastrophic avalanche effect. In this paper we consider the problem of reducing the financial contagion by introducing some targeted interventions that can mitigate the cascaded failure effects. We consider a multi-step dynamic model of clearing payments and introduce an external control term that represents corrective cash injections made by a ruling authority. The proposed control model can be cast and efficiently solved as a linear program. We show via numerical examples that the proposed approach can significantly reduce the default propagation by applying small targeted cash injections.
    Date: 2022–05
  5. By: Max Marczinek; Stephan E. Maurer; Ferdinand Rauch
    Abstract: How do trade networks persist following disruptions of political networks? We study different types of persistence following the decline of the Hanseatic League using a panel of 21,590 city-level trade flows over 190 years, covering 1,425 cities. We use the Sound Toll data, a dataset collected by the Danish crown until 1857 that registered every ship entering or leaving the Baltic Sea, forming one of the most granular and extensive trade data sets. We measure trade flows by counting the number of ships sailing on a particular route in a given year and estimate gravity equations using PPML and an appropriate set of fixed effects. Bilateral gravity estimation results show that trade among former Hansa cities only shows persistence after its dissolution in 1669 for about 30 years, but this persistence is not robust across different regression specifications. However, when we incorporate the flag under which a ship is sailing and consider trilateral trade (where an observation is a combination of origin, destination, and flag), we find that trade persistently exceeds the gravity benchmark: Hansa cities continued to trade more with each other, but only on ships that were owned in another former Hansa city and thus sailed under a Hansa flag. Similar effects are found for trade among former Hansa cities and their trading posts abroad, yet again only conditional on the ship sailing under a former Hanseatic flag. Trade flows among the same pair of origin and destination cities, but under a different flag, do not show this persistence. Our main result shows that the identity of traders persists longer and more strongly than other forms of trading relationships we can measure. Apart from these new quantitative and qualitative insights on the persistence of trade flows, our paper is also of historic interest, as it provides new and detailed information on the speed of decline of trade amongst members of the Hanseatic League.
    Keywords: Hanseatic League, Hansa, gravity
    Date: 2022–12
  6. By: Florian Ederer; Bruno Pellegrino
    Abstract: We study the welfare implications of the rise of common ownership in the United States from 1994 to 2018. We build a general equilibrium model with a hedonic demand system in which firms compete in a network game of oligopoly. Firms are connected through two large networks: the first reflects ownership overlap, the second product market rivalry. In our model, common ownership of competing firms induces unilateral incentives to soften competition. The magnitude of the common ownership effect depends on how much the two networks overlap. We estimate our model for the universe of U.S. public corporations using a combination of firm financials, investor holdings, and text-based product similarity data. We perform counterfactual calculations to evaluate how the efficiency and the distributional impact of common ownership have evolved over time. According to our baseline estimates the welfare cost of common ownership, measured as the ratio of deadweight loss to total surplus, has increased nearly tenfold (from 0.3% to over 4%) between 1994 and 2018. Under alternative assumptions about governance, the deadweight loss ranges between 1.9% and 4.4% of total surplus in 2018. The rise of common ownership has also resulted in a significant reallocation of surplus from consumers to producers.
    JEL: D43 D85 E23 G23 G34 L16 L21
    Date: 2022–04
  7. By: Melina London (Aix Marseille University, CNRS, AMSE, Marseille, France.)
    Abstract: Large-scale analyses to map interactions between financial health at the sectoral level are still scarce. To fill the gap, in this paper, I map a network of predictive relationships across the financial health of several sectors. I provide a new advanced indicator to track propagation of financial distress across industries and countries on a monthly basis. I use defaults on trade credit as a measure of firms’ worsening financial conditions in a sector. To control for omitted-variable bias, I apply a high- dimensional VAR analysis, and isolate direct cross-sector causalities `a la Granger from common exposure to macroeconomic shocks or to third-sector shock. I show that monitoring some key sectors–among which construction, wholesale and retail, or the automotive sector–can improve the detection of financial distress in other sectors. Finally, I find that those financial predictive relationships correlates with the input-output structure in the considered economies. Such structure of financial interactions reflect the propagation of financial distress along the supply chain.
    Keywords: trade credit; network; cross-sector financial interdependencies
    JEL: F14 F36 F44 L14
    Date: 2022–05

This nep-net issue is ©2022 by Alfonso Rosa García. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.