nep-net New Economics Papers
on Network Economics
Issue of 2021‒04‒26
seven papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. The global network of embodied R&D flows By Fabrizio Fusillo; Sandro Montresor; Giuseppe Vittucci Marzetti
  2. Homophily, Peer Effects, and Dishonesty By Liza Charroin; Bernard Fortin; Marie Villeval
  3. The International Transmission of Local Economic Shocks Through Migrant Networks By María Esther Caballero; Brian Cadena; Brian K. Kovak
  4. The Nexus of Elites and War Mobilization By Ying Bai; Ruixue Jia; Jiaojiao Yang
  5. Identification of Peer Effects with Miss-specified Peer Groups: Missing Data and Group Uncertainty By Christiern Rose
  6. Avoiding the bullies: The resilience of cooperation among unequals By Michael Foley; Rory Smead; Patrick Forber; Christoph Riedl
  7. Macroeconomic forecasting with statistically validated knowledge graphs By Sonja Tilly; Giacomo Livan

  1. By: Fabrizio Fusillo (Università di Torino); Sandro Montresor (Gran Sasso Science Institute); Giuseppe Vittucci Marzetti (Università di Milano-Bicocca)
    Abstract: We combine the World Input-Output Dataset (WIOD) with OECD data on Analytical Business Enterprise R&D (ANBERD) and build up the network that emerges by mapping the sectoral R&D expenditure that flows in an embodied way among 690 industry-country nodes (23 industries of 30 countries), from 2009 to 2013. Drawing on frontier network analysis techniques, we examine the distribution of the relational properties of the country-industry nodes, identify the most central of them, and detect the clusters that they form. Our analysis reveals that, while the diffusion of embodied R&D is highly pervasive on a global scale, the linkages it creates across sectors tend to be highly asymmetric and polarised. Furthermore, except for transportation and ICT related industries, embodied R&D flows determine communities largely confined within national borders. Despite being based on structural inputoutput relationships, the position and role of country-industry nodes in the global network of embodied R&D knowledge show a certain variability both over time and across network dimensions.
    Keywords: R&D flows, input-output, global innovation network, network analysis
    JEL: O33 R15 O57
    Date: 2021–04
  2. By: Liza Charroin (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Paris 1 Panthéon-Sorbonne); Bernard Fortin (Département d'Economique, Université Laval - ULaval - Université Laval [Québec], CIRPEE - Centre interuniversitaire sur le risque, les politiques économiques et l'emploi [Montréal] - UQAM - Université du Québec à Montréal = University of Québec in Montréal, CIRANO - Centre interuniversitaire de recherche en analyse des organisations - UQAM - Université du Québec à Montréal = University of Québec in Montréal, IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics); Marie Villeval (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique, IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics)
    Abstract: If individuals tend to behave like their peers, is it because of conformity, that is, the preference of people to align behavior with the behavior of their peers; homophily, that is, the tendency of people to bond with similar others; or both? We address this question in the context of an ethical dilemma. Using a peer effect model allowing for homophily, we designed a real-effort laboratory experiment in which individuals could misreport their performance to earn more. Our results reveal a preference for conformity and for homophily in the selection of peers, but only among participants who were cheating in isolation. The size of peer effects is similar when identical peers were randomly assigned and when they were selected by individuals. We thus jointly reject the presence of a self-selection bias in the peer effect estimates and of a link strength effect.
    Keywords: Peer Effects,Homophily,Dishonesty,Self-Selection Bias,Experiment
    Date: 2021–04
  3. By: María Esther Caballero; Brian Cadena; Brian K. Kovak
    Abstract: Using newly validated data on geographic migration networks, we study how labor demand shocks in the United States propagate across the border with Mexico. We show that the large exogenous decline in US employment brought about by the Great Recession affected demographic and economic outcomes in Mexican communities that were highly connected to the most affected markets in the US. In the Mexican locations with strong initial ties to the hardest hit US migrant destinations, return migration increased, emigration decreased, and remittance receipt declined. These changes significantly increased local employment and hours worked, but wages were unaffected. Investment in durable goods and children's education also slowed in these communities. These findings document the effects in Mexico when potential migrants lose access to a strong US labor market, providing insight regarding the potential impacts of stricter US migration restrictions.
    JEL: F22 J21 J23 J61 R23
    Date: 2021–04
  4. By: Ying Bai; Ruixue Jia; Jiaojiao Yang
    Abstract: How do elites mobilize commoners to participate in a war? How does war mobilization affect elite power after the war? We argue that these two questions are interconnected, as elites mobilize war often because war benefits them. We demonstrate these relationships using the setting of the organization of the Hunan Army – an army organized by one Hunanese scholargeneral that suppressed the deadliest civil war in history, the Taiping Rebellion (1850–1864). We construct comprehensive datasets to depict the elites in the scholar-general’s pre-war network as well as the distribution of political power before and after the war. By examining how pre-war elite connections affected where soldiers who were killed came from, and subsequent shifts in the post-war distribution of political power toward the home counties of these very elites, we highlight a two-way nexus of elites and war mobilization: (i) elites used their personal network for mobilization; and (ii) network-induced mobilization elevated regional elites to the national political stage, where they influenced the fortunes of the country after the war.
    JEL: D74 H11 L14 N45 O11
    Date: 2021–04
  5. By: Christiern Rose
    Abstract: We consider identification of peer effects under peer group miss-specification. Our model of group miss-specification allows for missing data and peer group uncertainty. Missing data can take the form of some individuals being completely absent from the data, and the researcher need not have any information on these individuals and may not even know that they are missing. We show that peer effects are nevertheless identifiable if these individuals are missing completely at random, and propose a GMM estimator which jointly estimates the sampling probability and peer effects. In practice this means that the researcher need only have access to an individual/household level sample with group identifiers. The researcher may also be uncertain as to what is the relevant peer group for the outcome under study. We show that peer effects are nevertheless identifiable provided that the candidate peer groups are nested within one another (e.g. classroom, grade, school) and propose a non-linear least squares estimator. We conduct a Monte-Carlo experiment to demonstrate our identification results and the performance of the proposed estimators in a setting tailored to real data (the Dartmouth room-mate data).
    Date: 2021–04
  6. By: Michael Foley; Rory Smead; Patrick Forber; Christoph Riedl
    Abstract: Can egalitarian norms or conventions survive the presence of dominant individuals who are ensured of victory in conflicts? We investigate the interaction of power asymmetry and partner choice in games of conflict over a contested resource. We introduce three models to study the emergence and resilience of cooperation among unequals when interaction is random, when individuals can choose their partners, and where power asymmetries dynamically depend on accumulated payoffs. We find that the ability to avoid bullies with higher competitive ability afforded by partner choice mostly restores cooperative conventions and that the competitive hierarchy never forms. Partner choice counteracts the hyper dominance of bullies who are isolated in the network and eliminates the need for others to coordinate in a coalition. When competitive ability dynamically depends on cumulative payoffs, complex cycles of coupled network-strategy-rank changes emerge. Effective collaborators gain popularity (and thus power), adopt aggressive behavior, get isolated, and ultimately lose power. Neither the network nor behavior converge to a stable equilibrium. Despite the instability of power dynamics, the cooperative convention in the population remains stable overall and long-term inequality is completely eliminated. The interaction between partner choice and dynamic power asymmetry is crucial for these results: without partner choice, bullies cannot be isolated, and without dynamic power asymmetry, bullies do not lose their power even when isolated. We analytically identify a single critical point that marks a phase transition in all three iterations of our models. This critical point is where the first individual breaks from the convention and cycles start to emerge.
    Date: 2021–04
  7. By: Sonja Tilly; Giacomo Livan
    Abstract: This study leverages narrative from global newspapers to construct theme-based knowledge graphs about world events, demonstrating that features extracted from such graphs improve forecasts of industrial production in three large economies compared to a number of benchmarks. Our analysis relies on a filtering methodology that extracts "backbones" of statistically significant edges from large graph data sets. We find that changes in the eigenvector centrality of nodes in such backbones capture shifts in relative importance between different themes significantly better than graph similarity measures. We supplement our results with an interpretability analysis, showing that the theme categories "disease" and "economic" have the strongest predictive power during the time period that we consider. Our work serves as a blueprint for the construction of parsimonious - yet informative - theme-based knowledge graphs to monitor in real time the evolution of relevant phenomena in socio-economic systems.
    Date: 2021–04

This nep-net issue is ©2021 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.