nep-net New Economics Papers
on Network Economics
Issue of 2021‒02‒08
twelve papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Best-response dynamics in directed network games By P\'eter Bayer; Gy\"orgy Kozics; N\'ora Gabriella Sz\H{o}ke
  2. The computation of pairwise stable networks By Herings, P. Jean-Jacques; Zhan, Yang
  3. Modeling simultaneous supply and demand shocks in input-output networks By Anton Pichler; J. Doyne Farmer
  4. Crisis Propagation in a Heterogeneous Self-Reflexive DSGE Model By Federico Guglielmo Morelli; Michael Benzaquen; Jean-Philippe Bouchaud; Marco Tarzia
  5. Robust communication on networks By Marie Laclau; Ludovic Renou; Xavier Venel
  6. Friendship Networks and Political Opinions: A Natural Experiment among Future French Politicians By Algan, Yann; Dalvit, Nicolò; Do, Quoc-Anh; Le Chapelain, Alexis; Zenou, Yves
  7. Dynamic industry uncertainty networks and the business cycle By Jozef Barunik; Mattia Bevilacqua; Robert Faff
  8. Interdependence of sectors of economic activities for world countries from the reduced Google matrix analysis of WTO data By Célestin Coquidé; José Lages; Dima L. Shepelyansky
  9. No inventor is an island: social connectedness and the geography of knowledge flows in the US By Andreas Diemer; Tanner Regan
  10. Can Charitable Appeals Identify and Exploit Belief Heterogeneity? By Michalis Drouvelis; Benjamin M. Marx
  11. On the typicality of the representative agent By Teglio, Andrea
  12. Social Distancing During a Pandemic: The Role of Friends By Michael Bailey; Drew M. Johnston; Martin Koenen; Theresa Kuchler; Dominic Russel; Johannes Stroebel

  1. By: P\'eter Bayer; Gy\"orgy Kozics; N\'ora Gabriella Sz\H{o}ke
    Abstract: We study public goods games played on networks with possibly non-reciprocal relationships between players. Examples for this type of interactions include one-sided relationships, mutual but unequal relationships, and parasitism. It is well known that many simple learning processes converge to a Nash equilibrium if interactions are reciprocal, but this is not true in general for directed networks. However, by a simple tool of rescaling the strategy space, we generalize the convergence result for a class of directed networks and show that it is characterized by transitive weight matrices. Additionally, we show convergence in a second class of networks; those rescalable into networks with weak externalities. We characterize the latter class by the spectral properties of the absolute value of the network's weight matrix and show that it includes all directed acyclic networks.
    Date: 2021–01
  2. By: Herings, P. Jean-Jacques (RS: GSBE Theme Data-Driven Decision-Making, RS: GSBE Theme Conflict & Cooperation, Microeconomics & Public Economics); Zhan, Yang
    Abstract: One of the most important stability concepts for network formation is pairwise stability. We develop a homotopy algorithm that is effective in computing pairwise stable networks for a generic network formation problem. To do so, we reformulate the concept of pairwise stability as a Nash equilibrium of a non-cooperative game played by the links in the network and adapt the linear tracing procedure for non-cooperative games to the network formation problem. As a by-product of our main result, we obtain that the number of pairwise stable networks is generically odd. We apply the algorithm to the connections model.
    Date: 2021–01–26
  3. By: Anton Pichler; J. Doyne Farmer
    Abstract: Natural and anthropogenic disasters frequently affect both the supply and demand side of an economy. A striking recent example is the Covid-19 pandemic which has created severe industry-specific disruptions to economic output in most countries. Since firms are embedded in production networks, these direct shocks to supply and demand will propagate downstream and upstream. We show that existing input-output models which allow for binding demand and supply constraints yield infeasible solutions when applied to pandemic shocks of three major European countries (Germany, Italy, Spain). We then introduce a mathematical optimization procedure which is able to determine best-case feasible market allocations, giving a lower bound on total shock propagation. We find that even in this best-case scenario network effects substantially amplify the initial shocks. To obtain more realistic model predictions, we study the propagation of shocks bottom-up by imposing different rationing rules on firms if they are not able to satisfy incoming demand. Our results show that overall economic impacts depend strongly on the emergence of input bottlenecks, making the rationing assumption a key variable in predicting adverse economic impacts. We further establish that the magnitude of initial shocks and network density heavily influence model predictions.
    Date: 2021–01
  4. By: Federico Guglielmo Morelli; Michael Benzaquen; Jean-Philippe Bouchaud; Marco Tarzia
    Abstract: We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp crossover between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for which cascading contagion effects are stronger. For the same reason, larger income inequalities tend to reduce, in our model, the probability of global crises. Finally, we are able to reproduce a perhaps counter-intuitive empirical finding: in countries with higher Gini coefficients, the consumption of the lowest income households tends to drop less than that of the highest incomes in crisis times.
    Date: 2021–01
  5. By: Marie Laclau (CNRS - Centre National de la Recherche Scientifique, GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique, HEC Paris - Ecole des Hautes Etudes Commerciales); Ludovic Renou (QMUL - Queen Mary University of London, University of Adelaide); Xavier Venel (LUISS - Libera Università Internazionale degli Studi Sociali Guido Carli [Roma])
    Abstract: We consider sender-receiver games, where the sender and the receiver are two distinct nodes in a communication network. Communication between the sender and the receiver is thus indirect. We ask when it is possible to robustly implement the equilibrium outcomes of the direct communication game as equilibrium outcomes of indirect communication games on the network. Robust implementation requires that: (i) the implementation is independent of the preferences of the intermediaries and (ii) the implementation is guaranteed at all histories consistent with unilateral deviations by the intermediaries. We show that robust implementation of direct communication is possible if and only if either the sender and receiver are directly connected or there exist two disjoint paths between the sender and the receiver. We also show that having two disjoint paths between the sender and the receiver guarantees the robust implementation of all communication equilibria of the direct game. We use our results to reflect on organizational arrangements.
    Keywords: Cheap talk,direct,mediated,communication,protocol,network. JEL CLASSIFICATION: C72,D82
    Date: 2021–01–06
  6. By: Algan, Yann (Sciences Po, Paris); Dalvit, Nicolò (Sciences Po, Paris); Do, Quoc-Anh (Sciences Po, Paris); Le Chapelain, Alexis; Zenou, Yves (Monash University)
    Abstract: We study how social interaction and friendship shape students' political opinions in a natural experiment at Sciences Po, the cradle of top French politicians. We exploit arbitrary assignments of students into short-term integration groups before their scholar cursus, and use the pairwise indicator of same-group membership as instrumental variable for friendship. After six months, friendship causes a reduction of differences in opinions by one third of the standard deviation of opinion gap. The evidence is consistent with a homophily-enforced mechanism, by which friendship causes initially politically-similar students to join political associations together, which reinforces their political similarity, without exercising an effect on initially politically-dissimilar pairs. Friendship affects opinion gaps by reducing divergence, therefore polarization and extremism, without forcing individuals' views to converge. Network characteristics also matter to the friendship effect.
    Keywords: political opinion, polarization, friendship effect, social networks, homophily, extremism, learning, natural experiment
    JEL: C93 D72 Z13
    Date: 2020–12
  7. By: Jozef Barunik; Mattia Bevilacqua; Robert Faff
    Abstract: This paper introduces new forward-looking uncertainty network measures built from the main US industries. We argue that this network structure extracted from options investors' expectations is meaningfully dynamic and contains valuable information relevant for business cycles. Classifying industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not propagate strongly across the network. We find that a dynamic ex-ante network of uncertainty is a useful predictor of business cycles especially when it is based on uncertainty hubs. The uncertainty network is found to behave counter-cyclically since a tighter network of industry uncertainty tends to associate with future business cycle contractions.
    Date: 2021–01
  8. By: Célestin Coquidé (UTINAM - Univers, Transport, Interfaces, Nanostructures, Atmosphère et environnement, Molécules (UMR 6213) - INSU - CNRS - Institut national des sciences de l'Univers - CNRS - Centre National de la Recherche Scientifique - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE]); José Lages (UTINAM - Univers, Transport, Interfaces, Nanostructures, Atmosphère et environnement, Molécules (UMR 6213) - INSU - CNRS - Institut national des sciences de l'Univers - CNRS - Centre National de la Recherche Scientifique - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE]); Dima L. Shepelyansky (Information et Chaos Quantiques (LPT) - LPT - Laboratoire de Physique Théorique - IRSAMC - Institut de Recherche sur les Systèmes Atomiques et Moléculaires Complexes - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UT3 - Université Toulouse III - Paul Sabatier - Université Fédérale Toulouse Midi-Pyrénées - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We apply the recently developed reduced Google matrix algorithm for the analysis of the OECD-WTO world network of economic activities. This approach allows to determine interdependences and interactions of economy sectors of several countries, including China, Russia and USA, properly taking into account the influence of all other world countries and their economic activities. Within this analysis we also obtain the sensitivity of economy sectors and EU countries to petroleum activity sector. We show that this approach takes into account multiplicity of network links with economy interactions between countries and activity sectors thus providing more rich information compared to the usual export-import analysis.
    Keywords: World Trade Organization,networks,Google matrix,Markovian process,PageRank
    Date: 2020–12–13
  9. By: Andreas Diemer; Tanner Regan
    Abstract: Do informal social ties connecting inventors across distant places promote knowledge flows between them? To measure informal ties, we use a new and direct index of social connectedness of regions based on aggregate Facebook friendships. We use a well-established identification strategy that relies on matching inventor citations with citations from examiners. Moreover, we isolate the specific effect of informal connections, above and beyond formal professional ties (co-inventor networks) and geographic proximity. We identify a significant and robust effect of informal ties on patent citation. Further, we find that the effect of geographic proximity on knowledge flows is entirely explained by informal social ties and professional networks. We also show that the effect of informal social ties on knowledge flows: has become increasingly important over the last two decades, is higher for older or `forgotten' patents, is more important for new entrepreneurs or `garage inventors', and is somewhat stronger across distant technology fields.
    Keywords: knowledge flows, diffusion, social connectedness, informal networks
    JEL: O33 R12 Z13
    Date: 2020–11
  10. By: Michalis Drouvelis; Benjamin M. Marx
    Abstract: Charitable fundraisers frequently announce giving by others, and research shows that this can increase donations. However, this mechanism may not put information about peers to the most efficient use if it is costly to inform individuals who are indifferent to peer actions or causes some individuals to give less. We investigate whether a simple mechanism without incentives can predict heterogeneity in charitable responses to peer decisions. We elicit beliefs about donations in a baseline solicitation, and in subsequent solicitations we randomly assign information about others’ donations. We find that elicited beliefs are often logically inconsistent and that many subjects fail to update beliefs when treated. However, elicited beliefs can predict heterogeneous treatment effects if individuals are engaged and the information is salient.
    Keywords: charitable, donation, norm, social preferences, peer effects, experiment
    JEL: D01 D64 A13
    Date: 2021
  11. By: Teglio, Andrea
    Abstract: The aim of this paper is to explore under which conditions a representative agent (RA) model is able to correctly approximate the output of a more realistic model based on the "true" assumption of many interacting agents. The starting point is the widespread Keynesian cross diagram, which is compared to an extended versions that explicitly considers a multiplicity of interacting households and firms, and collapses into the original model when the number of agents is one per type. Results show that the RA Keynesian cross diagram model is not a good approximation of the extended model when (i) the network structure of the economy is not symmetric enough, e.g. firms have different sizes, or (ii) the rationality of agents is not high enough. When income inequality is considered, through the introduction of capitalists, the representative agent model is no more a good approximation, even if the agents are rational. A fiscal policy that targets income redistribution improves the prediction of the RA model. In general, all features that increase overall rationality in the economy and decrease its heterogeneity, tend to improve the performance of the RA approximation.
    Keywords: macroeconomics; rationality; inequality; Keynesian cross-diagram; representative agent; agent-based models; networks; simulation; complex adaptive systems
    JEL: C63 E00 E12
    Date: 2020–10–10
  12. By: Michael Bailey; Drew M. Johnston; Martin Koenen; Theresa Kuchler; Dominic Russel; Johannes Stroebel
    Abstract: We explore how social network exposure to COVID-19 cases shapes individuals' social distancing behavior during the early months of the ongoing pandemic. We work with de-identified data from Facebook to show that U.S. users whose friends live in areas with worse coronavirus outbreaks reduce their mobility more than otherwise similar users whose friends live in areas with smaller outbreaks. The effects are quantitatively large: a one standard deviation increase in friend-exposure to COVID-19 cases early in the pandemic results in a 1.2 percentage point increase in the probability that an individual stays home on a given day. As the pandemic progresses, changes in friend-exposure drive changes in social distancing behavior. Given the evolving nature and geography of the pandemic -- and hence friend-exposure -- these results rule out many alternative explanations for the observed relationships. We also analyze data on public posts and membership in groups advocating to "reopen" the economy to show that our findings can be explained by friend-exposure raising awareness about the risks of the disease and inducing individuals to participate in mitigating public health behavior.
    JEL: D83 D85 H0 I0
    Date: 2020–12

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