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on Network Economics |
| By: | Choi, S.; Goyal, S.; Moisan, F.; To, Y. Y. T. |
| Abstract: | Subjects observe a private signal and then make an initial guess; they observe their neighbors’ guesses and guess again, and so forth. We study learning dynamics in three networks: Erdös-Rényi, Stochastic Block (reflecting homophily) and Royal Family (that accommodates both highly connected celebrities and local intearctions). We find that the Royal Family network is more likely to sustain incorrect consensus and that the Stochastic Block network is more likely to persist with diverse beliefs. These aggregate patterns are consistent with individuals following DeGroot updating rule. |
| Keywords: | consensus, experimental social science, social learning, social networks |
| JEL: | C91 C92 D83 D85 |
| Date: | 2022–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camjip:2212&r= |
| By: | Chien-Hsiang Yeh |
| Abstract: | This paper extends the unified network model, proposed by Acemoglu et al. (2016b), such that interaction functions can be heterogeneous, and the sensitivity matrix has less than or equal to one spectral radius. We show the existence and (almost surely) uniqueness of equilibrium under both eventually contracting and noncontracting assumptions. Applying the equilibrium in the study of systemic risk, we provide a measure to determine the key player who causes the most significant impact if removed from the network. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2206.00158&r= |
| By: | Olga Balakina (Department of Economics and Business Economics, Aarhus University); Claes Bäckman (Department of Economics and Business Economics, Aarhus University, Knut Wiksell Center for Financial Studies, Lund University); Andreas Hackethal (Goethe University Frankfurt, Leibniz Institute for Financial Research SAFE Frankfurt); Tobin Hanspal (Department of Finance, Vienna University of Economics and Business); Dominique M. Lammer |
| 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: | 2022–07–18 |
| URL: | http://d.repec.org/n?u=RePEc:aah:aarhec:2022-02&r= |
| By: | Anukriti, S (World Bank); Herrera-Almanza, Catalina (University of Illinois at Urbana-Champaign); Karra, Mahesh (Boston University) |
| Abstract: | We experimentally test if enabling individuals to incentivize others to socialize with them can strengthen social networks and improve well-being. We examine family planning access for women in India, who tend to be socially isolated and for whom peer support may overcome intrahousehold constraints. Enabling women to jointly visit a clinic with other women not only increased social ties and strengthened peer engagement, but also increased clinic visits and contraceptive use. Moreover, this intervention was more effective in improving reproductive autonomy of women who faced greater intrahousehold opposition than an intervention that only improved women's own access to the clinic. |
| Keywords: | women’s social networks, peers, vouchers, India, family planning, contraception, female autonomy, mother-in-law |
| JEL: | J13 J16 O15 O33 I15 Z13 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp15381&r= |
| By: | Tomas Scagliarini; Giuseppe Pappalardo; Alessio Emanuele Biondo; Alessandro Pluchino; Andrea Rapisarda; Sebastiano Stramaglia |
| Abstract: | In this paper we analyse the effects of information flows in cryptocurrency markets. We first define a cryptocurrency trading network, i.e. the network made using cryptocurrencies as nodes and the Granger causality among their weekly log returns as links, later we analyse its evolution over time. In particular, with reference to years 2020 and 2021, we study the logarithmic US dollar price returns of the cryptocurrency trading network using both pairwise and high-order statistical dependencies, quantified by Granger causality and O-information, respectively. With reference to the former, we find that it shows peaks in correspondence of important events, like e.g., Covid-19 pandemic turbulence or occasional sudden prices rise. The corresponding network structure is rather stable, across weekly time windows in the period considered and the coins are the most influential nodes in the network. In the pairwise description of the network, stable coins seem to play a marginal role whereas, turning high-order dependencies, they appear in the highest number of synergistic information circuits, thus proving that they play a major role for high order effects. With reference to redundancy and synergy with the time evolution of the total transactions in US dollars, we find that their large volume in the first semester of 2021 seems to have triggered a transition in the cryptocurrency network toward a more complex dynamical landscape. Our results show that pairwise and high-order descriptions of complex financial systems provide complementary information for cryptocurrency analysis. |
| Date: | 2022–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2207.04004&r= |
| By: | Kim, Jun Sung; Patacchini, Eleonora (Cornell University); Picard, Pierre M. (University of Luxembourg); Zenou, Yves (Monash University) |
| Abstract: | This paper studies how the strength of social ties are affected by the geographical location of other individuals and their social capital. We characterize the equilibrium in terms of both social interactions and social capital. We show that lower travel costs increase not only the interaction frequency but also the social capital for all agents. We also show that the equilibrium frequency of interactions is lower than the efficient one. Using a unique geo-coded dataset of friendship networks among adolescents in the United States, we structurally estimate the model and show that, indeed, agents socially interact less than that at the first best optimum. Our policy analysis suggests that, at the same cost, subsidizing social interactions yields a higher total welfare than subsidizing transportation costs. |
| Keywords: | social networks, location, structural estimation, policies |
| JEL: | D85 R1 Z13 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp15376&r= |
| By: | Alessandro Avellone; Stefano Benati; Rosanna Grassi; Giorgio Rizzini |
| Abstract: | The persistence probability is a statistical index that has been proposed to detect one or more communities embedded in a network. Even though its definition is straightforward, e.g, the probability that a random walker remains in a group of nodes, it has been seldom applied possibly for the difficulty of developing an efficient algorithm to calculate it. Here, we propose a new mathematical programming model to find the community with the largest persistence probability. The model is integer fractional programming, but it can be reduced to mixed-integer linear programming with an appropriate variable substitution. Nevertheless, the problem can be solved in a reasonable time for networks of small size only, therefore we developed some heuristic procedures to approximate the optimal solution. First, we elaborated a randomized greedy-ascent method, taking advantage of a peculiar data structure to generate feasible solutions fast. After analyzing the greedy output and determining where the optimal solution is eventually located, we implemented improving procedures based on a local exchange, but applying different long term diversification principles, that are based on variable neighborhood search and random restart. Next, we applied the algorithms on simulated graphs that reproduce accurately the clustering characteristics found in real networks to determine the reliability and the effectiveness of our methodology. Finally, we applied our method to two real networks, comparing our findings to what found by two well-known alternative community detection procedures. |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2206.10330&r= |
| By: | Berliant, Marcus |
| Abstract: | We examine the fine microstructure of commuting in a game-theoretic setting with a continuum of commuters. Commuters' home and work locations can be heterogeneous. A commuter transport network is exogenous. Traffic speed is determined by link capacity and by local congestion at a time and place along a link, where local congestion at a time and place is endogenous. The model can be reinterpreted to apply to congestion on the internet. We find sufficient conditions for existence of equilibrium, that multiple equilibria are ubiquitous, and that the welfare properties of morning and evening commute equilibria differ on a generalization of a directed tree. |
| Keywords: | Commuting; Internet traffic; Congestion externality; Efficient Nash equilibrium |
| JEL: | L86 R41 |
| Date: | 2022–06–30 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:113616&r= |
| By: | Mélina London (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université) |
| 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 highdimensional VAR analysis, and isolate direct cross-sector causalities à 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: | Cross-Sector Financial Interdependencies,Network,Trade credit |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03667832&r= |
| By: | Hempfing, Alexander; Mundt, Philipp |
| Abstract: | Using a statistical model of an evolving multiplex network, we study tie formation in global production chains within and across developed countries, their trade activities with developing economies in the intermediate goods market, and the mutual dependencies between these relationships. Our model approaches these dynamics from the perspective of individual nodes and thus identifies the driving forces behind the tie formation process. The empirical value of our approach is demonstrated by fitting the model to a panel data set from the OECD Inter-Country Input-Output Tables between 2005 and 2015. Based on these data, we find that (i) geography, two-sided heterogeneity of buyers and sellers, trade costs, as well as structural characteristics of the production network determine the formation of trade linkages between OECD country-sectors, (ii) some of these determinants have an asymmetric effect on import and export ties between OECD and non-OECD countries, and (iii) intra-OECD trade and import and export ties with non-OECD economies are mutually dependent. |
| Keywords: | trade network,network formation,stochastic actor-oriented model,multiplex dynamics,input-output analysis |
| JEL: | E23 F14 D57 R15 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bamber:181&r= |
| By: | Cotter, Christopher; Rousseau, Peter L |
| Abstract: | During the U.S. National Banking Period (1863-1913), a network of correspondent banking relationships left the nation vulnerable to systemic risks, bank failures, and financial panics. We use comprehensive data on primary correspondent relationships for all national, state, savings, and private banks in the lead up to the Panic of 1893 to show that failures of both upstream and downstream correspondents increased the likelihood that a given bank would itself fail, and that these effects varied over the course of the Panic. Members of the New York Clearinghouse, despite a very low incidence of actual failure, also saw significant weakening of their balance sheets early in the Panic when their downstream respondents failed, and falling stock prices throughout the disruption. The results demonstrate a two-way system-wide weakness of the correspondent system that the Federal Reserve Act of 1914 presumably sought to remedy. |
| Keywords: | Interbank networks, correspondent banking, the Panic of 1893, bank contagion |
| JEL: | G01 G21 N21 |
| Date: | 2022–05–19 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:113340&r= |
| By: | Bruno Baranek; L. Musolff; Vitezslav Titl |
| Abstract: | Collusion likely has adverse effects on social welfare. In this paper, we study collusion in the e-procurement market in Ukraine. We document that the bidding patterns in the data are incompatible with a competitive equilibrium. We develop a novel structural test to detect pairs and, thereby, networks of collusive firms. We validate the soundness of our collusion detection algorithm on a sample of 863 prosecuted collusive firms that participated in 23,515 tenders. |
| Keywords: | Public procurement, Collusion, Online markets |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:use:tkiwps:2111&r= |