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on Network Economics |
| By: | Péter Bayer; György Kozics; Nóra Gabriella Szőke |
| 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: | 2020–01–13 |
| URL: | http://d.repec.org/n?u=RePEc:ceu:econwp:2020_1&r=all |
| By: | Boeing, Geoff (Northeastern University) |
| Abstract: | OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales - namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use. |
| Date: | 2018–08–02 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:hmhts&r=all |
| By: | Dungey, Mardi (University of Tasmania); Kangogo, Moses (University of Tasmania); Volkov, Vladimir (University of Tasmania) |
| Abstract: | This paper investigates the changing network of financial markets between Asian markets and those of the rest of the world during January 2003–December 2017 to capture both the direction and strength of the links between them. Because each market chooses whether to connect with emerging markets as a bridge to the wider network, there are advantages to having access to this bridge for protection during periods of financial stress. Both parties gain by overcoming the information asymmetry between emerging and global markets. We analyze networks for four key periods, capturing networks in financial markets before and after the Asian financial crisis and the global financial crisis. Increased connections during crisis periods are evident, as well as a general deepening of the global network. The evidence on Asian market developments suggests caution is needed on regulations proposing methods to create stable networks, because these may result in reduced opportunities for emerging markets. |
| Keywords: | Asian markets; financial crises; networks |
| JEL: | C21 G01 G15 N25 |
| Date: | 2019–05–30 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbewp:0583&r=all |
| By: | Bergantiños, Gustavo; Vidal-Puga, Juan |
| Abstract: | We consider a cost allocation problem arising from a hub network problem design. Finding an optimal hub network is NP-hard, so we start with a hub network that could be optimal or not. Our main objective is to divide the cost of such network among the nodes. We consider two cases. In the one-way flow case, we assume that the cost paid by a set of nodes depends only on the flow they send to other nodes (including nodes outside the set), but not on the flow they receive from nodes outside. In the two-way flow case, we assume that the cost paid by a set of nodes depends on the flow they send to other nodes(including nodes outside the set) and also on the flow they receive from nodes outside. In both cases, we study the core and the Shapley value of the corresponding cost game. |
| Keywords: | game theory; hub network; cost allocation; core; Shapley value |
| JEL: | C71 |
| Date: | 2018–05–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:97935&r=all |
| By: | Jan-Peter Siedlarek |
| Abstract: | High levels of clustering—the tendency for two nodes in a network to share a neighbor—are ubiquitous in economic and social networks across different applications. In addition, many real-world networks show high payoffs for nodes that connect otherwise separate network regions, representing rewards for filling “structural holes” in the sense of Burt (1992) and keeping distances in networks short. This paper proposes a parsimonious model of network formation with introductions and intermediation rents that can explain both these features. Introductions make it cheaper to create connections that share a common node. They are subject to a tradeoff between gains from shorter connections with lower search cost and losses from lower intermediation rents for the central node. Stable networks are shown to have high levels of clustering at the same time that they permit substantial intermediation rents for nodes bridging structural holes. |
| Keywords: | networks; network formation; clustering; intermediation; introductions |
| JEL: | A14 D85 |
| Date: | 2020–01–15 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedcwq:87371&r=all |
| By: | Aymeric Vi\'e; Alfredo J. Morales |
| Abstract: | Economic interdependencies have become increasingly present in globalized production, financial and trade systems. While establishing interdependencies among economic agents is crucial for the production of complex products, they may also increase systemic risks due to failure propagation. It is crucial to identify how network connectivity impacts both the emergent production and risk of collapse of economic systems. In this paper we propose a model to study the effects of network structure on the behavior of economic systems by varying the density and centralization of connections among agents. The complexity of production increases with connectivity given the combinatorial explosion of parts and products. Emergent systemic risks arise when interconnections increase vulnerabilities. Our results suggest a universal description of economic collapse given in the emergence of tipping points and phase transitions in the relationship between network structure and risk of individual failure. This relationship seems to follow a sigmoidal form in the case of increasingly denser or centralized networks. The model sheds new light on the relevance of policies for the growth of economic complexity, and highlights the trade-off between increasing the potential production of the system and its robustness to collapse. We discuss the policy implications of intervening in the organization of interconnections and system features, and stress how different network structures and node characteristics suggest different directions in order to promote complex and robust economic systems. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.09814&r=all |
| By: | Orlova, Olena (Center for Mathematical Economics, Bielefeld University) |
| Abstract: | We consider a network of players endowed with individual preferences and involved in interactions of various patterns. We show that their ability to make choices according to their preferences is limited, in a specific way, by their involvement in the network. The earlier literature demonstrated the conflict between individuality and peer pressure. We show that such a conflict is also present in contexts in which players do not necessarily aim at conformity with their peers. We investigate the consequences of preference heterogeneity for different interaction patterns, characterize corresponding equilibria and outline the class of games in which following own preferences is the unique Nash equilibrium. The introduction of personal preferences changes equilibrium outcomes in a non-trivial fashion: some equilibria disappear, while other, qualitatively new, appear. These results are robust to both independent and interdependent relationship between personal and social utility components. |
| Date: | 2020–01–13 |
| URL: | http://d.repec.org/n?u=RePEc:bie:wpaper:631&r=all |
| By: | Simon Gaechter (University of Nottingham); Chris Starmer (University of Nottingham); Fabio Tufano (University of Nottingham) |
| Abstract: | We introduce the concept of “group cohesion†to study the economic consequences of social relationships in team production. We measure group cohesion, adapting the “oneness scale†from psychology to group level. A series of experiments, including a pre-registered replication, reveals that higher cohesion groups are more likely to achieve Pareto-superior outcomes in weak-link coordination games. Judged against benchmarks, the effects of cohesion are economically large. We identify beliefs rather than social preferences as a primary mechanism explaining the effects of cohesion. Our comprehensive evidence establishes group cohesion as a powerful production factor and a useful new tool of economic research. |
| Keywords: | Group Cohesion, Oneness |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:not:notcdx:2019-16&r=all |
| By: | gopal, ganesh; Solanky, Debanjum Singh; Rajamanickam, Govindaraj |
| Abstract: | As we move towards more data intensive, device centric global communication networks, our ability to usefully harvest these large datastores is degrading. The widening asym-metry in the explosive growth of data versus our ability to use it, is forcing us towards centralized analytics. This splintered concentration of data further consolidates analytical capabilities in the hands of the few and divides the network into the analysors and the analysed. The fracturing of the system into opaque datastores and analytics blocks creates a strong positive feedback loop and has a significant negative impact on the stability, transparency and freedom of the network. This paper attempted to identify problems associated with the internet, internet dependent business models and reviewing available solutions and discuss possible solutions which became necessary. |
| Date: | 2018–02–20 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:apd5r&r=all |
| By: | Yuichi Ikeda; Hidetoshi Takeda |
| Abstract: | We develop a network reconstruction model based on the entropy maximization considering the sparsity of network. Here the reconstruction is to estimate network's adjacency matrix from node's local information. We reconstruct the interbank network in Japan from financial data in balance sheets of individual banks using the developed reconstruction model in the period from 2000 to 2016. The sparsity of the interbank network is successfully reproduced in the reconstructed network. We examine the accuracy of the reconstructed interbank network by comparing the actual data and analyze the characteristics of the interbank network. The comparison confirms that the accuracy of the reconstruction model is acceptably good. For the reconstructed interbank network, we obtain the following characteristics which are consistent with the previously known stylized facts: the short path length, the small clustering coefficient, the disassortative property, and the core and peripheral structure. Community analysis shows that the number of communities is 2-3 in the normal period, 1 in the economic crisis (2003, 2008-2013). The major nodes in each community have been the major commercial banks. Since 2013, the major commercial banks have lost the average PageRank and the leading regional banks have obtained both the average degree and the average PageRank. The observed changing role of banks is considered as a result of the quantitative and qualitative easing monetary policy started by Bank of Japan in April of 2013. |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2001.04097&r=all |
| By: | Niklas Stoehr; Fabian Braesemann; Michael Frommelt; Shi Zhou |
| Abstract: | The digital transformation is driving revolutionary innovations and new market entrants threaten established sectors of the economy such as the automotive industry. Following the need for monitoring shifting industries, we present a network-centred analysis of car manufacturer web pages. Solely exploiting publicly-available information, we construct large networks from web pages and hyperlinks. The network properties disclose the internal corporate positioning of the three largest automotive manufacturers, Toyota, Volkswagen and Hyundai with respect to innovative trends and their international outlook. We tag web pages concerned with topics like e-mobility and environment or autonomous driving, and investigate their relevance in the network. Sentiment analysis on individual web pages uncovers a relationship between page linking and use of positive language, particularly with respect to innovative trends. Web pages of the same country domain form clusters of different size in the network that reveal strong correlations with sales market orientation. Our approach maintains the web content's hierarchical structure imposed by the web page networks. It, thus, presents a method to reveal hierarchical structures of unstructured text content obtained from web scraping. It is highly transparent, reproducible and data driven, and could be used to gain complementary insights into innovative strategies of firms and competitive landscapes, which would not be detectable by the analysis of web content alone. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.10097&r=all |
| By: | Boeing, Geoff (Northeastern University) |
| Abstract: | Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city’s spatial logic and order. Measures of entropy reveal a city’s streets’ order and disorder. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. It measures the entropy of street bearings in weighted and unweighted network models, along with each city’s typical street segment length, average circuity, average node degree, and the network’s proportions of four-way intersections and dead-ends. It also develops a new indicator of orientation-order that quantifies how a city’s street network follows the geometric ordering logic of a single grid. A cluster analysis is performed to explore similarities and differences among these study sites in multiple dimensions. Significant statistical relationships exist between city orientation-order and other indicators of spatial order, including street circuity and measures of connectedness. On average, US/Canadian study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. These indicators, taken in concert, help reveal the extent and nuance of the grid. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world. |
| Date: | 2018–08–02 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:qj3p5&r=all |
| By: | Bail, Christopher A.; Argyle, Lisa; Brown, Taylor; Bumpuss, John; Chen, Haohan; Hunzaker, M.B. Fallin (New York University); Lee, Jaemin; Mann, Marcus; Merhout, Friedolin; Volfovsky, Alexander |
| Abstract: | There is mounting concern that social media sites contribute to political polarization by creating "echo chambers" that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a Twitter bot for one month that exposed them to messages produced by elected officials, organizations, and other opinion leaders with opposing political ideologies. Respondents were re-surveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative post-treatment, and Democrats who followed a conservative Twitter bot became slightly more liberal post-treatment. These findings have important implications for the interdisciplinary literature on political polarization as well as the emerging field of computational social science. |
| Date: | 2018–03–19 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:4ygux&r=all |
| By: | Jean-Sébastien Fontaine; Adrian Walton |
| Abstract: | Dealers connect investors who want to buy or sell securities in financial markets. Over time, dealers and investors form trading networks to save time and resources. An emerging field of research investigates how networks form. Using detailed data on trades in Government of Canada bonds, we reconstruct dealer networks and document how they respond to the release of relevant economic information. On one hand, we find that networks handle larger volumes of transactions and become more complex. On the other hand, we document more frequent and more severe contagion of settlement fails across dealer networks following these information releases. Settlement fails are unexpected delays in a buyer receiving bonds from a seller, creating counterparty risk and potential disruption to trading. Our findings suggest a trade-off. Large, complex dealer networks effectively connect investors but are also associated with contagion and an increase in counterparty risk due to settlement fails. One way to simplify dealer networks is through a central counterparty (CCP). A CCP reduces settlement volume, making fails less likely. |
| Keywords: | Financial markets; Market structure and pricing; Payment clearing and settlement systems |
| JEL: | E4 G1 G21 L14 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:20-1&r=all |
| By: | Mustafa Abdallah; Parinaz Naghizadeh; Ashish R. Hota; Timothy Cason; Saurabh Bagchi; Shreyas Sundaram |
| Abstract: | We consider a system consisting of multiple interdependent assets, and a set of defenders, each responsible for securing a subset of the assets against an attacker. The interdependencies between the assets are captured by an attack graph, where an edge from one asset to another indicates that if the former asset is compromised, an attack can be launched on the latter asset. Each edge has an associated probability of successful attack, which can be reduced via security investments by the defenders. In such scenarios, we investigate the security investments that arise under certain features of human decision-making that have been identified in behavioral economics. In particular, humans have been shown to perceive probabilities in a nonlinear manner, typically overweighting low probabilities and underweighting high probabilities. We show that suboptimal investments can arise under such weighting in certain network topologies. We also show that pure strategy Nash equilibria exist in settings with multiple (behavioral) defenders, and study the inefficiency of the equilibrium investments by behavioral defenders compared to a centralized socially optimal solution. |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2001.03213&r=all |
| By: | Kubinec, Robert (Princeton University); Owen, John |
| Abstract: | It is generally impossible to observe counterfactuals in which ideological polarization occurs both with and without international influence. To address this thorny problem, we employ a new statistical method, item response theory-vector auto-regression (IRT-VAR), that permits us to identify separately the transnational and domestic dynamics of polarization after the Arab Uprisings of 2011. We collected a dataset of Twitter accounts in Egypt and Tunisia during the critical year of 2013 when the Egyptian military staged a coup against the Islamist president Muhammad Morsi. We find that the coup increased retweets among ideological allies by as high as 50 percent each day following the coup and decreased cross-ideological retweets by as high as 25 percent. However, we also show that the transnational influence of external Islamist groups on Egyptian's Islamists served to dampen domestic polarization relative to the level that polarization might have reached if international social connections had not existed. |
| Date: | 2018–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:wykmj&r=all |