nep-net New Economics Papers
on Network Economics
Issue of 2016‒01‒29
eleven papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. A nonlinear impact: evidences of causal effects of social media on market prices By Th\'arsis T. P. Souza; Tomaso Aste
  2. Aggregation theory and the relevance of some issues to others By Franz Dietrich
  3. Is ride-sharing really as novel as it claims - Understanding Uber and its supply-side impacts in New Zealand By Chu, Yuet
  4. Differences of Opinions By Aliprantis, Dionissi
  5. International Trade: a Reinforced Urn Network Model By Stefano Peluso; Antonietta Mira; Pietro Muliere; Alessandro Lomi
  6. Testing for Causality in Continuous Time Bayesian Network Models of High-Frequency Data By Jonas Hallgren; Timo Koski
  8. Air transport liberalisation and airline network dynamics: Investigating the complex relationships By Frédéric Dobruszkes; Anne Graham
  9. Systemic Risk Management in Financial Networks with Credit Default Swaps By Matt V. Leduc; Sebastian Poledna; Stefan Thurner
  10. R&D in trade Networks: The Role of Asymmetry By Mariya Teteryatnikova
  11. Desperately Seeking Small Worlds in Corporate Boards:International Evidence from Listed Firms By Malika Hamadi; Andreas Heinen; Nicolas Jonard; Alfonso Valdesogo

  1. By: Th\'arsis T. P. Souza; Tomaso Aste
    Abstract: We provide empirical evidence that suggests social media and stock markets have a nonlinear causal relationship. We take advantage of an extensive data set composed of social media messages related to DJIA index components. By using information-theoretic measures to cope for possible nonlinear causal coupling between social media and stock markets systems, we point out stunning differences in the results with respect to linear coupling. Two main conclusions are drawn: First, social media significant causality on stocks' returns are purely nonlinear in most cases; Second, social media dominates the directional coupling with stock market, an effect not observable within linear modeling. Results also serve as empirical guidance on model adequacy in the investigation of sociotechnical and financial systems.
    Date: 2016–01
  2. By: Franz Dietrich (EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: I propose a relevance-based independence axiom on how to aggregate individual yes/no judgments on given propositions into collective judgments: the collective judgment on a proposition depends only on people's judgments on propositions which are relevant to that proposition. This axiom contrasts with the classical independence axiom: the collective judgment on a proposition depends only on people's judgments on the same proposition. I generalize the premise-based rule and the sequential-priority rule to an arbitrary priority order of the propositions, instead of a dichotomous premise/conclusion order resp. a linear priority order. I prove four impossibility theorems on relevance-based aggregation. One theorem simultaneously generalizes Arrow's Theorem (in its general and indifference-free versions) and the well-known Arrow-like theorem in judgment aggregation.
    Keywords: judgment aggregation,generalized Arrow theorem,generalized premise-based and sequential-priority rules,priority graph,aggregation of non-binary evalua-tions
    Date: 2015
  3. By: Chu, Yuet
    Abstract: In recent years, the emergence of multi-sided platforms has allowed peer-to-peer networks to grow exponentially, allowing individuals to form a collaborative economy by the sharing of underutilized resources. Within the realm of sharing economy, ride-sharing is the social phenomenon of allowing drivers and riders to congregate through a web-based platform to match the demand and supply sides in real time. The ride-sharing industry has posed as a major disruption to taxi industries worldwide. This paper seeks to investigate the industry dynamics surrounding Uber, a global ride-sharing company, in the New Zealand context, with main focus on the implications it has on the supply-side players (i.e. taxi companies and drivers) to evaluate if it has a sustainable competitive advantage in the market. Uber is the first ride-sharing company coming to New Zealand, established originally in San Francisco. Due to various differences in the market and legal factors, Uber has adapted its business model to suit this unique environment. Although it does not position itself as a ride-sharing business in New Zealand, but rather a private hire service company, Uber is using the same tools and resources to pool drivers and riders together under its multi-sided platform. The main competitive advantages Uber brings are the convenience, flexibility to drivers and the lower cost to consumers. While more and more ride-sharing and taxi-booking apps join in the competition; while taxi companies begin to innovate to create a stronger differentiating factor; and while regulators start to narrow the gaps in the regulations where Uber is deemed to have been given unfair advantages; Uber is facing stronger competition and challenges in the New Zealand market incrementally.
    Keywords: Sharing economy, Uber, Ride-sharing,
    Date: 2015
  4. By: Aliprantis, Dionissi (Federal Reserve Bank of Cleveland)
    Abstract: This paper presents a generalization of the DeGroot learning rule in which social learning can lead to polarization, even for connected networks. I first develop a model of biased assimilation in which the utility an agent receives from past decisions depends on current beliefs when uncertainty is slow to resolve. I use this model to motivate key features of an agent’s optimization problem subject to scarce private information, which forces the agent to extrapolate using social information. Even when the agent extrapolates under “scientific” assumptions and all individuals in the network process and report their private signals in an unbiased way, the possibility of biased processing or reporting leads agents to process social signals differently depending on the sender. The resulting solution to the agent’s problem is a heterogeneous confidence learning rule that is distinct from bounded confidence learning rules in that the agent may actually move her beliefs away from, and not only discard, signals from untrustworthy senders.
    Keywords: Biased Assimilation; Social Learning; Network; DeGroot Learning Rule; Bounded Confidence; Heterogeneous Confidence; Self-Affirmation;
    JEL: D83
    Date: 2016–01–20
  5. By: Stefano Peluso; Antonietta Mira; Pietro Muliere; Alessandro Lomi
    Abstract: We propose a unified modelling framework that theoretically justifies the main empirical regularities characterizing the international trade network. Each country is associated to a Polya urn whose composition controls the propensity of the country to trade with other countries. The urn composition is updated through the walk of the Reinforced Urn Process of Muliere et al. (2000). The model implies a local preferential attachment scheme and a power law right tail behaviour of bilateral trade flows. Different assumptions on the urns' reinforcement parameters account for local clustering, path-shortening and sparsity. Likelihood-based estimation approaches are facilitated by feasible likelihood analytical derivation in various network settings. A simulated example and the empirical results on the international trade network are discussed.
    Date: 2016–01
  6. By: Jonas Hallgren; Timo Koski
    Abstract: Continuous time Bayesian networks are investigated with a special focus on their ability to express causality. A framework is presented for doing inference in these networks. The central contributions are a representation of the intensity matrices for the networks and the introduction of a causality measure. A new model for high-frequency financial data is presented. It is calibrated to market data and by the new causality measure it performs better than older models.
    Date: 2016–01
  7. By: Swaha Bhattacharya; Sona Biswas
    Abstract: The aim of the present investigation is to study the social interaction anxiety and self-esteem of internet users between the ages 18 to 25 years. Accordingly, a group of 90 internet users (30 from internet user without addiction, 30 from internet user with mild addiction and 30 from internet user with moderate addiction) were selected as sample in this investigation. A General Information Schedule, Internet Addiction Test, Social Interaction Anxiety Scale and Rosenberg’s Self-Esteem Scale were used as tools. The findings revealed that social interaction anxiety increases with the increase of internet usage, on the other hand, self-esteem is comparatively higher among the internet users without addiction than that of the mild and moderately addicted internet users. Besides this, there is positive correlation between internet usage and social interaction anxiety. On the contrary, there is negative correlation between internet usage and self-esteem. Considering the findings of the study, it can be said that there is a dire need to develop intervention strategies for the internet addicted people to increase their self-esteem and also to reduce their problems related to social interaction anxiety. Key words: Social-interaction anxiety, Self-esteem and Internet usage
    Date: 2015–12
  8. By: Frédéric Dobruszkes; Anne Graham
    Date: 2016
  9. By: Matt V. Leduc; Sebastian Poledna; Stefan Thurner
    Abstract: We study insolvency cascades in an interbank system when banks are allowed to insure their loans with credit default swaps (CDS) sold by other banks. We show that, by properly shifting financial exposures from one institution to another, a CDS market can be designed to rewire the network of interbank exposures in a way that makes it more resilient to insolvency cascades. A regulator can use information about the topology of the interbank network to devise a systemic insurance surcharge that is added to the CDS spread. CDS contracts are thus effectively penalized according to how much they contribute to increasing systemic risk. CDS contracts that decrease systemic risk remain untaxed. We simulate this regulated CDS market using an agent-based model (CRISIS macro-financial model) and we demonstrate that it leads to an interbank system that is more resilient to insolvency cascades.
    Date: 2016–01
  10. By: Mariya Teteryatnikova
    Abstract: Countries differ substantially in their exposure to international trade as determined by the number of their trade partners. This exposure to trade and the asymmetry in trade exposure are anticipated by rms when making their R&D investments. We model a choice of R&D investments by firms in a given trade network focusing on the effects of the network asymmetry. The two large classes of networks considered include asymmetric hub-and-spoke networks and symmetric networks. We find that R&D, productivity and welfare are highest in a hub economy and lowest in a spoke, and the larger the degree of network asymmetry, the larger the dierence. A country in a symmetric network exhibits intermediate levels of R&D and welfare, even if the number of its trade partners is the same as in a hub or in a spoke. This implies that regional/preferential trade agreements, which result in a highly asymmetric trade network, benefit hub economies but harm spokes. By contrast, multilateral trade agreements, which lead to a symmetric complete network, generate equal R&D and welfare benefits for all countries.
    JEL: O31 D85 D43 L13 F13
    Date: 2016–01
  11. By: Malika Hamadi (CRENoS, University of Sassari); Andreas Heinen (THEMA, Université de Cergy-Pontoise); Nicolas Jonard (CREA, Université de Luxembourg); Alfonso Valdesogo (Department of Economics, Universidade Federal Fluminense)
    Abstract: This paper analyzes the structure of national corporate board networks of listed firms in a large cross-section of countries. We introduce an explicitly bivariate nonparametric hypothesis test for small worlds, based on the comparison of observed distance and clustering with simulated measures obtained from a number of increasingly stringent bipartite counterfactuals. Using our test, we find little support for the small world hypothesis regardless of the counterfactual. Moreover, we show that results are sensitive to the choice of counterfactual. We further identify the role played by bicliques, small densely connected subsets of the network, in the rejection of the small world hypothesis.
    Keywords: Boards of directors, small worlds, bipartite graphs, testing, bicliques
    JEL: G34 D85 C63
    Date: 2015

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