nep-net New Economics Papers
on Network Economics
Issue of 2020‒04‒06
ten papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Modeling of the Greek road transportation network using complex network analysis By Dimitrios Tsiotas
  2. Adoption and use of mobile banking by low-income individuals in Senegal By François-Seck Fall; Luis Orozco; Al‐mouksit Akim
  3. Network-Based Measures of Systemic Risk in Korea By Jaewon Choi; Jieun Lee
  4. Experimental Design under Network Interference By Davide Viviano
  5. Centralized vs decentralized markets in the laboratory: The role of connectivity By Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu
  6. For better or for worse mental health? The role of social networks for exogamous older couples By Peter Eibich; Chia Liu
  7. Estimation of dyadic characteristics of family networks using sample data By Skinner, Chris J.; Steele, Fiona
  8. The commuting phenomenon as a complex network: The case of Greece By Dimitrios Tsiotas; Konstantinos Raptopoulos
  9. Network dependence in multi-indexed data on international trade flows By LeSage, James P.; Fischer, Manfred M.
  10. A spatial agent based model for simulating and optimizing networked eco-industrial systems By J. Raimbault; J. Broere; M. Somveille; J. M. Serna; E. Strombom; C. Moore; B. Zhu; L. Sugar

  1. By: Dimitrios Tsiotas
    Abstract: This article studies the interregional Greek road network (GRN) by applying complex network analysis (CNA) and an empirical approach. The study aims to extract the socioeconomic information immanent to the GRN's topology and to interpret the way in which this road network serves and promotes the regional development. The analysis shows that the topology of the GRN is submitted to spatial constraints, having lattice-like characteristics. Also, the GRN's structure is described by a gravity pattern, where places of higher population enjoy greater functionality, and its interpretation in regional terms illustrates the elementary pattern expressed by regional development through road construction. The study also reveals some interesting contradictions between the metropolitan and non-metropolitan (excluding Attica and Thessaloniki) comparison. Overall, the article highlights the effectiveness of using complex network analysis in the modeling of spatial networks and in particular of transportation systems and promotes the use of the network paradigm in the spatial and regional research.
    Date: 2020–03
  2. By: François-Seck Fall (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2J - Université Toulouse - Jean Jaurès - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville); Luis Orozco (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2J - Université Toulouse - Jean Jaurès - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville); Al‐mouksit Akim (World Bank Group, LEDA-DIAL - Développement, Institutions et Modialisation - LEDa - Laboratoire d'Economie de Dauphine - IRD - Institut de Recherche pour le Développement - Université Paris Dauphine-PSL - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The wide use of mobile phones is increasing low-income individuals' access to a large range of services. One of these services is mobile banking (m-banking). Today, m-banking represents a key vector of financial inclusion in many countries in Sub-Saharan Africa, especially in Senegal. Based on technology adoption theories applied to households in developing countries, this paper studies the determinants of the adoption and use of m-banking. We distinguish between possession or adoption from actual use of m-banking and examine the interdependence between these two decisions by using a Heckman sample selection model, through a sample of 1052 individuals in the suburbs of Dakar. Our main results are that the two decisions (adoption and use) are not independent from each other. Individual characteristics, such as education, possession of a bank account, and family network effects, are determinants of the adoption, and age, gender, and being a member of a tontine are determinants of the use. A major result of this study concerns women's low propensity to adopt m-banking because of their low levels of education. However, compared with men, when women adopt m-banking, they have a stronger propensity to use it.
    Keywords: Mobile banking,mobile technologies,technology adoption,financial inclusion,individual characteristics,Senegal
    Date: 2020
  3. By: Jaewon Choi (Gies College of Business, University of Illinois/College of Business, Yonsei University); Jieun Lee (Economic Research Institute, Bank of Korea)
    Abstract: We estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic risk concerns arising from the high concentration of the economy in large business groups and a few export-oriented sectors, we perform three levels of estimation using individual stocks, business groups, and industry returns. Our results show that the measures perform well over our sample period by indicating heightened levels of commonality and interconnectedness during crisis periods. In out-of-sample tests, we show that the measures can predict future losses in the stock market during the crises. We also provide the recent readings of our measures, both at the market, chaebol, and industry levels. The measures indicate systemic risk is currently not a major concern in Korea, as they tend to be at the lowest level since 1998. Systemic risk within-chaebols or within-industries overall has not significantly increased in the recent sub-period. In contrast, commonality within the finance industry has not subsided, which we interpret as capturing the interconnectedness endemic to the finance industry, rather than indicating a heightened systemic risk within the banking sector.
    Keywords: Systemic risk, Network analysis, Korean economy
    JEL: G11 G14 G23
    Date: 2020–03–26
  4. By: Davide Viviano
    Abstract: This paper discusses the problem of the design of experiments under network interference. We allow for a possibly fully connected network and a general class of estimands, which encompasses average treatment and average spillover effects, as well as estimands obtained from interactions of the two. We discuss a near-optimal design mechanism, where the experimenter optimizes over participants and treatment assignments to minimize the variance of the estimators of interest, using a first-wave experiment for estimation of the variance. We guarantee valid asymptotic inference on causal effects using either parametric or non-parametric estimators under the proposed experimental design, allowing for local dependence of potential outcomes, arbitrary dependence of the treatment assignment indicators, and spillovers across units. We showcase asymptotic optimality and finite-sample upper bounds on the regret of the proposed design mechanism. Simulations illustrate the advantage of the method over state-of-art methodologies.
    Date: 2020–03
  5. By: Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu
    Abstract: This paper compares the performance of centralized and decentralized markets experimentally. We constrain trading exchanges to happen on an exogenously predetermined network, representing the trading relationships in markets with differing levels of connectivity. Our experimental results show that, despite having lower trading volumes, decentralized markets are not necessarily less efficient. Although information can propagate quicker through highly connected markets, we show that higher connectivity also induces informed traders to trade faster and exploit further their information advantages before the information becomes fully incorporated into prices. This not only reduces market efficiency, but it also increases wealth inequality. We show that, in more connected markets, informed traders trade not only relatively quicker, but also more, in the right direction, despite not doing it at better prices.
    Keywords: Experiments, financial markets, diffusion of information, decentralized trading.
    JEL: C92 D82 G14
    Date: 2020–02
  6. By: Peter Eibich (Max Planck Institute for Demographic Research, Rostock, Germany); Chia Liu (Max Planck Institute for Demographic Research, Rostock, Germany)
    JEL: J1 Z0
    Date: 2020
  7. By: Skinner, Chris J.; Steele, Fiona
    Abstract: We consider the use of sample survey data to estimate dyadic characteristics of family networks, with an application to non-coresident parent-child dyads. We suppose that survey respondents report either from a parent or child perspective about a dyad, depending on their membership of the dyad. We construct separate estimators of com- mon dyadic characteristics using data from both a parent and a child perspective and show how comparisons of these estimators can shed light on data quality issues including differential missingness and re- porting error. In our application we find that a simple missingness model explains some striking patterns of discrepancies between the estimators and consider the use of poststratification and a related re- definition of count variables to adjust for these discrepancies. We also develop approaches to combining the separate estimators efficiently to estimate means and frequency distributions within subpopulations.
    Keywords: ES/P000118/1
    JEL: C1
    Date: 2019–11–01
  8. By: Dimitrios Tsiotas; Konstantinos Raptopoulos
    Abstract: This article studies the Greek interregional commuting network (GRN) by using measures and methods of complex network analysis and empirical techniques. The study aims to detect structural characteristics of the commuting phenomenon, which are configured by the functionality of the land transport infrastructures, and to interpret how this network serves and promotes the regional development. In the empirical analysis, a multiple linear regression model for the number of commuters is constructed, which is based on the conceptual framework of the term network, in effort to promote the interdisciplinary dialogue. The analysis highlights the effect of the spatial constraints on the network's structure, provides information on the major road transport infrastructure projects that constructed recently and influenced the country capacity, and outlines a gravity pattern describing the commuting phenomenon, which expresses that cities of high population attract large volumes of commuting activity within their boundaries, a fact that contributes to the reduction of their outgoing commuting and consequently to the increase of their inbound productivity. Overall, this paper highlights the effectiveness of complex network analysis in the modeling of spatial and particularly of transportation network and promotes the use of the network paradigm in the spatial and regional research.
    Date: 2020–03
  9. By: LeSage, James P.; Fischer, Manfred M.
    Abstract: In this paper, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiple network interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.
    Keywords: origin-destination panel data ows, cross-sectional dependence, MCMC estimation, log-marginal likelihood, gravity models of trade, sociocultural distance
    Date: 2020–03–30
  10. By: J. Raimbault; J. Broere; M. Somveille; J. M. Serna; E. Strombom; C. Moore; B. Zhu; L. Sugar
    Abstract: Industrial symbiosis involves creating integrated cycles of by-products and waste between networks of industrial actors in order to maximize economic value, while at the same time minimizing environmental strain. In such a network, the global environmental strain is no longer equal to the sum of the environmental strain of the individual actors, but it is dependent on how well the network performs as a whole. The development of methods to understand, manage or optimize such networks remains an open issue. In this paper we put forward a simulation model of by-product flow between industrial actors. The goal is to introduce a method for modelling symbiotic exchanges from a macro perspective. The model takes into account the effect of two main mechanisms on a multi-objective optimization of symbiotic processes. First it allows us to study the effect of geographical properties of the economic system, said differently, where actors are divided in space. Second, it allows us to study the effect of clustering complementary actors together as a function of distance, by means of a spatial correlation between the actors' by-products. Our simulations unveil patterns that are relevant for macro-level policy. First, our results show that the geographical properties are an important factor for the macro performance of symbiotic processes. Second, spatial correlations, which can be interpreted as planned clusters such as Eco-industrial parks, can lead to a very effective macro performance, but only if these are strictly implemented. Finally, we provide a proof of concept by comparing the model to real world data from the European Pollutant Release and Transfer Register database using georeferencing of the companies in the dataset. This work opens up research opportunities in interactive data-driven models and platforms to support real-world implementation of industrial symbiosis.
    Date: 2020–03

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