nep-net New Economics Papers
on Network Economics
Issue of 2023‒02‒20
nine papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Follow the leader: community-based health insurance in West Africa By Rute M. Caeiro; Alexander Coutts; Teresa Molina-Millan; Pedro C. Vicente
  2. Sparse production networks By Bernard, Andrew B.; Zi, Yuan
  3. Network analysis of the UK reinsurance market By Kotlicki, Artur; Austin, Andrea; Humphry, David; Burnett, Hanna; Ridgill, Philip; Smith, Sam
  4. Climate change concerns and information spillovers from socially-connected friends By Mayer, Maximilian
  5. News Diffusion in Social Networks and Stock Market Reactions By David Hirshleifer; Lin Peng; Qiguang Wang
  6. Drivers of organic farming: Lab-in-the-field evidence of the role of social comparison and information nudge in networks in Vietnam By Kene Boun My; Phu Nguyen-Van; Thi Kim Cuong Pham; Anne Stenger; Tuyen Tiet; Nguyen To-The
  7. Emerging Labour Flow Networks By Kathyrn R. Fair; Omar A. Guerrero
  8. Around Asia in 80 days: Uncovering inter-linked networks in the corporate landscape Keiretsu of Japan By Hoang, Giang
  9. Are groups always more dishonest than individuals? The case of salient negative externalities By Geoffrey Castillo; Lawrence Choo; Veronika Grimm

  1. By: Rute M. Caeiro; Alexander Coutts; Teresa Molina-Millan; Pedro C. Vicente
    Abstract: In this study, we analyze the role of social networks in health insurance adoption in rural Guinea-Bissau. Using detailed social network data, and exploiting the mobilization of local female leaders to promote the insurance scheme, we find that, following the promoters’ intervention, households’ probability of take-up increased by 22 percentage points. Looking at effects along social networks, we find that households well connected to insurance promoters are more likely to adopt if promoters adopt as well. Lastly, our results show that distribution of insurance promotional material by the promoters has a positive effect in households’ adoption and payment of health insurance.
    Keywords: Health insurance, Social networks, Africa
    JEL: O12 I13 D83
    Date: 2022
  2. By: Bernard, Andrew B.; Zi, Yuan
    Abstract: Firm-to-firm connections in domestic and international production networks play a fundamental role in economic outcomes. Firm heterogeneity and the sparse nature of firm-to-firm connections implicitly discipline network structure. We find that a large group of well-established statistical relationships are not useful in improving our understanding of production networks. We propose an "elementary" model for production networks based on random matching and firm heterogeneity and characterize the families of statistics and data generating processes that may raise underidentification concerns in more complex models. The elementary model is a useful benchmark in developing "instructive" statistics and informing model construction and selection.
    Keywords: firm-to-firm networks; model selection; balls-and-bias; buyer-seller matching; underidentification
    JEL: F11 F14
    Date: 2022–10–17
  3. By: Kotlicki, Artur (Bank of England); Austin, Andrea (Australian Energy Regulator); Humphry, David (Bank of England); Burnett, Hanna (Bank of England); Ridgill, Philip (Bank of England); Smith, Sam (Bank of England)
    Abstract: We provide an empirical analysis of the network structure of the UK reinsurance sector based on 2016 Solvency II regulatory data. We examine counterparty credit risk originating from reinsurance contracts as a source of financial contagion in the insurance industry. The granularity of the Solvency II data provides a new opportunity for detailed analysis of the actual exposures in the system, detection of potential systemic vulnerabilities, and reinsurance spirals. In our multi-layered network approach, we incorporate information on reinsurance contract risk types and ownership structure for both life and non-life insurers. Our findings suggest that the UK reinsurance sector exhibits the ‘small-world’ property with a scale-free, core-periphery structure and topological characteristics common to other financial networks. These characteristics of risk dispersion from the periphery to the core make the network ‘robust-yet-fragile’ to financial shocks. We explore the robustness of the network to adverse shocks through a stress-simulation exercise, where we find it robust to system wide shocks affecting the value of total investments, and to idiosyncratic shocks applied to large, highly interconnected reinsurers.
    Keywords: Reinsurance; systemic risk; financial contagion; scale-free network
    JEL: D85 G01 G22 G28
    Date: 2023–01–23
  4. By: Mayer, Maximilian
    Abstract: This paper studies the role of social connections in shaping individuals' concerns about climate change. I combine granular climate data, region-level social network data and survey responses for 24 European countries in order to document large information spillovers. Individuals become more concerned about climate change when their geographically distant friends living in sociallyconnected regions have experienced large increases in temperatures since 1990. Exploring the heterogeneity of the spillover effects, I uncover that the learning via social networks plays a central role. Further, results illustrate the important role of social values and economic preferences for understanding how information spillovers affect individual concerns.
    Keywords: beliefs, climate change, information spillovers, social networks
    JEL: D01 D62 D64 D8 Q5
    Date: 2023
  5. By: David Hirshleifer; Lin Peng; Qiguang Wang
    Abstract: We study how the social transmission of public news influences investors' beliefs and securities markets. Using an extensive dataset to measure investor social networks, we find that earnings announcements from firms in higher-centrality locations generate stronger immediate price and trading volume reactions. Post announcement, such firms experience weaker price drifts but higher and more persistent volume. This evidence suggests that while greater social connectedness facilitates timely incorporation of news into prices, it also triggers opinion divergence and excessive trading. We provide a model of these effects and present further supporting evidence with granular data based on StockTwits messages and household trading records.
    JEL: G11 G12 G14 G4 G41
    Date: 2023–01
  6. By: Kene Boun My (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Phu Nguyen-Van (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, Thang Long University); Thi Kim Cuong Pham (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique); Anne Stenger (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Tuyen Tiet (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Nguyen To-The (Thang Long University, VNU - Vietnam National University [Hanoï])
    Abstract: This study examines factors determining farmers' investment in organic farming using a contextualized lab-in-the-field experiment with 220 small household farmers in Northern Vietnam. We focus on the role of network structure, information nudge, and social comparison between farmers using three types of networks: circle, star and complete. Our results suggest that, on average, around 64% of the land is invested in organic farming in the complete network in which each farmer is connected to all of the others, while only about 57% of the land is invested in the circle and star network. Moreover, social comparison (i.e., information about the average investment) performs better in a circle network than in a star network. Finally, information nudges about the socially optimal investment could encourage farmers' coordination in all three networks, particularly in the complete network with an increase in organic investment up to 76%.
    Keywords: Lab-in-the-field, Network, Nudge, Organic agriculture, Small household farmers, Social comparison.
    Date: 2022
  7. By: Kathyrn R. Fair; Omar A. Guerrero
    Abstract: The study of labour dynamics has led to the introduction of labour flow networks (LFNs) as a way to conceptualise job-to-job flows, and to the development of mathematical models to explore the dynamics of these networked flows. To date, LFN models have relied upon an assumption of static network structure. However, as recent events (increasing automation in the workplace, the COVID-19 pandemic, etc.) have shown, we are experiencing drastic shifts to the job landscape that are altering the ways individuals navigate the labour market. Here we develop a novel model that emerges LFNs from agent-level behaviour, removing the necessity of assuming that future job-to-job flows will be along the same paths where they have been historically observed. This model, informed by microdata for the United Kingdom, generates empirical LFNs with a high level of accuracy. We use the model to explore how shocks impacting the underlying distributions of jobs and wages alter the topology of the LFN. This framework represents a crucial step towards the development of models that can answer questions about the future of work in an ever-changing world.
    Date: 2023–01
  8. By: Hoang, Giang
    Abstract: Zaibatsu, which means “wealthy clique” in Japanese, is any of the large capitalist enterprises of Japan whose influence and control were pervasive from the Meiji period until the end of WWII
    Date: 2023–01–19
  9. By: Geoffrey Castillo (VCEE - Vienna Center for Experimental Economics, University of Vienna); Lawrence Choo (China Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics); Veronika Grimm (FAU - Friedrich-Alexander Universität Erlangen-Nürnberg)
    Abstract: A common finding of the literature on dishonesty is that groups are more dishonest than individuals. We revisit this finding by replacing the experimenter, implicitly hurt by subjects' dishonesty, with an explicit third-party: a local charity. With the charity we do not find groups to be more dishonest than individuals. Instead, groups can even help moderate the extent of the dishonesty.
    Keywords: Dishonesty, Group decisions, Communication, Social norms
    Date: 2022–06

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