nep-net New Economics Papers
on Network Economics
Issue of 2021‒05‒03
eight papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Social Networks with Mismeasured Links By Arthur Lewbel; Xi Qu; Xun Tang
  2. Financial Risk Meter based on expectiles By Ren, Rui; Lu, Meng-Jou; Li, Yingxing; Härdle, Wolfgang
  3. Control and Spread of Contagion in Networks By John Higgins; Tarun Sabarwal
  4. Regshock: Interactive Visual Analytics of Systemic Risk in Financial Networks By Zhibin Niu; Junqi Wu; Dawei Cheng; Jiawan Zhang
  5. Do High Schools Choose Financial Education Policies Based on Their Neighbors? By Luedtke, Allison Oldham; Urban, Carly
  6. Breaking Bad: Supply Chain Disruptions in a Streamlined Agent Based Model By Domenico Delli Gatti; Elisa Grugni
  7. A Multiperiod Consensus-Based Transactive Energy System for Unbalanced Distribution Networks By Cheng, Rui; Tesfatsion, Leigh; Wang, Zhaoyu
  8. Improved selection of critical network elements for flow-based market coupling based on congestion patterns By Schönheit, David; Bruninx, Kenneth; Kenis, Michiel; Möst, Dominik

  1. By: Arthur Lewbel (Boston College); Xi Qu (Shanghai Jiao Tong University); Xun Tang (Rice University)
    Abstract: We consider estimation of peer effects in social network models where some network links are incorrectly measured. We show that if the number of mismeasured links does not grow too quickly with the sample size, then standard instrumental variables estimators that ignore the measurement error remain consistent, and standard asymptotic inference methods remain valid. These results hold even when measurement errors in the links are correlated with regressors, or with the model errors. Monte Carlo simulations and real data experiments confirm our results in finite samples. These findings imply that researchers can ignore small amounts of measurement errors in networks.
    Keywords: Social networks, Peer e§ects, MisclassiÖed links, Missing links, Mismeasured network
    JEL: C31 C51
    Date: 2021–04–28
  2. By: Ren, Rui; Lu, Meng-Jou; Li, Yingxing; Härdle, Wolfgang
    Abstract: The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of expectiles, thus indicating not only the tail probability but rather the actual tail loss given a stress situation in the network. The expectile variant of the FRM enjoys several advantages: Firstly, the coherent and multivariate tail risk indicator conditional expectile-based VaR (CoEVaR) can be derived, which is sensitive to the magnitude of extreme losses. Next, FRM index is not restricted to an index compared to the quantile based FRM mechanisms, but can be expanded to a set of systemic tail risk indicators, which provide investors with numerous tools in terms of diverse risk preferences. The power of FRM also lies in displaying FRM distribution across various entities every day. Two distinct patterns can be discovered under high stress and during stable periods from the empirical results in the United States stock market. Furthermore, the framework is able to identify individual risk characteristics and capture spillover effects in a network.
    Keywords: expectiles,EVaR,CoEVaR,expectile lasso regression,network analysis,systemicrisk,Financial Risk Meter
    JEL: C00
    Date: 2021
  3. By: John Higgins (Department of Economics, University of Kansas, Lawrence, KS 66045, USA); Tarun Sabarwal (Department of Economics, University of Kansas, Lawrence, KS 66045, USA)
    Abstract: We study proliferation of an action in a network coordination game that is generalized to include a tractable, model-based measure of virality to make it more realistic. We present new algorithms to compute contagion thresholds and equilibrium depth of contagion and prove their theoretical properties. These algorithms apply to arbitrary connected networks and starting sets, both with and without virality. Our algorithms are easy to implement and help to quantify relationships previously inaccessible due to computational intractability. Using these algorithms, we study the spread of contagion in scale-free networks with 1,000 players using millions of Monte Carlo simulations. Our results highlight channels through which contagion may spread in networks. Small starting sets lead to greater depth of contagion in less connected networks. Virality amplifies the effect of a larger starting set and may make full network contagion inevitable in cases where it would not occur otherwise. It also brings contagion dynamics closer to a type of singularity. Our model and analysis can be used to understand potential consequences of policies designed to control or spread contagion in networks.
    JEL: C62 C72
    Date: 2021–04
  4. By: Zhibin Niu; Junqi Wu; Dawei Cheng; Jiawan Zhang
    Abstract: Financial regulatory agencies are struggling to manage the systemic risks attributed to negative economic shocks. Preventive interventions are prominent to eliminate the risks and help to build a more resilient financial system. Although tremendous efforts have been made to measure multi-risk severity levels, understand the contagion behaviors and other risk management problems, there still lacks a theoretical framework revealing what and how regulatory intervention measurements can mitigate systemic risk. Here we demonstrate regshock, a practical visual analytical approach to support the exploration and evaluation of financial regulation measurements. We propose risk-island, an unprecedented risk-centered visualization algorithm to help uncover the risk patterns while preserving the topology of financial networks. We further propose regshock, a novel visual exploration and assessment approach based on the simulation-intervention-evaluation analysis loop, to provide a heuristic surgical intervention capability for systemic risk mitigation. We evaluate our approach through extensive case studies and expert reviews. To our knowledge, this is the first practical systemic method for the financial network intervention and risk mitigation problem; our validated approach potentially improves the risk management and control capabilities of financial experts.
    Date: 2021–04
  5. By: Luedtke, Allison Oldham (St. Olaf College); Urban, Carly (Montana State University)
    Abstract: Financial Education courses required for high school graduation make a difference in students' future financial lives. Given that schools exercise local control, there are a variety of types of courses offered and required by US high schools. It remains unclear why and where this variation exists. Using a novel data set of unique high school personal finance course offerings and requirements paired with distances between high schools in the US, we approximate a network of nearby peer high schools. We use this network of peer schools to measure the potential influence of nearby schools on an individual high school's decision to offer financial education courses. We find that high schools are more likely to require or offer financial education courses similar to those of their peer schools. Having an additional peer that incorporates financial education into their curriculum makes it more likely a high school will change their curriculum to do the same. This is true across types of courses: required standalone courses, required courses that incorporate but do not solely focus on personal finance, and standalone electives. The results indicate that schools' nearby peers are related to what types of services to offer their students, and these networks are more predictive than economic or demographic characteristics of the school in determining personal finance course requirements. Local networks can potentially provide momentum in expanding access to financial education.
    Keywords: financial education, financial literacy, networks
    JEL: G53 I20 L14
    Date: 2021–04
  6. By: Domenico Delli Gatti; Elisa Grugni
    Abstract: We explore the macro-financial consequences of the disruption of a supply chain in an agent based framework characterized by two networks, a credit network connecting banks and firms and a production network connecting upstream and down-stream firms. We consider two scenarios. In the first one, because of the lockdown all the upstream firms are forced to cut production. This generates a sizable down-turn during the lockdown due to the indirect effects of the shock (network based financial accelerator). In the second scenario, only those upstream firms located in the “red zone” are forced to contract production. In this case the recession is milder and the recovery begins earlier. Upstream firms hit by the shock, in fact, will be abandoned by their customers who will switch to suppliers who are located outside the red zone. In this way firms endogenously reconstruct (at least in part) the supply chain after the disruption. This is the main determinant of the mitigated impact of the shock in the “red zone” type of lockdown.
    Keywords: supply chain disruption, agent based macroeconomic model
    JEL: E17 E44 E70
    Date: 2021
  7. By: Cheng, Rui; Tesfatsion, Leigh; Wang, Zhaoyu
    Abstract: This study develops a consensus-based transactive energy system design managed by an independent distribution system operator (DSO) for an unbalanced radial distribution network. The network is populated by welfare-maximizing customers with price-sensitive and fixed (non-price-sensitive) demands who make multiple successive power decisions during each real-time operating period OP. The DSO and customers engage in an iterative negotiation process in advance of each OP to determine retail price-to-go sequences for OP that align customer power decisions with network reliability constraints in a manner that respects customer privacy. The convergence properties of a dual decomposition algorithm developed to implement this negotiation process are analytically established. A case study is presented for an unbalanced 123-bus radial distribution network populated by household customers that demonstrates the practical effectiveness of the design.
    Date: 2021–04–23
  8. By: Schönheit, David; Bruninx, Kenneth; Kenis, Michiel; Möst, Dominik
    Abstract: Flow-based market coupling provides zonal day-ahead markets with appropriate signals of possible real-time congestions by incorporating information on local load and generation patterns. It relies on predictive parameters, notably the base case and generation shift keys. Also it only monitors part of the grid, through selecting critical network elements. In consequence, it naturally falls short of a nodal pricing-based cost-optimal solution. Based on a test network with three flow-based market coupling zones, we show that the results of flow-based market coupling converge to nodal pricing solutions with an increasing amount of re-configured market zones. We identify if re-configured market zones can help to improve the selection of critical network elements and lead to cost reductions even in the original market zone setting. We find that around 90% of the cost reductions from a market zone re-configuration can be maintained when the critical network elements, obtained from the re-configured market zones, are used for the original market zones. This is a strong indication that, both in reality as well as model-based research of flow-based market coupling, the selection of critical network elements should be based on expected congestion patterns. To find these congestions, we conduct a nodal price-based market zone re-configuration that helps to identify lines with different congestion signals. This approach can constitute a helpful addition to static and assumption-based selection criteria for critical network elements, such as the often-used zone-to-zone power transfer distribution factors that strongly rely on assumptions like generation shift keys.
    Keywords: critical network elements,flow-based market coupling,market zones,nodal and zonal markets,zone re-configuration
    JEL: C61 D47 L94 Q41 Q43 Q47
    Date: 2021

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