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on Network Economics |
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Issue of 2018‒07‒23
three papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Bernard, Andrew B.; Moxnes, Andreas |
| Abstract: | Trade occurs between firms both across borders and within countries, and the vast majority of trade transactions includes at least one large firm with many trading partners. This paper reviews the literature on firm-to-firm connections in trade. A growing body of evidence coming from domestic and international transaction data has established empirical regularities which have inspired the development of new theories emphasizing firm heterogeneity among both buyers and suppliers in production networks. Theoretical work has considered both static and dynamic matching environments in a framework of many-to-many matching. The literature on trade and production networks is at an early stage, and there are a large number of unanswered empirical and theoretical questions. |
| Keywords: | international trade; production networks; offshoring; productivity |
| JEL: | F10 F12 F14 L11 L21 |
| Date: | 2018–04–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:88692&r=net |
| By: | Ariah Klages-Mundt; Andreea Minca |
| Abstract: | We develop a model for contagion in reinsurance networks by which primary insurers' losses are spread through the network. Our model handles general reinsurance contracts, such as typical excess of loss contracts. We show that simpler models existing in the literature--namely proportional reinsurance--greatly underestimate contagion risk. We characterize the fixed points of our model and develop efficient algorithms to compute contagion with guarantees on convergence and speed under conditions on network structure. We characterize exotic cases of problematic graph structure and nonlinearities, which cause network effects to dominate the overall payments in the system. We lastly apply our model to data on real world reinsurance networks. Our simulations demonstrate the following: (1) Reinsurance networks face extreme sensitivity to parameters. A firm can be wildly uncertain about its losses even under small network uncertainty. (2) Our sensitivity results reveal a new incentive for firms to cooperate to prevent fraud, as even small cases of fraud can have outsized effect on the losses across the network. (3) Nonlinearities from excess of loss contracts obfuscate risks and can cause excess costs in a real world system. |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1805.12222&r=net |
| By: | Výrost, Tomas; Lyócsa, Štefan; Baumöhl, Eduard |
| Abstract: | In this study, we construct financial networks in which nodes are represented by assets and where edges are based on long-run correlations. We construct four networks (complete graph, a minimum spanning tree, a planar maximally filtered graph, and a threshold significance graph) and use three centrality measures (betweenness, eigenvalue centrality, and the expected force). To improve risk-return characteristics of well-known return maximization and risk minimization benchmark portfolios, we propose simple adjustments to portfolio selection strategies that utilize centralization measures from financial networks. From a sample of 45 assets (stock market indices, bond and money market instruments, commodities, and foreign exchange rates) and from data for 1999 to 2015, we show that irrespective of the network and centrality employed, the proposed network-based asset allocation strategies improve key portfolio return characteristics in an out-of-sample framework, most notably, risk and left-tail risk-adjusted returns. Resolving portfolio model selection uncertainties further improves risk-return characteristics. Improvements made to portfolio strategies based on risk minimization are also robust to transaction costs. |
| Keywords: | networks,portfolio,centrality,risk-return profile |
| JEL: | G10 G11 G15 C61 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:180063&r=net |