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on Network Economics |
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Issue of 2018‒04‒09
three papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Hyunju Lee (University of Minnesota); Alessandra Fogli (Minneapolis Federal Reserve Bank) |
| Abstract: | We analyze the geographic dimension of innovation. Innovation is the critical component of long term prosperity and it is unevenly distributed across US. Using data on 1.8 million US patents and their citation properties, we map the innovation network of all major US cities over the last three decades. We find that the innovation gap among cities, which was shrinking until 1980, has recently started growing, generating divergence. We develop a network model of cities that captures the knowledge spillovers within and across industries as well as within and across cities, and calibrate it using information on the patterns of patents citations. We show that the IT revolution, by reducing the cost of information exchange across cities, induced an endogenous response of the network structure of cities. This change in network structure can explain a large part of the recent divergence in innovation patterns across cities, and is consistent with a number of stylized facts about the evolution of US cities over the past thirty years. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed017:1630&r=net |
| By: | Nils Detering; Thilo Meyer-Brandis; Konstantinos Panagiotou; Daniel Ritter |
| Abstract: | We extend analytic large network results on default contagion in random graphs to capture a pronounced Block Model structure. This includes as a special case the Core-Periphery network structure, which plays a prominent role in recent research on systemic risk. Further, in the existing literature on systemic risk using random graph methods the problematic assumption that the distribution of liabilities solely depends on the creditor type seems to persist. Under this assumption a straightforward application of the law of large numbers allows to turn edge related random elements into deterministic vertex properties. Here we study a general setting in which the liabilities may depend on both the creditor and the debtor where this argument breaks down and a direct asymptotic analysis of the edge weighted random graph becomes necessary. Among several other applications our results allow us to obtain resilience conditions for the entire network (for example the global financial network) based only on subnetwork conditions. Contrasting earlier research we also give an example that demonstrates how reshuffling edge weights to form blocks can in fact impact resilience even for otherwise very homogeneous networks. |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1803.08169&r=net |
| By: | Francisco RUGE-MURCIA |
| Abstract: | This paper constructs an asset pricing model where heterogeneous sectors interact with each other in a production network as producers and consumers of materials and investment goods. Idiosyncratic sectoral shocks are transmitted through the network with the dynamics being affected by the heterogeneity in production functions and capital adjustment costs. The model is estimated using sectoral and aggregate U.S. data. Results show that 1) shocks to the primary sector account for a substantial part of the equity premium in all sectors because their volatility is much higher than that of shocks to the other sectors, and 2) the model endogenously generates conditional heteroskedasticity despite the fact that shocks are conditional homoskedatic. These results depend crucially on the presence of network effects. |
| Keywords: | network, input-output, production economy, stock returns, sectoral shocks |
| JEL: | E44 G12 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:mtl:montec:02-2018&r=net |