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on Network Economics |
| By: | Andrea Gabrielli; Valentina Macchiati; Diego Garlaschelli |
| Abstract: | The structure of many financial networks is protected by privacy and has to be inferred from aggregate observables. Here we consider one of the most successful network reconstruction methods, producing random graphs with desired link density and where the observed constraints (related to the market size of each node) are replicated as averages over the graph ensemble, but not in individual realizations. We show that there is a minimum critical link density below which the method exhibits an `unreconstructability' phase where at least one of the constraints, while still reproduced on average, is far from its expected value in typical individual realizations. We establish the scaling of the critical density for various theoretical and empirical distributions of interbank assets and liabilities, showing that the threshold differs from the critical densities for the onset of the giant component and of the unique component in the graph. We also find that, while dense networks are always reconstructable, sparse networks are unreconstructable if their structure is homogeneous, while they can display a crossover to reconstructability if they have an appropriate core-periphery or heterogeneous structure. Since the reconstructability of interbank networks is related to market clearing, our results suggest that central bank interventions aimed at lowering the density of links should take network structure into account to avoid unintentional liquidity crises where the supply and demand of all financial institutions cannot be matched simultaneously. |
| Date: | 2023–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2305.17285&r=net |
| By: | Julliard, Christian; Shi, Ran; Yuan, Kathy |
| Abstract: | We generalise a stochastic version of the workhorse SIR (Susceptible-Infectious-Removed) epidemiological model to account for spatial dynamics generated by network interactions. Using the London metropolitan area as a salient case study, we show that commuter network externalities account for about 47% of the propagation of COVID-19. We find that the UK lockdown measure reduced total propagation by 44%, with more than one third of the effect coming from the reduction in network externalities. Counterfactual analyses suggest that: the lockdown was somehow late, but further delay would have had more extreme consequences; a targeted lockdown of a small number of highly connected geographic regions would have been equally effective, arguably with significantly lower economic costs; targeted lockdowns based on threshold number of cases are not effective, since they fail to account for network externalities. |
| Keywords: | COVID-19; networks; key players; spatial modelling; SIR model; Elsevier deal |
| JEL: | I18 C51 D85 |
| Date: | 2023–08–01 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:118825&r=net |
| By: | Hassan Afrouzi; Saroj Bhattarai |
| Abstract: | We derive closed-form solutions and sufficient statistics for inflation and GDP dynamics in multi-sector New Keynesian economies with arbitrary input-output linkages. Analytically, we decompose how production linkages (1) amplify the persistence of inflation and GDP responses to monetary and sectoral shocks and (2) increase the pass-through of sectoral shocks to aggregate inflation. Quantitatively, we confirm the significant role of production networks in shock propagation, emphasizing the disproportionate effects of sectors with large input-output adjusted price stickiness: The three sectors with the highest contribution to the persistence of aggregate inflation have consumption shares of around zero but explain 16% of monetary non-neutrality. |
| Keywords: | production networks, multi-sector model, sufficient statistics, inflation dynamics, real effects of monetary policy, sectoral shocks |
| JEL: | E32 E52 C67 |
| Date: | 2023 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_10416&r=net |
| By: | Alexander M. Petersen; Felber Arroyave; Fabio Pammolli |
| Abstract: | A recent analysis of scientific publication and patent citation networks by Park et al. (Nature, 2023) suggests that publications and patents are becoming less disruptive over time. Here we show that the reported decrease in disruptiveness is an artifact of systematic shifts in the structure of citation networks unrelated to innovation system capacity. Instead, the decline is attributable to 'citation inflation', an unavoidable characteristic of real citation networks that manifests as a systematic time-dependent bias and renders cross-temporal analysis challenging. One driver of citation inflation is the ever-increasing lengths of reference lists over time, which in turn increases the density of links in citation networks, and causes the disruption index to converge to 0. A second driver is attributable to shifts in the construction of reference lists, which is increasingly impacted by self-citations that increase in the rate of triadic closure in citation networks, and thus confounds efforts to measure disruption, which is itself a measure of triadic closure. Combined, these two systematic shifts render the disruption index temporally biased, and unsuitable for cross-temporal analysis. The impact of this systematic bias further stymies efforts to correlate disruption to other measures that are also time-dependent, such as team size and citation counts. In order to demonstrate this fundamental measurement problem, we present three complementary lines of critique (deductive, empirical and computational modeling), and also make available an ensemble of synthetic citation networks that can be used to test alternative citation-based indices for systematic bias. |
| Date: | 2023–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2306.01949&r=net |
| By: | Fernando E. Alvarez; David Argente; Francesco Lippi; Esteban Méndez; Diana Van Patten |
| Abstract: | This paper develops a dynamic model of technology adoption featuring strategic complementarities: the benefits of usage increase with the number of adopters. We study the diffusion of new means of payments, where such complementarities are pervasive. We show that complementarities give rise to multiple equilibria, suboptimal allocations, and study the planner’s problem. The model generates gradualism in adoption, as individuals optimally wait for others to adopt before doing so. We apply the theory to the adoption of SINPE, an electronic peer-to-peer (P2P) payment app developed by the Central Bank of Costa Rica. Transaction-level data on the use of SINPE and several administrative data sets on the network structure allow us to exploit plausibly exogenous variation and to document sizable complementarities. A calibrated version of the model shows that the optimal subsidy pushes the economy to universal adoption. |
| JEL: | O1 O2 |
| Date: | 2023–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:31280&r=net |
| By: | Yoshimichi Murakami (Research Institute for Economics and Business Administration, Kobe University, JAPAN) |
| Abstract: | This study analyzes the causal effects of the depth of regional trade agreements (RTAs) measured by the coverage and legal enforceability of WTO-plus and WTO-extra policy areas on the production networks trade in all 33 Latin American and Caribbean (LAC) countries from 1990 to 2016, using a structural gravity model. The study constructs a unique dataset on the indexes of the depth, breadth, and core depth of all RTAs in force that include at least two LAC countries, based on a World Bank database on RTAs’ contents. Results indicate that both depth and breadth of RTAs have positive effects on the intra-regional parts and components exports in the LAC region. However, the effects are substantially heterogeneous by the type of agreements and the characteristics of country-pairs. The depth of custom unions among Latin American countries, mainly the Southern Common Market (MERCOSUR), has positive effects, whereas the depth and breadth of plurilateral free trade agreements with developed countries outside the region (e.g., the United States or European countries) have negative effects. These findings are robust to the use of the mirror import data, the use of three-year interval data, and the inclusion of future values that controls for reverse causality. |
| Keywords: | Depth and breadth of regional trade agreements; Parts and components exports; Heterogeneous effects; Latin American and Caribbean countries; Structural gravity model |
| JEL: | F13 F14 F15 O54 |
| Date: | 2023–03 |
| URL: | https://d.repec.org/n?u=RePEc:kob:dpaper:dp2023-09&r=net |