|
on Network Economics |
| By: | Joel P. Flynn; Christina Patterson; John Sturm |
| Abstract: | Advanced economies feature complicated networks that connect households, firms, and regions. How do these structures affect the impact of fiscal policy and its optimal targeting? We study these questions in a model with input-output linkages, regional structure, and household heterogeneity in MPCs, consumption baskets, and shock exposures. Theoretically, we derive estimable formulae for the effects of fiscal policies on aggregate GDP, or fiscal multipliers, and show how network structures determine their size. Empirically, we find that multipliers vary substantially across policies, so targeting is important. Beneath these aggregate effects are large spatial and sectoral spillovers from policies directed to any one firm or household. However, virtually all variation in multipliers stems from differences in policies’ direct incidence onto households’ MPCs. Thus, while the distributional effects of fiscal policy depend on the detailed structure of the economy, maximally expansionary fiscal policy simply targets households’ MPCs. |
| JEL: | E62 |
| Date: | 2021–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:29619&r= |
| By: | Giammetti, Raffaele; Papi, Luca; Teobaldelli, Desiree; Ticchi, Davide |
| Abstract: | This paper investigates the effects of a retreat from global economic integration on the European regional production network for the period 2000-2010. We find that production has become increasingly fragmented, although the degree of heterogeneity across regions is substantial. This heterogeneity is also present in the direct and indirect effects of three different deglobalisation scenarios that we simulate. Our results show that deglobalisation generates winners and losers. Specifically, two groups of regions emerge; regions that would benefit from a return to a less integrated world, and regions that would instead gain from a strengthening of the European production network. |
| Keywords: | Reshoring, Global Value Chains, production networks, input-output, regional fragmentation, supply chains interruption. |
| JEL: | D57 F16 F62 F66 |
| Date: | 2021–12–16 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:111135&r= |
| By: | Wang, Xingang (University of Auckland); Maani, Sholeh A. (University of Auckland) |
| Abstract: | The conventional model of immigrant earnings does not account for the correlation of outcomes across immigrant ethnic networks. We apply a spatial autoregressive network approach to account for the spill-over effects of migrant ethnic group economic resources and labour market outcomes. We employ unit-record data across 10 years for New Zealand, a major immigrant receiving country. By applying generalised method of moment (GMM) estimation, we address endogeneity of the spatial network variable. Results confirm strong positive associations of earnings with both ethnic concentration and networks of resources. The analytically enhanced approach provides opportunities for new research on the determinants of immigrant earnings. |
| Keywords: | earnings, ethnic network, immigrant, spatial autoregressive model, GMM estimation |
| JEL: | J30 J31 Z13 Z18 |
| Date: | 2021–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp14862&r= |
| By: | Michel Grabisch (Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne, Paris School of Economics); Antoine Mandel (Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne, Paris School of Economics); Agnieszka Rusinowska (Centre d'Economie de la Sorbonne, CNRS, Paris School of Economics) |
| Abstract: | We propose a model of the joint evolution of opinions and social relationships in a setting where social influence decays over time. The dynamics are based on bounded confidence: social connections between individuals with distant opinions are severed while new connections are formed between individuals with similar opinions. Our model naturally gives raise to strong diversity, i.e., the persistence of heterogeneous opinions in connected societies, a phenomenon that most existing models fail to capture. the intensity of social interactions is the key parameter that governs the dynamics. First, it determines the asymptotic distributionn of opinions. In particular, increasing the intensity of social interactions brings society closer to consensus. Second, it determines the risk of polariztion, which is shown to increase with the intensity of social interactions. Our results allow to frame the problem of the design of public debates in a formal setting. We hence characterize the optimal strategy for a social planner who controls the intensity of the public debate and thus faces a trade-off between the pursuit of social consensus and the risk of polarization. We also consider applications to political campaigning and show that both minority and majority candidates can have incentives to lead society towards polarization |
| Keywords: | opinion dynamics; network formation; network fragility; polarization; institution design; political campaign |
| JEL: | D85 C65 D83 |
| Date: | 2022–01 |
| URL: | https://d.repec.org/n?u=RePEc:mse:cesdoc:22001&r= |
| By: | Bertogg, Ariane; Koos, Sebastian |
| Abstract: | Contact restrictions and distancing measures are among the most effective non-pharmaceutical measures to stop the spread of the SARS-CoV2 virus. Yet, research has only begun to understand the wider social consequences of these interventions. This study investigates how individuals' social networks have changed since the outbreak of the pandemic and how these changes relate to psychological strain. Based on an online survey of the German adult population, four types of change are distinguished: loss, gain, and intensification of ties, as well as pandemic-related conflicts. One in two respondents has experienced at least one of these four changes. Loss is more frequently reported than gain of ties, and intensification occurred more frequently than conflicts. Loss of ties and conflicts are furthermore associated with higher levels of psychological strain. |
| Keywords: | Network Change,Social Ties,Health Risks,Covid-19 |
| JEL: | L14 I31 |
| Date: | 2021 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:cexwps:07&r= |
| By: | Phu Nguyen-Van (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, TIMAS, Thang Long University); Anne Stenger (BETA - Bureau d'Économie Théorique et Appliquée - 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 - 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, University of Management and Technology [Hanoi]) |
| Abstract: | Based on a meta-analysis, this paper highlights the strength and relevance of several social incentive factors concerning pro-environmental behaviors, including social influence, network factors (like network size, network connection and leadership), trust in others, and trust in institutions. Firstly, our results suggest that social influence is necessary for the emergence of pro-environmental behaviors. More specifically, an internal social influence (i.e., motivating people to change their perceptions and attitudes) is essential to promote pro-environmental behaviors. Secondly, network connection encourages pro-environmental behaviors, meaning that the effectiveness of a conservation policy can be improved if connections among individuals are increased. Finally, trust in institutions can dictate individual behaviors to shape policy design and generate desired policy outcomes. |
| Keywords: | Trust, Social incentive, Social influence, Pro-environmental behavior, Network, Meta-analysis |
| Date: | 2021–12–08 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-03472060&r= |
| By: | Ernest Liu; Song Ma |
| Abstract: | We study the optimal allocation of R&D resources in an endogenous growth model with an innovation network, through which one sector’s past innovations may benefit other sectors’ future innovations. First, we provide closed-form sufficient statistics for the optimal path of R&D resource allocation, and we show that planners valuing long-term growth should allocate more R&D toward key sectors that are upstream in the innovation network. Second, we extend to an open-economy setting and illustrate an incentive for countries to free-ride on fundamental technologies: an economy more reliant on foreign knowledge spillovers has less incentive to direct resources toward innovation-upstream sectors, leading to cross-country differences in unilaterally optimal R&D allocations across sectors. Third, we build the global innovation network based on over 30 million global patents and establish its empirical importance for knowledge spillovers. Fourth, we apply the model to evaluate R&D allocations across countries and time. Adopting optimal R&D allocations can generate substantial welfare improvements across the globe. For the United States, R&D misallocation accounts for about 0.68 percentage points of missing annual growth since the 2000s. |
| JEL: | F43 O33 O38 |
| Date: | 2021–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:29607&r= |
| By: | Christis Katsouris |
| Abstract: | We propose a novel risk matrix to characterize the optimal portfolio choice of an investor with tail concerns. The diagonal of the matrix contains the Value-at-Risk of each asset in the portfolio and the off-diagonal the pairwise Delta-CoVaR measures reflecting tail connections between assets. First, we derive the conditions under which the associated quadratic risk function has a closed-form solution. Second, we examine the relationship between portfolio risk and eigenvector centrality. Third, we show that portfolio risk is not necessarily increasing with respect to stock centrality. Forth, we demonstrate under certain conditions that asset centrality increases the optimal weight allocation of the asset to the portfolio. Overall, our empirical study indicates that a network topology which exhibits low connectivity is outperformed by high connectivity based on a Sharpe ratio test. |
| Date: | 2021–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2112.12031&r= |