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on Network Economics |
| By: | Michael B Devereux (Vancouver school of economics, University of British Columbia, NBER - The National Bureau of Economic Research, CEPR - Center for Economic Policy Research - CEPR); Karine Gente (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Changhua Yu (China Center for Economic Research, National School of Development, Peking University) |
| Abstract: | This paper analyzes the impact of fiscal spending shocks in a dynamic, multi-country model with international production networks. We first derive a decomposition of the effects of a fiscal spending shock on the GDP of any country. This decomposition defines the response as the sum of a Direct, Income, and Price effect. The Direct Effect depends only on structural parameters and is independent of assumptions about monetary policy, wage setting, or capital mobility, while the Price Effect is zero in the aggregate across countries. We apply this decomposition to an analysis of fiscal spillovers in the Eurozone, using the production network structure from the World Input Output Database (WIOD). We find that fiscal spillovers from Germany and some other large Eurozone countries may be large, and within the range of empirical estimates. Without international production network linkages, spillovers would be only a third as large as predicted by the baseline model. Finally, we explore the diffusion of identified government spending shocks at the sectoral level, both within and across countries, using an empirical measure of the response, based on the theoretical decomposition. The empirical estimates are strongly consistent with the theoretical model. |
| Keywords: | Production Network,Fiscal Policy,Spillovers,Eurozone,Nominal Rigidities |
| Date: | 2022–07–13 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03740043&r= |
| By: | Yuhang Guo; Dong Hao; Bin Li |
| Abstract: | This paper studies one emerging procurement auction scenario where the market is constructed over the social networks. In a social network composed of many agents, smartphones or computers, one requester releases her requirement for goods or tasks to suppliers, then suppliers who have entered the market are also encouraged to invite some other suppliers to join and all the suppliers in the network could compete for the business. The key problem for this networked auction is about how to incentivize each node who have entered the sell not only to truthfully use her full ability, but also to forward the task to her neighbours. Auctions conducting over social networks have attracted considerable interests in recent years. However, most of the existing works focus on classic forward auctions. Moreover, there is no existing valid networked auction considering multiple goods/tasks. This work is the first to explore procurement auction for both homogeneous and heterogeneous goods or tasks in social networks. From both theoretical proof and experimental simulation, we proved that the proposed mechanisms are proved to be individual-rational and incentive-compatible, also both the cost of the system and the requester could get decreased. |
| Date: | 2022–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2208.14591&r= |
| By: | Lorenzo Ductor (Department of Economic Theory and Economic History, University of Granada.); Bauke Visser (Erasmus University Rotterdam and Tinbergen Institute) |
| Abstract: | A department’s yearly publication count in a journal increases when a member of the department joins the journal’s editorial board. The common interpretation of this fact—that during the board member’s tenure, departmental colleagues publish more—is inaccurate. In a sample of 106 economics journals covering 1990-2011, we estimate that of the observed increase in the publication count, 73 per cent is (co-)authored by board members themselves. Their single-authored papers in a journal receive significantly less citations if they are on that journal’s editorial board. We find no evidence that they discover attractive papers among their colleagues that otherwise wouldn’t be published. |
| Keywords: | Editorial boards, Networks, Colleague, Coauthor, Rent extraction, Publishing |
| JEL: | A11 A14 O31 |
| Date: | 2022–09–15 |
| URL: | http://d.repec.org/n?u=RePEc:gra:wpaper:22/13&r= |
| By: | Zema, Sebastiano Michele |
| Abstract: | The network structure of non-centrally cleared derivative markets, uncovered via the European Market Infrastructure Regulation (EMIR), is investigated with a focus on the Covid-19 market turmoil period. Initial and variation margin networks are reconstructed to analyze channels of potential losses and liquidity dynamics. Despite the absence of central clearing, the derivative network is found to be ultrasmall and a filtering tool is proposed to identify channels in the network characterized by the highest exposures. I find these exposures to be mainly toward institutions outside the euro-area (EA), emphasizing the need for cooperation across different jurisdictions. Anomalous behavior in terms of diverging first and second moments on the degree and strength distributions are detected, signaling the presence of large exposures generating extreme liquidity outflows. A reference table of parameters’ estimates based on real data is provided for different network sizes, with no break of confidentiality, making possible to simulate in a realistic way the liquidity dynamic in global derivative markets even when the access to supervisory data is not granted. JEL Classification: G01, G15, G23 |
| Keywords: | complex networks, fat-tails, financial derivatives, maximum spanning trees, non-centrally cleared exposures |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20222721&r= |
| By: | Thomas-Agnan, Christine; Margaretic, Paula; Laurent, Thibault |
| Abstract: | We extend the impact decomposition proposed by LeSage and Thomas-Agnan (2015) in the spatialinteraction model to a more general framework, where the sets of origins and destinations can bedifferent, and where the relevant attributes characterizing the origins do not coincide with those of thedestinations. These extensions result in three flow data configurations which we study extensively: thesquare, the rectangular, and the non-cartesian cases. We propose numerical simplifications to computethe impacts, avoiding the inversion of a large filter matrix. These simplifications considerably reducecomputation time; they can also be useful for prediction. Furthermore, we define local measuresfor the intra, origin, destination and network effects. Interestingly, these local measures can beaggregated at different levels of analysis. Finally, we illustrate our methodology in a case study usingremittance flows all over the world. |
| Keywords: | Impact decomposition ; local effects; spatial interaction autoregressive models; non-cartesian flow data |
| JEL: | C13 C31 C46 C51 C65 |
| Date: | 2022–09–13 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:127301&r= |
| By: | Tae-Hwy Lee; Ekaterina Seregina |
| Abstract: | In this paper we develop a novel method of combining many forecasts based on a machine learning algorithm called Graphical LASSO. We visualize forecast errors from different forecasters as a network of interacting entities and generalize network inference in the presence of common factor structure and structural breaks. First, we note that forecasters often use common information and hence make common mistakes, which makes the forecast errors exhibit common factor structures. We propose the Factor Graphical LASSO (Factor GLASSO), which separates common forecast errors from the idiosyncratic errors and exploits sparsity of the precision matrix of the latter. Second, since the network of experts changes over time as a response to unstable environments such as recessions, it is unreasonable to assume constant forecast combination weights. Hence, we propose Regime-Dependent Factor Graphical LASSO (RD-Factor GLASSO) and develop its scalable implementation using the Alternating Direction Method of Multipliers (ADMM) to estimate regime-dependent forecast combination weights. The empirical application to forecasting macroeconomic series using the data of the European Central Bank's Survey of Professional Forecasters (ECB SPF) demonstrates superior performance of a combined forecast using Factor GLASSO and RD-Factor GLASSO. |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2209.01697&r= |
| By: | Sarah Cattan (Institute for Fiscal Studies); Kjell Salvanes (Norges Handelshøyskole); Emma Tominey (University of York) |
| Abstract: | Intergenerational persistence in studying for elite education is high across the world. We study the role that exposure to high school peers from elite educated families (`elite peers') plays in driving such a phenomenon in Norway. Using register data on ten cohorts of high school students and exploiting within school, between cohort variation, we identify the causal impact of elite peers on the probability of enrolling in elite education for students from different socioeconomic (SES) backgrounds. We show that exposure to elite peers in high school does drive enrolment into elite degree programmes, but the effect for low SES students is a third of the size than for high SES students. We explore mechanisms behind this pattern – finding that elite peers have a complex effect on students’ GPA which is a key part of the story. Elite peers increase the effort of both low and high SES students, but they also push the rank of other students down and trigger a change in teacher behaviour which disadvantages low SES students. To quantify the contribution of this mechanism, we perform a causal mediation analysis exploiting a lottery in the assessment system in Norway to instrument GPA. We find that the indirect effect of elite peers on enrolment through GPA explains just less than half of the total peer effect. Our concluding analysis shows that elite peers in high school raises intergenerational mobility for poor students, but increases persistence for rich students, thereby simultaneously facilitating first generation elite whilst contributing to the high intergenerational persistence at the top of the education and income distribution. |
| Keywords: | peers, elite university, subject choice, social mobility, teacher bias |
| JEL: | I24 J24 J62 |
| URL: | http://d.repec.org/n?u=RePEc:hka:wpaper:2022-028&r= |
| By: | Clarissa Caimol (University of Ferrara – Department of Economics and Management (Ferrara, Italy);) |
| Abstract: | The importance of local stakeholders in the regional governments regarding climate change policies has received a deeper attention during the last years, especially include adaptation policies. The achievement of the European targets is the implementation of both mitigation and adaptation policies by providing multiple funds from European to sub-national level. The directives to combat the issues of climate heating system come from the international level to the regional one. However, European regions require a higher level of adaptation than mitigation commitments due to the vulnerability of the territories. This paper applies a network perspective in the Emilia Romagna region to map the level of climate commitment in the local stakeholders’ involvement. These local actors have been clustered to facilitate the investigation in order to uncover the way specific stakeholders has relevant impact on climate change issues. A particular consideration has been given to the degree of participation in adaptation policies |
| Keywords: | climate change, adaptation, local stakeholders, social network analysis, regional policy |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:srt:wpaper:0922&r= |