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on Network Economics |
| By: | Philippe Bich (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Paris 1 Panthéon-Sorbonne, PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Julien Fixary (UP1 - Université Paris 1 Panthéon-Sorbonne, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | We determine the topological structure of the graph of pairwise stable weighted networks. As an application, we obtain that for large classes of polynomial payoff functions, there exists generically an odd number of pairwise stable networks. This improves the results in Bich and Morhaim ([5]) or in Herings and Zhan ([14]), and can be applied to many existing models, as for example to the public good provision model of Bramoullé and Kranton ([8]), the information transmission model of Calvó-Armengol ([9]), the two-way flow model of Bala and Goyal ([2]), or Zenou-Ballester's key-player model ([3]). |
| Keywords: | Weighted Networks,Pairwise Stable Networks Correspondence,Generic oddness |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-03287524&r= |
| By: | Bauer, Kevin; Kosfeld, Michael; von Siemens, Ferdinand |
| Abstract: | We study, theoretically and empirically, the effects of incentives on the self-selection and coordination of motivated agents to produce a social good. Agents join teams where they allocate effort to either generate individual monetary rewards (selfish effort) or contribute to the production of a social good with positive effort complementarities (social effort). Agents differ in their motivation to exert social effort. Our model predicts that lowering incentives for selfish effort in one team increases social good production by selectively attracting and coordinating motivated agents. We test this prediction in a lab experiment allowing us to cleanly separate the selection effect from other effects of low incentives. Results show that social good production more than doubles in the lowincentive team, but only if self-selection is possible. Our analysis highlights the important role of incentives in the matching of motivated agents engaged in social good production. |
| Keywords: | incentives,intrinsic motivation,self-selection,public service |
| JEL: | C91 D90 J24 J31 M52 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safewp:318&r= |
| By: | Roberto Antonietti; Paolo Falbo; Fulvio Fontini; Rosanna Grassi; Giorgio Rizzini |
| Abstract: | International trade is based on a set of complex relationships between different countries that can be modelled as an extremely dense network of interconnected agents. On the one hand, this network might favour the economic growth of countries, but on the other, it can also favour the diffusion of diseases, like the COVID-19. In this paper, we study whether, and to what extent, the topology of the trade network can explain the rate of COVID-19 diffusion and mortality across countries. We compute the countries' centrality measures and we apply the community detection methodology based on communicability distance. Then, we use these measures as focal regressors in a negative binomial regression framework. In doing so, we also compare the effect of different measures of centrality. Our results show that the number of infections and fatalities are larger in countries with a higher centrality in the global trade network. |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2107.14554&r= |
| By: | Laura Alfaro (Harvard Business School & NBER); Ester Faia (Goethe University Frankfurt & CEPR); Nora Lamersdorf (Goethe University Frankfurt); Farzad Saidi (University of Bonn & CEPR) |
| Abstract: | Externalities and social preferences, such as patience and altruism, play a key role in the endogenous choice of social interactions, which in turn affect the diffusion of a pandemic or patterns of social segregation. We build a dynamic model, augmented with an SIR block, in which agents optimally choose the intensity of both general and group-specific social interactions. The equilibria in the baseline and the SIR-network model result from a matching process governed by optimally chosen contact rates. Taking into account agents’ endogenous behavior generates markedly different predictions relative to a naıve SIR model. Through a planner’s problem, we show that neglecting agents’ response to risk leads to misguided policy decisions. Mobility restrictions beyond agents’ restraint are needed to the extent that aggregate externalities are not curtailed by social preferences. |
| Keywords: | social interactions, pandemics, SIR network models, social preferences, social planner, targeted policies |
| JEL: | D62 D64 D85 D91 E70 I10 I18 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ajk:ajkdps:110&r= |
| By: | Emanuela Sirtori (CSIL Centre for Industrial Studies); Alessandra Caputo (CSIL Centre for Industrial Studies); Domenico Scalera (Department of Law and Economics. University of Sannio, Italy) |
| Abstract: | This paper aims at identifying geographical patterns of Biopharma transformation trends in the EU over the period 2000-2016 through an analysis of cross-regional and cross-sectoral linkages. To this purpose, information on co-patenting, mergers and acquisitions, and joint ventures and alliances is used to carry out a network analysis at region level. Results show an increasing involvement of European regions in cross-sectoral Biopharma operations. However, while the network displays a tendency to enlarge toward the East (Poland) and West (Spain), a significant reduction in the activity of peripheral nodes in the Southern and Northern borders of the network is observed. More recently, the overall interconnectedness of the network slightly decreases; the network becomes sparser, showing a propensity toward regionalisation of cross-sectoral linkages. Finally, by exploiting information on the location of companies and inventors involved in cross-sectoral operations, the investigation allows pinpointing regional communities and their evolution throughout the yearsClassification-JEL: O18, R11, R58 |
| Keywords: | Biopharmaceutical industry, Cross-sectoral linkages, Emerging Industries, Network analysis |
| JEL: | R11 R12 L14 L65 |
| Date: | 2021–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:mst:wpaper:202101&r= |
| By: | Stefano Basilico (Friedrich Schiller University Jena, Economics Department); Uwe Cantner (Friedrich Schiller University Jena, Economics Department, and University of Southern Denmark, Odense); Holger Graf (Friedrich Schiller University Jena, Economics Department) |
| Abstract: | Cluster policies aim at improving collaboration between co-located actors to address systemic failures. As yet, cluster policy evaluations are mainly concerned with effects on firm performance. Some recent studies move to the system level by assessing how the structure of actor-based knowledge networks is affected by such policies. We continue in that direction and analyze how technology-based regional knowledge spaces structurally respond to the introduction of a cluster policy. Taking the example of the German BioRegio contest, we examine how such knowledge spaces in winning and non-winning regions evolved before, during and after the policy. Using a difference-in-differences approach, we identify treatment effects of increased knowledge space embeddedness of biotechnology only in the post-treatment period. Our findings imply that cluster policies can have long-term structural effects typically not accounted for in policy evaluations. |
| Keywords: | BioRegio contest, network analysis, knowledge space, difference in differences, patents |
| JEL: | O31 O38 R11 |
| Date: | 2021–08–02 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2021-011&r= |
| By: | Laura Pagani; Giovanni Pica |
| Abstract: | This paper investigates whether exposure to academically gifted peers of the same and opposite gender in primary school (grade 5, at age 10) affects later academic achievement (grade 8, at age 13) and high-school track choice. For identification we exploit random allocation of kids across classes within primary schools. We document that, conditional on primary school fixed effects and grade 8 class fixed effects, as well as on baseline achievement, a higher share of same/opposite-gender high-achievers in math in primary school is related, both for boys and girls, to better/worse later math academic achievement in grade 8 and to a higher/lower probability of choosing a scientific high-school track. We argue that these results are consistent with a role model channel. |
| Keywords: | Peer effects, early education stage, gender-specific effects |
| JEL: | I21 I24 J24 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:mib:wpaper:474&r= |