nep-net New Economics Papers
on Network Economics
Issue of 2019‒09‒30
four papers chosen by
Pedro CL Souza
University of Warwick

  1. Firms, Failures, and Fluctuations By Daron Acemoglu; Alireza Tahbaz-Salehi
  2. The Economics of Social Data: An Introduction By Dirk Bergemann; Alessandro Bonatti
  3. Corruption Risk in Contracting Markets: A Network Science Perspective By Johannes Wachs; Mih\'aly Fazekas; J\'anos Kert\'esz
  4. Education-occupation mismatch of migrants in the Italian labour market: the effect of social networks By Van Wolleghem, Pierre Georges; De Angelis, Marina; Scicchitano, Sergio

  1. By: Daron Acemoglu (Massachusetts Institute of Technology); Alireza Tahbaz-Salehi (Northwestern University)
    Abstract: This paper develops a theory of firm-level production networks, with firm-specific relationships, endogenous bankruptcies, and market power. Firms in each industry have access to a production technology that uses relationship-specific intermediate inputs produced by their “customized” suppliers, with prices determined via pairwise bargaining between suppliers and customers. Operating the customized technology, however, requires paying fixed costs of entry. Hence, negative shocks can result in a cascade of firm failures in the economy. We establish the existence of an equilibrium and provide comparative static results on how prices, firm failures, and macroeconomic aggregates respond to changes in parameters. We then study how the interplay between firm-level linkages and firm failures shape the propagation of shocks over the economy’s production network. Our theoretical results indicate that understanding network-originated aggregate fluctuations may require moving beyond models of sectoral linkages and focusing on how firm-level interactions can lead to chains of failures.
    Date: 2019
  2. By: Dirk Bergemann (Cowles Foundation, Yale University); Alessandro Bonatti (MIT)
    Abstract: Large internet platforms collect data from individual users in almost every interaction on the internet. Whenever an individual browses a news website, searches for a medical term or for a travel recommendation, or simply checks the weather forecast on an app, that individual generates data. A central feature of the data collected from the individuals is its social aspect. Namely, the data captured from an individual user is not only informative about this speci?c individual, but also about users in some metric similar to the individual. Thus, the individual data is really social data. The social nature of the data generates an informational externality that we investigate in this note.
    Keywords: Individual Data, Social Data, Informational Externality, Internet Platforms, Data Collection, Data Markup
    JEL: D80 D82 D83
    Date: 2019–03
  3. By: Johannes Wachs; Mih\'aly Fazekas; J\'anos Kert\'esz
    Abstract: We use methods from network science to analyze corruption risk in a large administrative dataset of over 4 million public procurement contracts from European Union member states covering the years 2008-2016. By mapping procurement markets as bipartite networks of issuers and winners of contracts we can visualize and describe the distribution of corruption risk. We study the structure of these networks in each member state, identify their cores and find that highly centralized markets tend to have higher corruption risk. In all EU countries we analyze, corruption risk is significantly clustered. However, these risks are sometimes more prevalent in the core and sometimes in the periphery of the market, depending on the country. This suggests that the same level of corruption risk may have entirely different distributions. Our framework is both diagnostic and prescriptive: it roots out where corruption is likely to be prevalent in different markets and suggests that different anti-corruption policies are needed in different countries.
    Date: 2019–09
  4. By: Van Wolleghem, Pierre Georges; De Angelis, Marina; Scicchitano, Sergio
    Abstract: Whilst migration has become a structural feature of most European countries, the integration of foreigners in the labour market continues to raise concerns. Evidence across countries shows that migrants are more often over-educated than natives. Over the last years, scholarship has intended to capture the effect of informal networks on migrants’ over-education. Interestingly, no study has looked into the Italian case, yet a country for which the effect of networks on education-occupation mismatch is well documented. This article has two objectives: it assesses the extent to which over-education affects migrants and it evaluates the role informal networks play in producing it. We find that foreigners are more over-educated than natives but that the role of networks is consistent across the two groups. Empirical evidence is drawn from the application of quantitative and counter-factual methods to PLUS 2018 – Participation, Labour, Unemployment Survey.
    Keywords: Network,Over-education,Migrants,labour market
    JEL: F22 J61 Z13
    Date: 2019

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