nep-net New Economics Papers
on Network Economics
Issue of 2023‒11‒13
eight papers chosen by
Alfonso Rosa García, Universidad de Murcia

  1. Measuring income inequality in social networks By Stark, Oded; Bielawski, Jakub; Falniowski, Fryderyk
  2. Identification and Estimation of a Semiparametric Logit Model using Network Data By Brice Romuald Gueyap Kounga
  3. Ring-fencing in financial networks By Bardoscia, Marco; Ka-Kay Pang, Raymond
  4. Cross-covariance isolate detect: a new change-point method for estimating dynamic functional connectivity By Anastasiou, Andreas; Cribben, Ivor; Fryzlewicz, Piotr
  5. Are sanctions for losers? A network study of trade sanctions By Fabio Ashtar Telarico
  6. The Belgian business-to-business transactions dataset 2002-2021 By Cédric Duprez; Emmanuel Dhyne; Toshiaki Komatsu
  7. The Aggregate Effects of Sectoral Shocks in an Open Economy By Philippe Andrade; Martin Arazi; Viacheslav Sheremirov
  8. Social Ties at Work and Effort Choice: Experimental Evidence from Tanzania By Martin Chegere; Paolo Falco; Andreas Menzel

  1. By: Stark, Oded; Bielawski, Jakub; Falniowski, Fryderyk
    Abstract: We present a new index for measuring income inequality in networks. The index is based on income comparisons made by the members of a network who are linked with each other by direct social connections. To model the comparisons, we compose a measure of relative deprivation for networks. We base our new index on this measure. The index takes the form of a ratio: the network’s aggregate level of relative deprivation divided by the aggregate level of the relative deprivation of a hypothetical network in which one member of the network receives all the income, and it is with this member that the other members of the network compare their incomes. We discuss the merits of this representation. We inquire how changes in the composition of a network affect the index. In addition, we show how the index accommodates specific network characteristics.
    Keywords: Food Security and Poverty, Research Methods/ Statistical Methods
    Date: 2023–10–31
  2. By: Brice Romuald Gueyap Kounga
    Abstract: This paper studies the identification and estimation of a semiparametric binary network model in which the unobserved social characteristic is endogenous, that is, the unobserved individual characteristic influences both the binary outcome of interest and how links are formed within the network. The exact functional form of the latent social characteristic is not known. The proposed estimators are obtained based on matching pairs of agents whose network formation distributions are the same. The consistency and the asymptotic distribution of the estimators are proposed. The finite sample properties of the proposed estimators in a Monte-Carlo simulation are assessed. We conclude this study with an empirical application.
    Date: 2023–10
  3. By: Bardoscia, Marco (Bank of England); Ka-Kay Pang, Raymond (London School of Economics and Political Sciences)
    Abstract: Ring-fencing is a reform of the UK banking system that requires large banks to separate their retail services from other activities of the group, such as investment banking. We consider a network of bilateral exposures between banks in which financial contagion can spread because banks incorporate the creditworthiness of their counterparties into the valuation of their assets. Ring-fencing acts as an exogenous shock that impacts the creditworthiness of banks through leverage, depending on how assets are allocated between ring-fenced and non-ring-fenced entities. We find conditions on this allocation that leads to safer ring-fenced entities and less safe non-ring-fenced entities when compared with their groups prior to the implementation of ring-fencing. We also show that ring-fencing can make both the equity of individual banking groups and the aggregate equity of the banking system decrease. When this happens, ring-fenced entities are safer than their groups prior to ring-fencing.
    Keywords: Ring-fencing; financial networks; systemic risk
    JEL: G21 G28
    Date: 2023–10–19
  4. By: Anastasiou, Andreas; Cribben, Ivor; Fryzlewicz, Piotr
    Abstract: Evidence of the non stationary behavior of functional connectivity (FC) networks has been observed in task based functional magnetic resonance imaging (fMRI) experiments and even prominently in resting state fMRI data. This has led to the development of several new statistical methods for estimating this time-varying connectivity, with the majority of the methods utilizing a sliding window approach. While computationally feasible, the sliding window approach has several limitations. In this paper, we circumvent the sliding window, by introducing a statistical method that finds change-points in FC networks where the number and location of change-points are unknown a priori. The new method, called cross-covariance isolate detect (CCID), detects multiple change-points in the second-order (cross-covariance or network) structure of multivariate, possibly high-dimensional time series. CCID allows for change-point detection in the presence of frequent changes of possibly small magnitudes, can assign change-points to one or multiple brain regions, and is computationally fast. In addition, CCID is particularly suited to task based data, where the subject alternates between task and rest, as it firstly attempts isolation of each of the change-points within subintervals, and secondly their detection therein. Furthermore, we also propose a new information criterion for CCID to identify the change-points. We apply CCID to several simulated data sets and to task based and resting state fMRI data and compare it to recent change-point methods. CCID may also be applicable to electroencephalography (EEG), magentoencephalography (MEG) and electrocorticography (ECoG) data. Similar to other biological networks, understanding the complex network organization and functional dynamics of the brain can lead to profound clinical implications. Finally, the R package ccid implementing the method from the paper is available from CRAN.
    Keywords: fMRI; dynamic functional connectivity; change-point analysis; networks; time varying connectivity
    JEL: C1
    Date: 2022–01–01
  5. By: Fabio Ashtar Telarico
    Abstract: Studies built on dependency and world-system theory using network approaches have shown that international trade is structured into clusters of 'core' and 'peripheral' countries performing distinct functions. However, few have used these methods to investigate how sanctions affect the position of the countries involved in the capitalist world-economy. Yet, this topic has acquired pressing relevance due to the emergence of economic warfare as a key geopolitical weapon since the 1950s. And even more so in light of the preeminent role that sanctions have played in the US and their allies' response to the Russian-Ukrainian war. Applying several clustering techniques designed for complex and temporal networks, this paper shows that a shift in the pattern of commerce away from sanctioning countries and towards neutral or friendly ones. Additionally, there are suggestions that these shifts may lead to the creation of an alternative 'core' that interacts with the world-economy's periphery bypassing traditional 'core' countries such as EU member States and the US.
    Date: 2023–10
  6. By: Cédric Duprez (Economics and Research Department, National Bank of Belgium and University of Mons); Emmanuel Dhyne (Economics and Research Department, National Bank of Belgium and University of Mons); Toshiaki Komatsu (Economics and Research Department, National Bank of Belgium and University of Chicago)
    Abstract: This paper provides an updated overview of the network of Belgian business-to-business transactions from 2002 to 2021, building on the previous vintage of the dataset which covered 2002-2014. Leveraging data from VAT client lists, we establish a comprehensive and cohesive database detailing the values of transactions between non-financial corporations in Belgium. This database encompasses all sectors, ranging from primary industries, manufacturing and utilities to construction, business services and other services. With its unmatched breadth at the level of individual firms and panel dimensionality, the dataset facilitates diverse research inquiries in areas such as industrial organisation, international trade, and network theory. To give readers a clearer picture, this paper also highlights several key insights about the Belgian network. Due to the confidential nature of the data, access to this dataset is restricted to NBB staff members.
    Keywords: Firm-Level Analysis, networks, VAT transactions, firm-to-firm linkages
    JEL: C67 C81 L23
    Date: 2023–10
  7. By: Philippe Andrade; Martin Arazi; Viacheslav Sheremirov
    Abstract: We study the aggregate effects of sectoral productivity shocks in a multisectoral New Keynesian open-economy model that allows for asymmetric input-output linkages, both within and between countries, as well as for heterogeneity in sectoral Calvo-type price stickiness. Asymmetries in the international production network play a key role in the model’s ability to produce large domestic effects of foreign sectoral supply shocks and large differential effects of domestic shocks and global shocks. Larger trade openness and substitutability between domestic inputs and foreign inputs can also significantly amplify the effects of foreign and global sectoral shocks on domestic aggregates. In comparison, sectoral heterogeneity in price stickiness does not materially amplify the domestic responses to productivity shocks that originate abroad.
    Keywords: international input-output linkages; sectoral shocks; Open-Economy New Keynesian Model
    JEL: E12 E31 F41 F44
    Date: 2023–10–01
  8. By: Martin Chegere; Paolo Falco; Andreas Menzel
    Abstract: Many firms hire workers via social networks. Whether workers who are socially connected to their employers exert more effort on the job is an unsettled debate. We address this question through a novel experiment with small-business owners in Tanzania. Participants are paired with a worker who conducts a real-effort task, and receive a payoff that depends on the worker’s effort. Some business owners are randomly paired with workers they are socially connected with, while others are paired with strangers. With a design that is sufficiently powered to detect economically meaningful effects, we find that being socially connected to one’s employer does not affect workers’ effort.
    Keywords: firms, hiring, productivity, social ties, kinship networks
    JEL: O17 M51 L2
    Date: 2023–09

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