nep-net New Economics Papers
on Network Economics
Issue of 2020‒05‒18
thirteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Social Interactions in Pandemics: Fear, Altruism, and Reciprocity By Laura Alfaro; Ester Faia; Nora Lamersdorf; Farzad Saidi
  2. Identification and Inference of Network Formation Games with Misclassified Links By Candelaria, Luis E.; Ura, Takuya
  3. Causal Inference on Networks under Continuous Treatment Interference By Davide Del Prete; Laura Forastiere; Valerio Leone Sciabolazza
  4. Sectoral Impact of COVID-19: Cascading Risks By Sophie Osotimehin; Latchezar Popov
  5. The Determinants of Trust: Evidence from Rural South India By Hilger, Anne; Nordman, Christophe Jalil
  6. Affirmative action programs and network benefits in the number of board positions By Burzynska, Katarzyna; Contreras, Gabriela
  7. Network Configuration as a Measure of Power in Global Production Networks By Panagiotis Iliopoulos; Giorgos Galanis; Ashok Kumar; Lilit Popoyan
  8. Peers, Gender, and Long-Term Depression By Giulietti, Corrado; Vlassopoulos, Michael; Zenou, Yves
  9. Mapping Coupled Time-series Onto Complex Network By Jamshid Ardalankia; Jafar Askari; Somaye Sheykhali; Emmanuel Haven; G. Reza Jafari
  10. Leaders among the leaders in Economics: A network analysis of the Nobel Prize laureates By Molina, José Alberto; Iñiguez, David; Ruiz, Gonzalo; Tarancón, Alfonso
  11. Engineering Economics in the Conflux Network By Yuxi Cai; Fan Long; Andreas Park; Andreas Veneris
  12. Social Connectedness in Europe By Bailey, Michael; Kuchler, Theresa; Russel, Dominic; State, Bogdan; Stroebel, Johannes
  13. Route choice, travel time variability, and rational inattention By Jiang, Gege; Fosgerau, Mogens; Lo, Hong

  1. By: Laura Alfaro; Ester Faia; Nora Lamersdorf; Farzad Saidi
    Abstract: In SIR models, homogeneous or with a network structure, infection rates are assumed to be exogenous. However, individuals adjust their behavior. Using daily data for 89 cities worldwide, we document that mobility falls in response to fear, as approximated by Google search terms. Combining these data with experimentally validated measures of social preferences at the regional level, we find that stringency measures matter less if individuals are more patient and altruistic preference traits, and exhibit less negative reciprocity community traits. We modify the homogeneous SIR and the SIR-network model to include agents' optimizing decisions on social interactions. Susceptible individuals internalize infection risk based on their patience, infected ones do so based on their altruism, and reciprocity matters for internalizing risk in SIR networks. A planner further restricts interactions due to a static and a dynamic inefficiency in the homogeneous SIR model, and due to an additional reciprocity inefficiency in the SIR-network model. We show that partial or targeted lockdown policies are efficient only when it is possible to identify infected individuals.
    JEL: D62 D64 D85 D91 I10
    Date: 2020–05
  2. By: Candelaria, Luis E. (University of Warwick); Ura, Takuya (University of California, Davis)
    Abstract: This paper considers a network formation model when links are potentially measured with error. We focus on a game-theoretical model of strategic network formation with incomplete information, in which the linking decisions depend on agents’ exogenous attributes and endogenous network characteristics. In the presence of link misclassification, we derive moment conditions that characterize the identified set for the preference parameters associated with homophily and network externalities. Based on the moment equality conditions, we provide an inference method that is asymptotically valid when a single network of many agents is observed. Finally, we apply our proposed method to study trust networks in rural villages in southern India.
    Keywords: Misclassification ; Network formation models ; Strategic interactions ; Incomplete information JEL codes: C13 ; C31
    Date: 2020
  3. By: Davide Del Prete; Laura Forastiere; Valerio Leone Sciabolazza
    Abstract: This paper presents a methodology to draw causal inference in a non-experimental setting subject to network interference. Specifically, we develop a generalized propensity score-based estimator that allows us to estimate both direct and spillover effects of a continuous treatment, which spreads through weighted and directed edges of a network. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of policy interventions in agricultural markets. Our results show that, in this context, neglecting interference may lead to a downward bias when assessing policy effectiveness.
    Date: 2020–04
  4. By: Sophie Osotimehin; Latchezar Popov
    Abstract: Workers are unequal in the face of the COVID-19 pandemic: Those who work in essential sectors face higher health risk whereas those in non-essential social-consumption sectors face greater economic risk. We study how these health and economic risks cascade into other sectors through supply chains and demand linkages. In the U.S., we find the cascading effects account for about 25-30% of the exposure to both risks. The cascading effect increases the health risk faced by workers in the transportation and retail sectors, and it increases the economic risk faced by workers in the textile and petroleum sectors. We provide sectoral estimates of the health and economic risk for 42 other countries in an online interactive document.
    Keywords: COVID-19; Input-output; Production network; Demand complementarity; Demand shocks
    JEL: E24 E23 D57
    Date: 2020–05–07
  5. By: Hilger, Anne (Paris School of Economics); Nordman, Christophe Jalil (IRD, DIAL, Paris-Dauphine)
    Abstract: Trust and participation in social networks are inherently interrelated. We make use of India's demonetization policy, an unexpected and unforeseeable exogenous variation, to causally identify the effect of social networks in determining trust. We use first-hand quantitative and qualitative data from rural South India and control for individual characteristics (personality traits, cognitive ability) that could influence network formation and trust, finding that social interactions have a significant effect on trust among men, as well as across castes. Among lower castes, who live in homogeneous neighborhoods and relied on neighbors and employers to cope, extending one's network lowers trust in neighbors. Among middle castes, who live in more heterogeneous neighborhoods and relied predominantly on other caste members, a larger network size leads to greater trust placed in kin among employees but lesser in neighbors. This paper thus shows that social interactions can foster trust and highlights the importance of clearly defining in- and out-groups in trust measures within highly segregated societies.
    Keywords: India, trust, social networks
    JEL: O12 D85 D91
    Date: 2020–04
  6. By: Burzynska, Katarzyna; Contreras, Gabriela (Radboud University)
    Abstract: Whereas governments are increasingly considering affirmative action programs to increase corporate board diversity, the effect of such programs can be superficial as they do not address the underlying problem, which is women's access to and inclusion in relevant corporate networks. To address this issue, we study the relationship among affirmative action programs (binding gender quotas and non-binding gender targets), director networks, and the number of board positions individual directors hold given their gender. We use personal, professional, and network characteristics of 25,127 unique directors from 2,435 public firms in 32 European countries over the period of 2000 through 2017. We find that in the absence of affirmative action programs, women directors benefit less from their networks than men directors suggesting the existence of a gender gap in network benefits. After the passage of binding gender quotas, this gender gap in network benefits narrows between women and men directors. Overall, this research suggests that binding gender quotas enhance the inclusion of women in corporate director networks and may help in leveling the playing field in the way these networks are used for achieving top management positions.
    Date: 2020–04–21
  7. By: Panagiotis Iliopoulos; Giorgos Galanis; Ashok Kumar; Lilit Popoyan
    Abstract: Power is one of the key components in understanding and analyzing global production and is central to the analytical frameworks of both GVCs and GPNs. By focusing on firms' power within GPNs, we are able to draw a novel analytical link between the governance structures of GVCs and network configuration presented in recent versions of GPNs. Using global input-output data, we show that the network structure of global production helps determine the distribution of power among firms in different economic sectors and, consequently, it influences the governance structures of supply networks. More specifically, we find a very high correlation between the distribution of profits and a sector's position in global production, captured by its (total strength) centrality. Based on this, we are able to provide a quantitative measure of power within global production and its governance structures.
    Keywords: Global production networks; global value chains; power relations; network theory.
    Date: 2020–05–16
  8. By: Giulietti, Corrado; Vlassopoulos, Michael; Zenou, Yves
    Abstract: We provide first evidence that peer depression in adolescence affects own depression in adulthood. We use data from Add Health and an identification strategy that relies on within-school and across-cohort idiosyncratic variation in the share of own-gender peers who are depressed. We find a significant peer effect for females but not for males. An increase of one standard deviation of the share of own-gender peers (schoolmates) who are depressed increases the probability of depression in adulthood by 2.6 percentage points for females (or 11.5% of mean depression). We also find that the peer effect is already present in the short term when girls are still in school and provide evidence for why it persists over time. Further analysis reveals that individuals from families with a lower socioeconomic background are more susceptible to peer influence, thereby suggesting that family can function as a buffer. Our findings underscore the importance of peer relationships in adolescence with regard to the development of long-lasting depression in women.
    Keywords: Peer effects,depression,contagion,gender,family background,adolescence,policy
    JEL: I12 Z13
    Date: 2020
  9. By: Jamshid Ardalankia; Jafar Askari; Somaye Sheykhali; Emmanuel Haven; G. Reza Jafari
    Abstract: For the sake of extracting hidden mutual and coupled information from possibly uncoupled time-series, we explored the profound measures of network science on time-series. Alongside common methods in time-series analysis of coupling between financial and economic markets, mapping coupled time-series onto networks is an outstanding measure to provide insight into hidden aspects embedded in couplings intrinsically. In this manner, we discretize the amplitude of coupled time-series and investigate relative simultaneous locations of the corresponding amplitudes (nodes). The transmissions between simultaneous amplitudes are clarified by edges in the network. In this sense, by segmenting magnitudes, the scaling features, volatilities' size and also the direction of the coupled amplitudes can be described. The frequency of occurrences of the coupled amplitudes is illustrated by the weighted edges, that is to say, some coupled amplitudes in the time-series can be identified as communities in the network. The results show that despite apparently uncoupled joint probabilities, the couplings possess some aspects which diverge from random Gaussian noise. Thereby, with the aid of the network's topological and statistical measurements, we distinguished basic structures of coupling of cross-market networks. Meanwhile, it was discovered that even two possibly known uncoupled markets may possess coupled patterns with each other. Thereby, those markets should be examined as coupled and weakly coupled markets!
    Date: 2020–04
  10. By: Molina, José Alberto; Iñiguez, David; Ruiz, Gonzalo; Tarancón, Alfonso
    Abstract: We analyse the production and networks of Nobel laureates in Economics, employing the Normalized Impact Factor (NIF) of their publications in the Journal of Citation Report (Economics), to identify the academic leaders among those laureates awarded between 1969 and 2016. Our results indicate that direct collaborations among laureates are, in general, rare, but when we add all the co-authors of the laureates, there appears a very large component containing 70% of the nodes, so that more than two thirds of the laureates can be connected through only two steps. Deaton, Tirole, Arrow, and Stiglitz are identified as leaders according to the total production of their respective networks.
    Keywords: Nobel prize,Economics,Impact factor,Research production,Complex networks
    Date: 2020
  11. By: Yuxi Cai; Fan Long; Andreas Park; Andreas Veneris
    Abstract: Proof-of-work blockchains need to be carefully designed so as to create the proper incentives for miners to faithfully maintain the network in a sustainable way. This paper describes how the economic engineering of the Conflux Network, a high throughput proof-of-work blockchain, leads to sound economic incentives that support desirable and sustainable mining behavior. In detail, this paper parameterizes the level of income, and thus network security, that Conflux can generate, and it describes how this depends on user behavior and "policy variables'' such as block and interest inflation. It also discusses how the underlying economic engineering design makes the Conflux Network resilient against double spending and selfish mining attacks.
    Date: 2020–04
  12. By: Bailey, Michael; Kuchler, Theresa; Russel, Dominic; State, Bogdan; Stroebel, Johannes
    Abstract: We use aggregated data from Facebook to study the structure of social networks across European regions. Social connectedness declines strongly in geographic distance and at country borders. Historical borders and unions — such as the Austro-Hungarian Empire, Czechoslovakia, and East/West Germany — shape present-day social connectedness over and above today’s political boundaries. All else equal, social connectedness is stronger between regions with residents of similar ages and education levels, as well as between those that share a language and religion. In contrast, region-pairs with dissimilar incomes tend to be more connected, likely due to increased migration from poorer to richer regions. We find more socially connected region-pairs to have more passenger train trips between them, even after controlling for distance and travel time. We also find that regions with a higher share of connections to other countries have higher rates of trust in the E.U. and lower rates of voting for anti-E.U. political parties.
    Date: 2020–04–28
  13. By: Jiang, Gege; Fosgerau, Mogens; Lo, Hong
    Abstract: This paper sets up a rational inattention model for the route choice problem in a stochastic network where travelers face random travel time. Previous research has assumed that travelers incorporate all provided information without effort. This study assumes that information is costly and that travelers rationally choose how much information to acquire prior to choosing route. We begin with a single traveler and then extend the model to heterogeneous travelers where rationally inattentive user equilibrium (RIUE) is achieved. From the perspective of a single traveler, more information always reduces the impact of travel time variability and increases the probability of choosing a less costly route. However, in RIUE, more information may reduce the social welfare in some scenarios.
    Keywords: Rational inattention; Travel time variability; Imperfect information; Information strategy; Discrete choice
    JEL: D8 R4
    Date: 2020

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