nep-net New Economics Papers
on Network Economics
Issue of 2020‒07‒20
ten papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Conflicts in Spatial Networks By Amarasinghe, Ashani; Raschky, Paul A.; Zenou, Yves; Zhou, Junjie
  2. Exclusion bias and the estimation of peer effects By Caeyers, Bet; Fafchamps, Marcel
  3. Social Groups and the Effectiveness of Protests By Battaglini, Marco; Morton, Rebecca; Patacchini, Eleonora
  4. An egalitarian approach for sharing the cost of a spanning tree By Giménez Gómez, José M. (José Manuel); Peris, Josep E.; Subiza, Begoña
  5. All Things Equal? Social Networks as a Mechanism for Discrimination By Chika O. Okafor
  6. Prophylaxis of Epidemic Spreading with Transient Dynamics By Geraldine Bouveret; Antoine Mandel
  7. A Semiparametric Network Formation Model with Unobserved Linear Heterogeneity By Candelaria, Luis E.
  8. Peer Effects in Academic Research: Senders and Receivers By Bosquet, Clément; Combes, Pierre-Philippe; Henry, Emeric; Mayer, Thierry
  9. Using Social Connections and Financial Incentives to Solve Coordination Failure: A Quasi-Field Experiment in India's Manufacturing Sector By Afridi, Farzana; Dhillon, Amrita; Li, Sherry Xin; Sharma, Swati
  10. Fractional Differencing: (In)stability of Spectral Structure and Risk Measures of Financial Networks By Chakrabarti, Arnab; Chakrabarti, Anindya S.

  1. By: Amarasinghe, Ashani; Raschky, Paul A.; Zenou, Yves; Zhou, Junjie
    Abstract: We develop a network model of conflict in which players are involved in different battles. A negative shock in one locality affects the conflict in this locality but may also increase battles in path-connected localities depending on the location of the battle in the network and the strength of each locality involved in each battle. We then empirically test this model by analyzing the effect of local natural disasters on battles in Africa. We construct a novel panel-dataset that combines geo-referenced information about battle events and natural disasters at the monthly level for 5,944 districts in 53 African countries over the period from 1989 to 2015. At this fine temporal and spatial resolution, natural disasters are formidable exogenous shocks that affect the costs and benefits of fighting in a locality. We find that natural disasters decrease battle incidence in the affected locality and that this effect persists over time and space. This mitigating effect appears to be more pronounced in more developed localities. As highlighted by the model, these results can be explained by the fact that natural disasters divert fighting activity to surrounding localities, particularly those that are connected via geographic and road networks.
    Keywords: Africa; battle; Natural Disasters; Spillovers
    JEL: D85 O55
    Date: 2020–01
  2. By: Caeyers, Bet; Fafchamps, Marcel
    Abstract: We examine a largely unexplored source of downward bias in peer effect estimation, namely, exclusion bias. We derive formulas for the magnitude of the bias in tests of random peer assignment, and for the combined reflection and exclusion bias in peer effect estimation. We show how to consistently test random peer assignment and how to estimate and conduct consistent inference on peer effects without instruments. The method corrects for the presence of reflection and exclusion bias but imposes restrictions on correlated effects. It allows the joint estimation of endogenous and exogenous peer effects in situations where instruments are not available and cannot be constructed from the network matrix. We estimate endogenous and exogenous peer effects in two datasets where instrumental approaches fail because peer assignment is to mutually exclusive groups of identical size. We find significant evidence of positive peer effects in one, negative peer effects in the other. In both cases, ignoring exclusion bias would have led to incorrect inference. We also demonstrate how the same approach applies to autoregressive models.
    Keywords: Autoregressive Models; Exclusion bias; Linear-in-means; peer effects; Random peer assignment; Reflection bias; Social interactions
    JEL: C32
    Date: 2020–02
  3. By: Battaglini, Marco; Morton, Rebecca; Patacchini, Eleonora
    Abstract: We present an informational theory of public protests, according to which public protests allow citizens to aggregate privately dispersed information and signal it to the policy maker. The model predicts that information sharing of signals within social groups can facilitate information aggregation when the social groups are sufficiently large even when it is not predicted with individual signals. We use experiments in the laboratory and on Amazon Mechanical Turk to test these predictions. We find that information sharing in social groups significantly affects citizens' protest decisions and as a consequence mitigates the effects of high conflict, leading to greater efficiency in policy makers' choices. Our experiments highlight that social media can play an important role in protests beyond simply a way in which citizens can coordinate their actions; and indeed that the information aggregation and the coordination motives behind public protests are intimately connected and cannot be conceptually separated.
    Keywords: Petitions; Public Protests; Social groups
    JEL: D72 D78
    Date: 2020–02
  4. By: Giménez Gómez, José M. (José Manuel); Peris, Josep E.; Subiza, Begoña
    Abstract: A minimum cost spanning tree problem analyzes the way to efficiently connect individuals to a source when they are located at different places; that is, to connect them with the minimum possible cost. This objective requires the cooperation of the involved individuals and, once an efficient network is selected, the question is how to fairly allocate the total cost among these agents. To answer this question the literature proposes several rules providing allocations that, generally, depend on all the possible connection costs, regardless of whether these connections have been used or not in order to build the efficient network. To this regard, our approach defines a simple way to allocate the optimal cost with two main criteria: (1) each individual only pays attention to a few connection costs (the total cost of the optimal network and the cost of connecting by himself to the source); and (2) an egalitarian criteria is used to share costs or benefits. Then, we observe that the spanning tree cost allocation can be turned into a claims problem and, by using claims rules, we define two egalitarian solutions so that the total cost is allocated trying to equalize either the payments in which agents incur, or the benefit that agents obtain throughout cooperation. Finally, by comparing both proposals with other solution concepts proposed in the literature, we select equalizing payments as much as possible and axiomatically analyze it, paying special attention to coalitional stability (core selection), a central property whenever cooperation is needed to carry out the project. As our initial proposal might propose allocations outside the core, we modify it to obtain a core selection and we obtain an alternative interpretation of the Folk solution. Keywords: Minimum cost spanning tree, Egalitarian, Cost sharing, Core. JEL classification: C71, D63, D71.
    Keywords: Jocs cooperatius, Economia del benestar, 33 - Economia,
    Date: 2019
  5. By: Chika O. Okafor
    Abstract: I study labor markets in which firms can hire via job referrals. Despite full equality in the initial time period (e.g., equal ability, employment, wages, and network structure), unequal wages and employment still emerge over time between majority and minority workers, due to homophily---the well-documented tendency for people to associate more with others similar to themselves. This inequality can be mitigated by minority workers having more social ties or a "stronger-knit" network. Hence, this paper uncovers a direct mechanism for discriminatory outcomes that neither relies on past inequality nor on discriminatory motives (i.e., neither of the prevailing economic models of taste-based and statistical discrimination). These findings introduce multiple policy implications, including disproving a primary justification for "colorblind" policies---namely disproving the position that such policies are inherently merit-enhancing.
    Date: 2020–06
  6. By: Geraldine Bouveret; Antoine Mandel
    Abstract: We investigate the containment of epidemic spreading in networks from a normative point of view. We consider a susceptible/infected model in which agents can invest in order to reduce the contagiousness of network links. In this setting, we study the relationships between social efficiency, individual behaviours and network structure. First, we exhibit an upper bound on the Price of Anarchy and prove that the level of inefficiency can scale up to linearly with the number of agents. Second, we prove that policies of uniform reduction of interactions satisfy some optimality conditions in a vast range of networks. In setting where no central authority can enforce such stringent policies, we consider as a type of second-best policy the shift from a local to a global game by allowing agents to subsidise investments in contagiousness reduction in the global rather than in the local network. We then characterise the scope for Pareto improvement opened by such policies through a notion of Price of Autarky, measuring the ratio between social welfare at a global and a local equilibrium. Overall, our results show that individual behaviours can be extremely inefficient in the face of epidemic propagation but that policy can take advantage of the network structure to design efficient containment policies.
    Date: 2020–07
  7. By: Candelaria, Luis E. (University of Warwick)
    Abstract: This paper analyzes a semiparametric model of network formation in the presence of unobserved agent-specific heterogeneity. The objective is to identify and estimate the preference parameters associated with homophily on observed attributes when the distributions of the unobserved factors are not parametrically specified. This paper offers two main contributions to the literature on network formation. First, it establishes a new point identification result for the vector of parameters that relies on the existence of a special regressor. The identification proof is constructive and characterizes a closed-form for the parameter of interest. Second, it introduces a simple two-step semiparametric estimator for the vector of parameters with a first-step kernel estimator. The estimator is computationally tractable and can be applied to both dense and sparse networks. Moreover, I show that the estimator is consistent and has a limiting normal distribution as the number of individuals in the network increases. Monte Carlo experiments demonstrate that the estimator performs well in finite samples and in networks with different levels of sparsity.
    Keywords: Network formation ; Unobserved heterogeneity ; Semiparametrics ; Special regressor ; Inverse weighting
    Date: 2020
  8. By: Bosquet, Clément; Combes, Pierre-Philippe; Henry, Emeric; Mayer, Thierry
    Abstract: Using an instrument based on a national contest in France determining researchers' location, we fi nd evidence of peereffects in academia, when focusing on precise groups of senders (producing the spillovers) and receivers (benefi ting from the spillovers),defi ned based on fi eld of specialisation, gender and age. These peereffects are shown to exist even outside formal co-authorship relationships. Furthermore, the match between the characteristics of senders and receivers plays a critical role. In particular, men benefi t a lot from peer effects provided by men, while all other types of gender combinations produce spillovers twice as small.
    Keywords: economics of science; gender publication gap; peer e�ects; Research productivity
    JEL: I23 J16 J24
    Date: 2020–02
  9. By: Afridi, Farzana; Dhillon, Amrita; Li, Sherry Xin; Sharma, Swati
    Abstract: Production processes are often organized in teams, yet there is limited evidence on whether and how social connections and financial incentives affect productivity in tasks that require coordination among workers. We simulate assembly line production in a lab-in-the-field experiment in which workers exert real effort in a minimum-effort game in teams whose members are either socially connected or unconnected and are paid according to the group output. We find that group output increases by 18%, and coordination improves by 30-39% when workers are socially connected with their co-workers. These findings can plausibly be explained by the higher levels of pro-social motivation between co-workers in socially connected teams.
    Keywords: caste-based networks; coordination; Financial incentives; minimum effort game; output; social incentives
    JEL: C93 D20 D22 D24 J33
    Date: 2020–01
  10. By: Chakrabarti, Arnab; Chakrabarti, Anindya S.
    Abstract: Computation of spectral structure and risk measures from networks of multivariate financial time series data has been at the forefront of the statistical finance literature for a long time. A standard mode of analysis is to consider log returns from the equity price data, which is akin to taking first difference ($d = 1$) of the log of the price data. Sometimes authors have considered simple growth rates as well. Either way, the idea is to get rid of the nonstationarity induced by the {\it unit root} of the data generating process. However, it has also been noted in the literature that often the individual time series might have a root which is more or less than unity in magnitude. Thus first differencing leads to under-differencing in many cases and over differencing in others. In this paper, we study how correcting for the order of differencing leads to altered filtering and risk computation on inferred networks. In summary, our results are: (a) the filtering method with extreme information loss like minimum spanning tree as well as filtering with moderate information loss like triangulated maximally filtered graph are very susceptible to such d-corrections, (b) the spectral structure of the correlation matrix is quite stable although the d-corrected market mode almost always dominates the uncorrected (d = 1) market mode indicating under-estimation in the standard analysis, and (c) the PageRank-based risk measure constructed from Granger-causal networks shows an inverted U-shape evolution in the relationship between d-corrected and uncorrected return data over the period of analysis 1972-2018 for historical data of NASDAQ.
    Date: 2020–07–08

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