#### Evaluating structural edge importance in temporal networks

To monitor risk in temporal financial networks, we need to understand how individual behaviours affect the global evolution of networks. Here we define a structural importance metric—which we denote as le—for the edges of a network. The metric is based on perturbing the adjacency matrix and observing the resultant change in its largest eigenvalues. We then propose a model of network evolution where this metric controls the probabilities of subsequent edge changes. We show using synthetic data how the parameters of the model are related to the capability of predicting whether an edge will change from its value of le. We then estimate the model parameters associated with five real financia..

Network Economics#### Avian influenza transmission risk along live poultry trading networks in Bangladesh

Live animal markets are known hotspots of zoonotic disease emergence. To mitigate those risks, we need to understand how networks shaped by trading practices influence disease spread. Yet, those practices are rarely recorded in high-risk settings. Through a large cross-sectional study, we assessed the potential impact of live poultry trading networks’ structures on avian influenza transmission dynamics in Bangladesh. Networks promoted mixing between chickens sourced from different farming systems and geographical locations, fostering co-circulation of viral strains of diverse origins in markets. Viral transmission models suggested that the observed rise in viral prevalence from farms to ma..

Network Economics#### What Makes a Classmate a Peer?Examining Which Peers Matter in NYC Elementary Schools Abstract

We identify and estimate the effects of student-level social spillovers on standardized test performance in New York City (NYC) elementary schools. We leverage student demographic data to construct within classroom social networks based on shared student characteristics, such as a gender or ethnicity. Rather than aggregate shared characteristics into a single network matrix, we specify additively separate network matrices for each shared characteristic and estimate city-wide peer effects for each one. Conditional on sharing a classroom, we find that the most important student peer effects are shared ethnicity, gender, and primary language spoken at home. Identification of the model is discus..

Network Economics#### Can you always reap what you sow? Network and functional data analysis of VC investments in health-tech companies

"Success" of firms in venture capital markets is hard to define, and its determinants are still poorly understood. We build a bipartite network of investors and firms in the healthcare sector, describing its structure and its communities. Then, we characterize "success" introducing progressively more refined definitions, and we find a positive association between such definitions and the centrality of a company. In particular, we are able to cluster funding trajectories of firms into two groups capturing different "success" regimes and to link the probability of belonging to one or the other to their network features (in particular their centrality and the one of their investors). We further..

Network Economics#### Clubs and Networks

A recurring theme in the study of society is the concentration of influence and power that is driven through unequal membership of groups and associations. In some instances these bodies constitute a small world while in others they are fragmented into distinct cliques. This paper presents a new model of clubs and networks to understand the sources of individual marginalization and the origins of different club networks. In our model, individuals seek to become members of clubs while clubs wish to have members. Club value is increasing in its size and in the strength of ties with other clubs. We show that a stable membership profile exhibits marginalization of individuals and that this is ge..

Network Economics#### Cyber contagion: impact of the network structure on the losses of an insurance portfolio

In this paper, we provide a model that aims to describe the impact of a massive cyber attack on an insurance portfolio, taking into account the structure of the network. Due to the contagion, such an event can rapidly generate consequent damages, and mutualization of the losses may not hold anymore. The composition of the portfolio should therefore be diversified enough to prevent or reduce the impact of such events, with the difficulty that the relationships between actor is difficult to assess. Our approach consists in introducing a multi-group epidemiological model which, apart from its ability to describe the intensity of connections between actors, can be calibrated from a relatively sm..

Network Economics#### Crisis Propagation in a Heterogeneous Self-Reflexive DSGE Model

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp crossover between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for ..

Network Economics#### MCMC Conditional Maximum Likelihood for the two-way fixed-effects logit

We propose a Markov chain Monte Carlo Conditional Maximum Likelihood (MCMC-CML) estimator for two-way fixed-effects logit models for dyadic data. The proposed MCMC approach, based on a Metropolis algorithm, allows us to overcome the computational issues of evaluating the probability of the outcome conditional on nodes in and out degrees, which are sufficient statistics for the incidental parameters. Under mild regularity conditions, the MCMC-CML estimator converges to the exact CML one and is asymptotically normal. Moreover, it is more efficient than the existing pairwise CML estimator. We study the finite sample properties of the proposed approach by means of a simulation study and three em..

Network Economics#### The Heterogeneous Impact of Referrals on Labor Market Outcomes

We document a new set of facts regarding the impact of referrals on labor market outcomes. Our results highlight the importance of distinguishing between different types of referrals—those from family and friends and those from business contacts—and different occupations. Then we develop an on-the-job search model that incorporates referrals and calibrate the model to key moments in the data. The calibrated model yields new insights into the roles played by different types of referrals in the match formation process, and provides quantitative estimates of the effects of referrals on employment, earnings, output, and inequality.

Network Economics#### Ethnicity and risk sharing network formation: Evidence from rural Viet Nam

Ethnic inequality remains a persistent challenge for Viet Nam. This paper aims at better understanding this ethnic gap through exploring the formation of risk sharing networks in rural areas. It first investigates the differences in risk sharing networks between the ethnic minorities and the Kinh majority, in terms of size and similarity attributes of the networks. Second, it relies on the concept of ethnic homophily in link formation to explain the mechanisms leading to those differences. In particular, it disentangles the effect of demographic and local distribution of ethnic groups on risk-sharing network formation from cultural and social distance between ethnic groups, while controlling..

Network Economics#### Circles of Trust: Rival Information in Social Networks

We analyze the diffusion of rival information in a social network. In our model, rational agents can share information sequentially, unconstrained by an exogenous protocol or timing. We show how to compute the set of eventually informed agents for any network, and show that it is essentially unique under altruistic preferences. The relationship between network structure and information diffusion is complex because the former shapes both the charity and confidentiality of potential senders and receivers.

Network Economics#### Universal Database for Economic Complexity

We present an integrated database suitable for the investigations of the Economic development of countries by using the Economic Fitness and Complexity framework. Firstly, we implement machine learning techniques to reconstruct the database of Trade of Services and we integrate it with the database of the Trade of the physical Goods, generating a complete view of the International Trade and denoted the Universal database. Using this data, we derive a statistically significant network of interaction of the Economic activities, where preferred paths of development and clusters of High-Tech industries naturally emerge. Finally, we compute the Economic Fitness, an algorithmic assessment of the c..

Network Economics#### Myerson value of directed hypergraphs

In this paper, we consider a directed hypergraph as cooperative network, and define the Myerson value for directed hypergraphs. We prove the axiomatization of the Myerson value, namely strong component efficiency and fairness. Moreover, we modified the concept of safety defined by Li-Shan, and proved the condition about the safety of the hyperedge with respect to the Myerson value for directed hypergraphs.

Network Economics#### Ordinal Synchronization and Typical States in High-Frequency Digital Markets

In this paper we show, through the study of ordinal patterns, information theoretic and network measures and clustering algorithms, the presence of typical states in automated high-frequency records during a one-year period in the US stock market, characterized by their degree of centralized or descentralized synchronicity. We also find two whole coherent seasons of highly centralized and descentralized synchronicity, respectively.

Network Economics#### Group Identity, Social Learning and Opinion Dynamics

In this paper, we study opinion dynamics in a balanced social structure consisting of two groups. Agents learn the true state of the world naively learning from their neighbors and from an unbiased source of information. Agents want to agree with others of the same group -- in-group identity, -- but to disagree with those of the opposite group -- out-group conflict. We characterize steady state opinions, and show that agents' influence depends on their Bonacich centrality in the signed network of opinion exchange. Finally, we study the effect of group size, the weight given to unbiased information and homophily when agents in the same group are homogeneous.

Network Economics#### Inferring supply networks from mobile phone data to estimate the resilience of a national economy

National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to now, systemic risk of individual companies was practically not quantifiable, due to the unavailability of firm-level transaction data. So far, economic shocks are typically studied in the framework of input-output analysis on the industry-level that can't relate risk to individual firms. Exact firm-level supply networks based on tax or payment data exist only for very few countries. Here we explore to what extent telecommunication data can be used as an ine..

Network Economics#### Dyadic Double/Debiased Machine Learning for Analyzing Determinants of Free Trade Agreements

This paper presents novel methods and theories for estimation and inference about parameters in econometric models using machine learning of nuisance parameters when data are dyadic. We propose a dyadic cross fitting method to remove over-fitting biases under arbitrary dyadic dependence. Together with the use of Neyman orthogonal scores, this novel cross fitting method enables root-$n$ consistent estimation and inference robustly against dyadic dependence. We illustrate an application of our general framework to high-dimensional network link formation models. With this method applied to empirical data of international economic networks, we reexamine determinants of free trade agreements (FTA..

Network Economics#### Group network effects in price competition

The partition of society into groups, polarization, and social networks are part of most conversations today. How do they influence price competition? We discuss Bertrand duopoly equilibria with demand subject to network effects. Contrary to models where network effects depend on one aggregate variable (demand for each choice), partitioning the dependence into groups creates a wealth of pure price equilibria with profit for both price setters, even if positive network effects are the dominant element of the game. If there is some asymmetry in how groups interact, two groups are sufficient. If network effects are based on undirected and unweighted graphs, at least five groups are required but..

Network Economics#### Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States

This study develops an economic model for a social planner who prioritizes health over short-term wealth accumulation during a pandemic. Agents are connected through a weighted undirected network of contacts, and the planner's objective is to determine the policy that contains the spread of infection below a tolerable incidence level, and that maximizes the present discounted value of real income, in that order of priority. The optimal unique policy depends both on the configuration of the contact network and the tolerable infection incidence. Comparative statics analyses are conducted: (i) they reveal the tradeoff between the economic cost of the pandemic and the infection incidence allowed..

Network Economics#### The network origins of aggregate fluctuations: a demand-side approach

We construct a model of cyclical growth with agent-based features designed to study the network origins of aggregate fluctuations from a demand-side perspective. In our model, aggregate fluctuations result from variations in investment behavior at firm level motivated by endogenously-generated changes in `animal spirits' or the state of long run expectations (SOLE). In addition to being influenced by their own economic conditions, firms pay attention to the performance of first-degree network neighbours, weighted (to differing degrees) by the centrality of these neighbours in the network, when revising their SOLE. This allows us to analyze the effects of the centrality of linked network neig..

Network Economics#### Dynamic Bipartite Matching Market with Arrivals and Departures

In this paper, we study a matching market model on a bipartite network where agents on each side arrive and depart stochastically by a Poisson process. For such a dynamic model, we design a mechanism that decides not only which agents to match, but also when to match them, to minimize the expected number of unmatched agents. The main contribution of this paper is to achieve theoretical bounds on the performance of local mechanisms with different timing properties. We show that an algorithm that waits to thicken the market, called the $\textit{Patient}$ algorithm, is exponentially better than the $\textit{Greedy}$ algorithm, i.e., an algorithm that matches agents greedily. This means that wai..

Network Economics#### Multiway empirical likelihood

his paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likeli- hood statistic that converges to a chi-square distribution under the non-degenerate case, where corresponding Hoeffding type decomposition is dominated by linear terms. Our methodology is related to the notion of jackknife empirical likelihood but the leave-out pseudo values are constructed by leaving out columns or rows. We further develop a modified version of our multiway empirical likelihood statistic, which converges to a chi-square distribution regardless of the degeneracy, and discover its desirable higher-order ..

Network Economics#### Free Riding in Networks

Players allocate their budget to links, a local public good and a private good. A player links to free ride on others' public good provision. We derive sufficient conditions for the existence of a Nash equilibrium. In equilibrium, large contributors link to each other, while others link to them. Poorer players can be larger contributors if linking costs are sufficiently high. In large societies, free riding reduces inequality only in networks in which it is initially low; otherwise, richer players benefit more, as they can afford more links. Finally, we study the policy implications, deriving income redistribution that increases welfare and personalized prices that implement the efficient so..

Network Economics#### Forecasting Financial Market Structure from Network Features using Machine Learning

We propose a model that forecasts market correlation structure from link- and node-based financial network features using machine learning. For such, market structure is modeled as a dynamic asset network by quantifying time-dependent co-movement of asset price returns across company constituents of major global market indices. We provide empirical evidence using three different network filtering methods to estimate market structure, namely Dynamic Asset Graph (DAG), Dynamic Minimal Spanning Tree (DMST) and Dynamic Threshold Networks (DTN). Experimental results show that the proposed model can forecast market structure with high predictive performance with up to $40\%$ improvement over a tim..

Network Economics#### Does Default Pecking Order Impact Systemic Risk? Evidence from Brazilian data

In network models of systemic risk, the loss distribution of a distressed debtor among its creditors follows a pro-rata fashion. It is proportional to the loan granted to the debtor. Despite its simplicity, this assumption is unrealistic. In this study, we create a framework for the computation of the systemic risk assuming a heterogeneous pattern of loss distribution, the default pecking order. Distressed debtors employ some criterion (equity, out-degree, or loan extended) to rank the creditors they are willing to default on first. Applying this framework to an extensive Brazilian data set, we found out the adoption of the default pecking order increases significantly the systemic risk. The..

Network Economics#### Supply Network Formtion and Fragility

We model the production of complex goods in a large supply network. Each firm sources several essential inputs through relationships with other firms. Individual supply relationships are at risk of idiosyncratic failure, which threatens to disrupt production. To protect against this, firms multisource inputs and strategically invest to make relationships stronger, trading off the cost of investment against the benefits of increased robustness. We find that equilibrium aggregate production is robust to idiosyncratic disruptions. Nevertheless, there is a regime in which arbitrarily small systemic shocks cause arbitrarily steep drops in output, so that the the supply network is fragile. The end..

Network Economics#### Supply Network Formtion and Fragility

We model the production of complex goods in a large supply network. Each firm sources several essential inputs through relationships with other firms. Individual supply relationships are at risk of idiosyncratic failure, which threatens to disrupt production. To protect against this, firms multisource inputs and strategically invest to make relationships stronger, trading off the cost of investment against the benefits of increased robustness. We find that equilibrium aggregate production is robust to idiosyncratic disruptions. Nevertheless, there is a regime in which arbitrarily small systemic shocks cause arbitrarily steep drops in output, so that the the supply network is fragile. The end..

Network Economics#### Liquidity Provision and Co-insurance in Bank Syndicates

We study the capacity of the banking system to provide liquidity to the corporate sector in times of stress and how changes in this capacity affect corporate liquidity management. We show that the contractual arrangements among banks in loan syndicates co-insure liquidity risks of credit line drawdowns and generate a network of interbank exposures. We develop a simple model and simulate the liquidity and insurance capacity of the banking network. We find that the liquidity capacity of large banks has significantly increased following the introduction of liquidity regulation, and that the liquidity co-insurance function in loan syndicates is economically important. We also find that borrowers..

Network Economics#### Uniqueness of Clearing Payment Matrices in Financial Networks

We study bankruptcy problems in financial networks in the presence of general bankruptcy laws. The set of clearing payment matrices is shown to be a lattice, which guarantees the existence of a greatest and a least clearing payment. Multiplicity of clearing payment matrices is both a theoretical and a practical concern. We present a new condition for uniqueness that generalizes all the existing conditions proposed in the literature. Our condition depends on the decomposition of the financial network into strongly connected components. A strongly connected component which contains more than one agent is called a cycle and the involved agents are called cyclical agents. If there is a cycle wit..

Network Economics#### Network structure and governance in sport clusters: a mixed methods analysis

Research question: This study contributes to our understanding of how network structures influence cluster governance and consequently cluster outcomes. We investigate the relational structure of cross-sectoral sport clusters and how these influence network governance. Research methods: We employed a mixed methods approach, combining qualitative research data and social network analysis (SNA). Forty-nine interviews were conducted with employees from the surfing clusters in Aquitaine (France) and Torquay (Australia). The interview transcripts were subjected to two rounds of coding prior to SNA on an aggregated actor level. Results and findings: Findings from both clusters show the core is com..

Network Economics