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on Network Economics |
| By: | Abhijit Banerjee; Emily Breza; Arun G. Chandrasekhar; Esther Duflo; Matthew O. Jackson; Cynthia Kinnan |
| Abstract: | Formal financial institutions can have far-reaching and long-lasting impacts on informal lending and information networks. We first study 75 villages in Karnataka, 43 of which were exposed to microfinance after we first collected detailed network data. Networks shrink more in exposed villages. Links between households that were unlikely to ever borrow from microfinance are at least as likely to disappear as links involving likely borrowers. We replicate these surprising findings in the context of a randomized controlled trial in Hyderabad, where a microfinance institution randomly selected neighborhoods to enter first. Four years after all neighborhoods were treated, households in early-entry neighborhoods had credit access longer and had larger loans. We again find fewer social relationships between households in early-entry neighborhoods, even among those ex-ante unlikely to borrow. Because the results suggest global spillovers, which are inconsistent with standard models of network formation, we develop a new dynamic model of network formation that emphasizes chance meetings, where efforts to socialize generate a global network-level externality. Finally, we analyze informal borrowing and the sensitivity of consumption to income fluctuations. Households unlikely to take up microcredit suffer the greatest loss of informal borrowing and risk sharing, underscoring the global nature of the externality. |
| JEL: | D13 D85 L14 O12 Z13 |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:28365&r=all |
| By: | Adam Altmejd; Andrés Barrios Fernandez; Marin Drlje; Joshua Goodman; Michael Hurwitz; Dejan Kovac; Christine Mulhern; Christopher Neilson; Jonathan Smith |
| Abstract: | Family and social networks are widely believed to influence important life decisions but identifying their causal effects is notoriously difficult. Using admissions thresholds that directly affect older but not younger siblings' college options, we present evidence from the United States, Chile, Sweden and Croatia that older siblings' college and major choices can significantly influence their younger siblings' college and major choices. On the extensive margin, an older sibling's enrollment in a better college increases a younger sibling's probability of enrolling in college at all, especially for families with low predicted probabilities of enrollment. On the intensive margin, an older sibling's choice of college or major increases the probability that a younger sibling applies to and enrolls in that same college or major. Spillovers in major choice are stronger when older siblings enroll and succeed in more selective and higher-earning majors. The observed spillovers are not well-explained by price, income, proximity or legacy effects, but are most consistent with older siblings transmitting otherwise unavailable information about the college experience and its potential returns. The importance of such personally salient information may partly explain persistent differences in college-going rates by geography, income, and other determinants of social networks. |
| Keywords: | sibling effects, college and major choice, peer and social network effects |
| JEL: | I21 I24 |
| Date: | 2020–05 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp1691&r=all |
| By: | Roy Cerqueti (Sapienza University of Rome and London South Bank University); Rocco Ciciretti (CEIS & DEF, University of Rome "Tor Vergata"); Ambrogio Dalò (University of Groningen); Marco Nicolosi (University of Perugia) |
| Abstract: | A network model is introduced and developed to compare portfolios of funds which are high ranked in Environmental Social and Governance (ESG) aspects with those with a poor ESG compliance. The nodes in the network represent funds and the edges are weighted on the basis of the capitalization due to the common components of the connected nodes. We specifically deal with the reactions of the considered financial networks to exogenous shocks of negative financial nature. To this aim, we provide a novel definition of the resilience of a financial network in terms of stability of its community structure. We test the theoretical proposal on different networks characterized by different ESG scores. We find that the high ranked funds networks are more resilient than the corresponding networks of low ranked funds. |
| Keywords: | Socially Responsible Investments, ESG criteria, Investment Funds, Financial networks Resilience. |
| JEL: | G32 C02 |
| Date: | 2020–06–17 |
| URL: | https://d.repec.org/n?u=RePEc:rtv:ceisrp:495&r=all |
| By: | Seung Bin Baik |
| Abstract: | This study more complex digital platforms in early stages in the two-sided market to produce powerful network effects. In this study, I use Transfer Entropy to look for super users who connect hominids in different networks to achieve higher network effects in the digital platform in the two-sided market, which has recently become more complex. And this study also aims to redefine the decision criteria of product managers by helping them define users with stronger network effects. With the development of technology, the structure of the industry is becoming more difficult to interpret and the complexity of business logic is increasing. This phenomenon is the biggest problem that makes it difficult for start-ups to challenge themselves. I hope this study will help product managers create new digital economic networks, enable them to make prioritized, data-driven decisions, and find users who can be the hub of the network even in small products. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.09886&r=all |
| By: | Yang Sun; Wei Zhao; Junjie Zhou |
| Abstract: | Two types of interventions are commonly implemented in networks: characteristic intervention which influences individuals' intrinsic incentives, and structural intervention which targets at the social links among individuals. In this paper we provide a general framework to evaluate the distinct equilibrium effects of both types of interventions. We identify a hidden equivalence between a structural intervention and an endogenously determined characteristic intervention. Compared with existing approaches in the literature, the perspective from such an equivalence provides several advantages in the analysis of interventions targeting on network structure. We present a wide range of applications of our theory, including identifying the most wanted criminal(s) in delinquent networks and targeting the key connector for isolated communities. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.12420&r=all |
| By: | Dimitrios Tsiotas; Vassilis Tselios |
| Abstract: | Using network analysis, this paper develops a multidimensional methodological framework for understanding the uneven (cross-country) spread of COVID-19 in the context of the global interconnected economy. The globally interconnected system of tourism mobility is modeled as a complex network, where two main stages in the temporal spread of COVID-19 are revealed and defined by the cutting-point of the 44th day from Wuhan. The first stage describes the outbreak in Asia and North America, the second one in Europe, South America, and Africa, while the outbreak in Oceania is spread along both stages. The analysis shows that highly connected nodes in the global tourism network (GTN) are infected early by the pandemic, while nodes of lower connectivity are late infected. Moreover, countries with the same network centrality as China were early infected on average by COVID-19. The paper also finds that network interconnectedness, economic openness, and transport integration are key determinants in the early global spread of the pandemic, and it reveals that the spatio-temporal patterns of the worldwide spread of COVID-19 are more a matter of network interconnectivity than of spatial proximity. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.11036&r=all |
| By: | Aref Mahdavi Ardekani (Centre d'Economie de la Sorbonne) |
| Abstract: | By applying the interbank network simulation, this paper examines whether the causal relationship between capital and liquidity is influenced by bank positions in the interbank network. While existing literature highlights the causal relationship that moves from liquidity to capital, the question of how interbank network characteristics affect this relationship remains unclear. Using a sample of commercial banks from 28 European countries, this paper suggests that bank's interconnectedness within interbank loan and deposit networks affects their decisions to set higher or lower regulatory capital ratios when facing higher iliquidity. This study provides support for the need to implement minimum liquidity ratios to complement capital ratios, as stressed by the Basel Committee on Banking Regulation and Supervision. This paper also highlights the need for regulatory authorities to consider the network characteristics of banks |
| Keywords: | Interbank network topology; Bank regulatory capital; Liquidity risk; Basel III |
| JEL: | G21 G28 L14 |
| Date: | 2020–10 |
| URL: | https://d.repec.org/n?u=RePEc:mse:cesdoc:20022r&r=all |
| By: | Ines Wilms; Jacob Bien |
| Abstract: | High-dimensional graphical models are often estimated using regularization that is aimed at reducing the number of edges in a network. In this work, we show how even simpler networks can be produced by aggregating the nodes of the graphical model. We develop a new convex regularized method, called the tree-aggregated graphical lasso or tag-lasso, that estimates graphical models that are both edge-sparse and node-aggregated. The aggregation is performed in a data-driven fashion by leveraging side information in the form of a tree that encodes node similarity and facilitates the interpretation of the resulting aggregated nodes. We provide an efficient implementation of the tag-lasso by using the locally adaptive alternating direction method of multipliers and illustrate our proposal's practical advantages in simulation and in applications in finance and biology. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.12503&r=all |
| By: | Cécile Bothorel (Lab-STICC_IMTA_CID_DECIDE - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire - IMT - Institut Mines-Télécom [Paris], IMT Atlantique - LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information - IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire - IMT - Institut Mines-Télécom [Paris]); Laurent Brisson (Lab-STICC_IMTA_CID_DECIDE - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire - IMT - Institut Mines-Télécom [Paris], IMT Atlantique - LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information - IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire - IMT - Institut Mines-Télécom [Paris]); Inna Lyubareva (IMT Atlantique - LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information - IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire - IMT - Institut Mines-Télécom [Paris]) |
| Abstract: | Discovering community structure in complex networks is a mature field since a tremendous number of community detection methods have been introduced in the literature. Nevertheless, it is still very challenging for practitioners to choose in each particular case the most suitable algorithm which would provide the richest insights into the structure of the social network they study. Through a case study of the French crowdfunding platform, Ulule, this paper demonstrates an original methodology for the selection of a relevant algorithm. For this purpose we, firstly, compare the partitions of 11 well-known algorithms. Then, bivariate map based on hub dominance and transitivity is used to identify the partitions which unveil communities with the most interesting size and internal topologies. These steps result in three community detection methods relevant for our data. Finally, we add the socioeconomic indicators, meaningful in the framework of the crowdfunding platform, in order to select the most significant algorithm of community detection, and to analyze the cooperation patterns among the platform's users and their impact on success of fundraising campaigns. In line with previous socioeconomic studies, we demonstrate that the social concept of homophily in online groups really matters. In addition, our approach puts in light that crowdfunding groups may benefit from diversity. |
| Keywords: | Social Networks Analysis,Community Detection,Choice of method,Complex Networks,Online cooperation,Crowdfunding |
| Date: | 2020 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-03028871&r=all |
| By: | Mehmet Ziya Gorpe; Giovanni Covi; Christoffer Kok |
| Abstract: | This paper presents a novel approach to investigate and model the network of euro area banks’ large exposures within the global banking system. Drawing on a unique dataset, the paper documents the degree of interconnectedness and systemic risk of the euro area banking system based on bilateral linkages. We develop a Contagion Mapping model fully calibrated with bank-level data to study the contagion potential of an exogenous shock via credit and funding risks. We find that tipping points shifting the euro area banking system from a less vulnerable state to a highly vulnerable state are a non-linear function of the combination of network structures and bank-specific characteristics. |
| Keywords: | Banking;Liquidity;Asset liquidity;Systemic risk;Commercial banks;WP,central bank,capital base,banking system,discount rate |
| Date: | 2019–05–10 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2019/102&r=all |
| By: | Dennis Essers; Francesco Grigoli; Evgenia Pugacheva |
| Abstract: | We study the determinants of new and repeated research collaborations, drawing on the co-authorship network of the International Monetary Fund (IMF)’s Working Papers series. Being an outlet where authors express their views on topics of interest, and given that IMF staff is not subject to the “publish-or-perish” conditions of the academia, the IMF Working Papers series constitutes an appropriate testing ground to examine the endogenous nature of co-authorship formation. We show that the co-authorship network is characterized by many authors with few direct co-authors, yet indirectly connected to each other through short co-authorship chains. We find that a shorter distance in the co-authorship network is key for starting research collaborations. Also, higher research productivity, being employed in the same department, and having citizenship of the same region help to start and repeat collaborations. Furthermore, authors with different co-authorship network sizes are more likely to collaborate, possibly reflecting synergies between senior and junior staff members. |
| Keywords: | Labor;International organization;Productivity;Women;Gender;WP,author pair,affiliation category,IMF author,IMF working papers,author characteristic |
| Date: | 2020–07–24 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2020/144&r=all |
| By: | David Baqaee; Emmanuel Farhi |
| Abstract: | The Covid-19 crisis is an unusual and seemingly all-encompassing economic shock. On the one hand, it was unquestionably a negative demand shock that, for fixed prices and incomes, reduced household spending. On the other hand, it was also unquestionably a negative supply shock that reduced firms' ability to maintain production at pre-pandemic prices and quantities. These negative shocks affected different industries differently: whereas some producers easily switched to remote-work and maintained both employment and production, industries that required face-to-face contact were forced to reduce production capacity and employment. We consider a stripped-down version of the model presented in Baqaee and Farhi (2020). Despite its simplicity, the model nevertheless allows for an arbitrary input-output network, complementarities in both consumption and production, incomplete markets, downward nominal wage rigidity, and a zero-lower bound. In this sense, it contains many of the ingredients typically considered to be important for understanding the economic fallout from Covid-19. Nevertheless, despite allowing for these realistic ingredients, this model has a stark property: factor income shares at the initial equilibrium are global sufficient statistics for the input-output network. This article clarifies clarifies what ingredients must be added to a model if the production network is to play an important role in the propagation of shocks. |
| JEL: | E0 E24 E3 E4 E5 |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:28346&r=all |
| By: | Mykola Babiak; Jozef Barunik |
| Abstract: | We examine the pricing of a horizon specific uncertainty network risk, extracted from option implied variances on exchange rates, in the cross-section of currency returns. Buying currencies that are receivers and selling currencies that are transmitters of short-term shocks exhibits a high Sharpe ratio and yields a significant alpha when controlling for standard dollar, carry trade, volatility, variance risk premium and momentum strategies. This profitability stems primarily from the causal nature of shock propagation and not from contemporaneous dynamics. Shock propagation at longer horizons is priced less, indicating a downward-sloping term structure of uncertainty network risk in currency markets. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.09738&r=all |
| By: | Denis Kojevnikov |
| Abstract: | This paper focuses on the bootstrap for network dependent processes under the conditional $\psi$-weak dependence. Such processes are distinct from other forms of random fields studied in the statistics and econometrics literature so that the existing bootstrap methods cannot be applied directly. We propose a block-based approach and a modification of the dependent wild bootstrap for constructing confidence sets for the mean of a network dependent process. In addition, we establish the consistency of these methods for the smooth function model and provide the bootstrap alternatives to the network heteroskedasticity-autocorrelation consistent (HAC) variance estimator. We find that the modified dependent wild bootstrap and the corresponding variance estimator are consistent under weaker conditions relative to the block-based method, which makes the former approach preferable for practical implementation. |
| Date: | 2021–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2101.12312&r=all |
| By: | Semenova, Valentina; Winkler, Julian |
| Abstract: | Tracking endogenous fluctuations in stock prices emerged as a key challenge for empirical work in behavioural and evolutionary finance. This paper uses new data from an online discussion forum, Reddit, to quantify social contagion, or `hype,' in specific stock market movements, using state of the art opinion dynamics modelling and sentiment analysis. The influence between users on the WallStreetBets (WSB) subreddit is measured by tracing the probability of a user starting a fresh discussion on an asset given their previous involvement in a discussion on the same asset, measured by their comment history. This paper finds that users who comment on one discussion involving a particular asset are approximately four times more likely to start a new discussion about this asset in the future, with the probability increasing with each additional discussion the user engages in. This is a strong indication that investment strategies are reproduced through social interaction. This is further validated by findings that sentiments expressed in the linked submissions are strongly correlated in a set of spatial regression models. In particular, bearish sentiments seem to spread more than their bullish counterparts. |
| Keywords: | Network Economics, Opinion Dynamics, Natural Language Processing, Behavioral Finance |
| JEL: | D85 G14 |
| Date: | 2020–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:105443&r=all |