|
on Network Economics |
| By: | Fan-chin Kung; Ping Wang |
| Abstract: | Observing the increasingly important roles played by the creation and transmission of information and tacit knowledge, we construct an information-network model incorporating both information transmitters and information aggregators. Given information-processing roles in aggregation or transmission, we establish various general properties concerning the existence of a network equilibrium, its optimality and the patterns of equilibrium and optimal configuration. We then allow for endogenous choice of the information-processing roles. We prove the existence and show that, with sufficiently small link maintenance costs, the monocentric network with one aggregator connecting to all other agents as transmitters on a tree graph is the unique configuration. In general, a rich array of equilibrium configurations may emerge, including core-star, star-with-satellites and cycles. We further characterize an information-processing chain network with all information aggregators and transmitters linked along a chain and compute numerically the ranges of transmission decays and link costs within which a network equilibrium arises. |
| JEL: | C7 D20 D83 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30585&r=net |
| By: | Dacic, Nikola; Melolinna, Marko (Bank of England) |
| Abstract: | We study two key characteristics of producers in a production network – size and centrality – and their relationship, which are intimately related to the extent of shock transmission in production networks, both at a macro and micro level. Our contributions are fourfold. First, we show empirically that the UK’s production network has significant asymmetries in producer centrality, varies over time, and yields an empirical size-centrality relationship that tends to be positive in and outside of steady state. Second, we set up a static multisector model with a production network which allows us to link producer size and centrality to underlying shocks in the economy. We show that as long as input substitutability is less than unitary, technology shocks tend to induce negative (positive) co-movement between real output (Domar weights) and outdegrees, unlike preference shocks which tend to induce a positive size-centrality relationship. Third, we calibrate a dynamic model featuring a production network to UK data and use it to filter out technology and demand shocks. The implied size-centrality relationship from the filtered shocks confirms the intuition from the static model. Finally, we use this model to analyse the UK’s post-2010 productivity growth slowdown from a production network perspective, distinguishing industries’ accounting contributions from the contributions of industry-specific and common shocks. We find that idiosyncratic shocks to the manufacturing sector have played a key role in driving the aggregate productivity slowdown. |
| Keywords: | Business cycle; aggregate productivity; productivity puzzle; input-output linkages; production network |
| JEL: | E23 E24 E32 |
| Date: | 2022–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0994&r=net |
| By: | Joshua Schwartzstein; Adi Sunderam |
| Abstract: | To understand new information, we exchange models or interpretations with others. This paper provides a framework for thinking about such social exchanges of models. The key assumption is that people adopt the interpretation in their network that best explains the data, given their prior beliefs. An implication is that interpretations evolve within a network. For many network structures, social learning mutes reactions to data: the exchange of models leaves beliefs closer to priors than they were before. Our results shed light on why disagreements persist as new information arrives, as well as the goal and structure of meetings in organizations. |
| JEL: | D83 D85 D9 G40 |
| Date: | 2022–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30642&r=net |
| By: | Melguizo, Isabel |
| Abstract: | This paper studies processes of integration and segregation using a connections model in which individuals form valuable links that also entail a cost. Individuals belong to two different groups and care about whether their own group represents a sufficient fraction in their neighborhood. Concerns for representation promote the segregation of societies as even for small linking costs individuals do not link to different others because of the threat that their group become under-represented. For certain cost ranges, concerns for representation also determine efficient networks because forming links with members of the opposite group entails a utility loss due to under-representation. |
| Keywords: | integration, segregation, representation concerns, homophily, welfare, pairwise stability |
| JEL: | D6 D85 Z13 |
| Date: | 2022–02–08 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:115172&r=net |
| By: | Liwen Chen (East China Normal University); Bobby Chung (St Bonaventure University); Guanghua Wang (Nanjing Audit University) |
| Abstract: | Increased exposure to gender-role information affects a girl's educational performance. Utilizing the classroom randomization in Chinese middle schools, we find that the increased presence of stay-at-home peer mothers significantly reduces a girl's performance in mathematics. This exposure also cultivates gendered attitudes towards mathematics and STEM professions. The influence of peer mothers increases with network density and when the girl has a distant relationship with her parents. As falsification tests against unobserved confounding factors, we find that the exposure to stay-at-home peer mothers does not affect boys' performance, nor do we find that stay-at-home peer fathers affect girls' outcomes. |
| Keywords: | cultural transmission, gender identity, gender norms, role models |
| JEL: | I24 J16 Z13 |
| URL: | http://d.repec.org/n?u=RePEc:hka:wpaper:2022-039&r=net |
| By: | Anish Agarwal; Sarah Cen; Devavrat Shah; Christina Lee Yu |
| Abstract: | We propose a generalization of the synthetic controls and synthetic interventions methodology to incorporate network interference. We consider the estimation of unit-specific treatment effects from panel data where there are spillover effects across units and in the presence of unobserved confounding. Key to our approach is a novel latent factor model that takes into account network interference and generalizes the factor models typically used in panel data settings. We propose an estimator, "network synthetic interventions", and show that it consistently estimates the mean outcomes for a unit under an arbitrary sequence of treatments for itself and its neighborhood, given certain observation patterns hold in the data. We corroborate our theoretical findings with simulations. |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2210.11355&r=net |
| By: | Kurt Maxwell Kusterer (LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Université Gustave Eiffel); Sylvain Mignot (UCL - Université catholique de Lille); Annick Vignes (CAMS - Centre d'Analyse et de Mathématique sociales - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | YouTube is the largest video hosting platform. The site has emerged in 2005 and has achieved a continuous pattern of growth since its conception (Burgess & Green 2018). A high number of creators, viewers, subscribers and commentators act in this specific ecosystem which generates a huge amount of money. In this article, YouTube is considered as a bilateral network between the videos and the commentators. Analyzing a detailed data set focused on French YouTubers, we consider each comment as a link between a commentator and a video. The main objective of this paper is to understand the determinants of the creation of these links. This is to say, what can explain the choice of an agent to comment a specific video instead of another one, taking into account characteristics of commentators, videos, topics, channels as well as recommendations. This work is different from the classic NLP studies, using text mining techniques to analyze the contents of the comments and the kind of information they diffuse. |
| Keywords: | Youtube ecosystem,Behavioral analysis,Network analysis of Web links |
| Date: | 2022–11–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03799185&r=net |
| By: | Qing Yao; Shaodong Ma; Jing Liang; Kim Christensen; Wanru Jing; Ruiqi Li |
| Abstract: | The Chinese venture capital (VC) market is a young and rapidly expanding financial subsector. Gaining a deeper understanding of the investment behaviours of VC firms is crucial for the development of a more sustainable and healthier market and economy. Contrasting evidence supports that either specialisation or diversification helps to achieve a better investment performance. However, the impact of the syndication network is overlooked. Syndication network has a great influence on the propagation of information and trust. By exploiting an authoritative VC dataset of thirty-five-year investment information in China, we construct a joint-investment network of VC firms and analyse the effects of syndication and diversification on specialisation and investment performance. There is a clear correlation between the syndication network degree and specialisation level of VC firms, which implies that the well-connected VC firms are diversified. More connections generally bring about more information or other resources, and VC firms are more likely to enter a new stage or industry with some new co-investing VC firms when compared to a randomised null model. Moreover, autocorrelation analysis of both specialisation and success rate on the syndication network indicates that clustering of similar VC firms is roughly limited to the secondary neighbourhood. When analysing local clustering patterns, we discover that, contrary to popular beliefs, there is no apparent successful club of investors. In contrast, investors with low success rates are more likely to cluster. Our discoveries enrich the understanding of VC investment behaviours and can assist policymakers in designing better strategies to promote the development of the VC industry. |
| Date: | 2022–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2211.00873&r=net |
| By: | Jimenez Martínez, Antonio; Melguizo Lopez, Isabel |
| Abstract: | We study friendship networks under the assumption that people are constrained to build the qualities of their relations. We investigate the connection between (exogenous) assor- tative interests and (endogenous) homophilic patterns, and its welfare implications. Un- der a simple link formation technology, capacity constraints bolster an interesting mech- anism that leads to asymmetric investments in the formation of links and, furthermore, makes relatively good-quality heterophilic relations necessary for extreme forms of ho- mophilic patterns to be stable. For intermediate assortative interests, extreme forms of either homophilic (or heterophilic) patterns may coexist with more moderate forms. We present empirical evidence on the identified features of stable patterns. Efficiency requires common aggregate qualities of relations across all agents within each different popula- tion group. Although efficiency of stable patterns needs not follow in general, we identify particular forms of extreme stable homophilic and heterophilic patterns that are efficient. Additionally, we identify a class of patterns that feature intermediate levels of homophily, and for which stability and efficiency are compatible. Such particular constructions provide insightful guidance on the role of population sizes to facilitate efficiency of stable patterns. |
| Keywords: | Friendship networks Assortative interests Homophily Heterophily Diversity Integration |
| JEL: | A14 D01 D71 D85 J15 Z13 |
| Date: | 2022–02–21 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:115174&r=net |
| By: | Geon Lee; Tae-Kyoung Kim; Hyun-Gyoon Kim; Jeonggyu Huh |
| Abstract: | In finance, implied volatility is an important indicator that reflects the market situation immediately. Many practitioners estimate volatility using iteration methods, such as the Newton--Raphson (NR) method. However, if numerous implied volatilities must be computed frequently, the iteration methods easily reach the processing speed limit. Therefore, we emulate the NR method as a network using PyTorch, a well-known deep learning package, and optimize the network further using TensorRT, a package for optimizing deep learning models. Comparing the optimized emulation method with the NR function in SciPy, a popular implementation of the NR method, we demonstrate that the emulation network is up to 1,000 times faster than the benchmark function. |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2210.15969&r=net |
| By: | Di Gangi, Domenico (Institute of Information Science and Technologies, National Research Council of Italy); Lazarov, Vladimir (Bank of England); Mankodi, Aakash (Bank of England); Silvestri, Laura (Bank of England) |
| Abstract: | We use transaction-level data to study trading and clearing relationships between dealers (ie, Gilt-edged Market Makers and clearing members) and their clients, and price discovery in the UK gilt cash and futures markets in 2016. Using a network approach we analyse the distribution of trading and clearing relationships between dealers and clients, the concentration of the associated volumes and how these change over time. We find that volumes in each market are concentrated in a few key dealers, that clients tend to have relationships with a limited number of dealers and that such relationships and volumes were resilient during most of 2016, including around the EU referendum and subsequent policy announcements. We also assess the systemic risk that could be caused by the inability of those dealers operating across the two markets to perform their roles as clearing member and market maker, finding that there may be some scope for spillover effects from potential disruption in the cash market to the futures market through this channel. Finally, we find that order flows (that we proxy using net volume traded) of clients in the UK gilt futures market can affect cash prices, suggesting that the futures market plays a role in price discovery in the cash market. |
| Keywords: | Gilt cash and futures markets; price discovery; network analysis; financial stability; resilience |
| JEL: | G10 G20 |
| Date: | 2022–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0991&r=net |
| By: | Elie Kapengut; Bruce Mizrach |
| Abstract: | On September 15, 2022, the Ethereum network adopted a proof-of-stake (PoS) consensus mechanism. We study the impact on the network and competing platforms in a short event window around the Beacon chain merge. We find that the transition to PoS has reduced energy consumption by 99.98%. Miners have not transformed into validators, and total block reward income has fallen by 95.6%. The validator network's Herfindahl index is 1,159, 8.6% lower than the miners' prior to the merge. Ethereum supply growth has fallen nearly 95%. Transaction fees for Ether have nearly doubled and token transaction fees have increased 23.7%. The time between consecutive blocks is now steady at 12 seconds, a speed increase of 18.9%. Fewer transactions are being included in each block though, so the transactions per second have actually fallen by 58.2%. On Polygon, Matic fees rose 21.7% and token fees 31.7%. Polygon also slows, processing 12.7% fewer transactions per second. Solana's fees and speed are unaffected by the merge. Stablecoin transfer volumes rise on all three networks. Polygon has the largest gain for USD Coin, 230%, and the Mainnet the largest for Tether, 86%. |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2210.13655&r=net |