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on Network Economics |
| By: | Kieran Marray |
| Abstract: | Empirical researchers often estimate spillover effects by fitting linear or non-linear regression models to sampled network data. Here, we show that common sampling schemes induce dependence between observed and unobserved spillovers. Due to this dependence, spillover estimates are biased, often upwards. We then show how researchers can construct unbiased estimates of spillover effects by rescaling using aggregate network statistics. Our results can be used to bound true effect sizes, determine robustness of estimates to missingness, and construct estimates when missingness depends on treatment. We apply our results to re-estimate the propagation of idiosyncratic shocks between US public firms, and peer effects amongst USAFA cadets. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.17154 |
| By: | Lukas Rosenberger; W. Walker Hanlon; Carl Hallmann |
| Abstract: | How did Britain sustain faster rates of economic growth than comparable European countries, such as France, during the Industrial Revolution? We argue that Britain possessed an important but underappreciated innovation advantage: British inventors worked in technologies that were more central within the innovation network. We offer a new approach for measuring the innovation network using patent data from Britain and France in the late-18th and early-19th century. We show that the network influenced innovation outcomes and demonstrate that British inventors worked in more central technologies within the innovation network than French inventors. Drawing on recently developed theoretical tools, and using a novel estimation strategy, we quantify the implications for technology growth rates in Britain compared to France. Our results indicate that the shape of the innovation network, and the location of British inventors within it, explains an important share of the more rapid technological change and industrial growth in Britain during the Industrial Revolution. |
| Keywords: | industrial revolution, innovation network, patents, economic growth |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11299 |
| By: | Husain, Tehreem; Buchnea, Emily |
| Abstract: | This article examines the role of agents and how their brokerage activities influenced the composition, shape and size of Baring’s business networks in Argentinian railways during 1880–1905. Baring was heavily involved in Argentine sovereign and railway financing and relied on trusted agents, who acted as important conduits of information, to manage their business empire. We explore 2700 pieces of correspondence in the form of letters and telegrams to illustrate Baring’s network over time. Studying the case of Argentinian railways, the correspondences reveal the longevity of Baring’s network and agents’ brokerage roles over time in response to changing local and global economic currents. Through this rich qualitative data and network analysis, we contribute to understanding agent’s brokerage and network change over time. By highlighting the role of invisible actors in the form of agents, the article contributes to understanding infrastructure finance, financial globalisation and more generally, the global history of capitalism. |
| Keywords: | networks; agents; railways; brokerage; baring |
| JEL: | D85 L14 N20 N80 |
| Date: | 2024–10–23 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:125980 |
| By: | Dragos Gorduza; Yaxuan Kong; Xiaowen Dong; Stefan Zohren |
| Abstract: | We investigate the effectiveness of a momentum trading signal based on the coverage network of financial analysts. This signal builds on the key information-brokerage role financial sell-side analysts play in modern stock markets. The baskets of stocks covered by each analyst can be used to construct a network between firms whose edge weights represent the number of analysts jointly covering both firms. Although the link between financial analysts coverage and co-movement of firms' stock prices has been investigated in the literature, little effort has been made to systematically learn the most effective combination of signals from firms covered jointly by analysts in order to benefit from any spillover effect. To fill this gap, we build a trading strategy which leverages the analyst coverage network using a graph attention network. More specifically, our model learns to aggregate information from individual firm features and signals from neighbouring firms in a node-level forecasting task. We develop a portfolio based on those predictions which we demonstrate to exhibit an annualized returns of 29.44% and a Sharpe ratio of 4.06 substantially outperforming market baselines and existing graph machine learning based frameworks. We further investigate the performance and robustness of this strategy through extensive empirical analysis. Our paper represents one of the first attempts in using graph machine learning to extract actionable knowledge from the analyst coverage network for practical financial applications. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.20597 |
| By: | Clément Marinos (LEGO - Laboratoire d'Economie et de Gestion de l'Ouest - UBS - Université de Bretagne Sud - UBO - Université de Brest - IMT - Institut Mines-Télécom [Paris] - IBSHS - Institut Brestois des Sciences de l'Homme et de la Société - UBO - Université de Brest - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris], MARSOUIN - Môle Armoricain de Recherche sur la SOciété de l'information et des usages d'INternet - UR - Université de Rennes - UBS - Université de Bretagne Sud - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - UBO - Université de Brest - IMT - Institut Mines-Télécom [Paris] - UR2 - Université de Rennes 2 - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris]) |
| Abstract: | In this article, we aim to highlight the importance of digital platforms, particularly the social network Facebook, in online relationships among digital nomads. To achieve this, we employ social capital theory, conducting both quantitative and qualitative analyses of user groups and posts. The results reveal a strong geographical dimension in the search for social capital, as well as a relative balance between bridging and bonding capital. We also underscore a limited presence of local actors on the social network, despite the richness of interactions among nomads, preferring virtual relationships among peers. |
| Abstract: | Dans cet article, nous cherchons à mettre en évidence l'importance des plateformes numériques et plus particulièrement du réseau social Facebook dans les relations en ligne entre nomades numériques. Pour y parvenir, nous convoquons la théorie du capital social en analysant quantitativement et qualitativement les groupes et les posts des usagers. Les résultats montrent la forte dimension géographique dans la recherche de capital social ainsi qu'un relatif équilibre entre capital qui relie (bridging) et capital qui renforce (bonding). Nous mettons par ailleurs en évidence une faible présence des acteurs locaux sur le réseau social malgré la richesse des échanges entre nomades qui ont tendance à privilégier les relations virtuelles entre pairs. |
| Keywords: | digital nomads, social capital, territory, digital social networks, Facebook, online communities, nomades numériques, capital social, territoire, réseaux sociaux numériques, communautés en ligne, capital social territoire réseaux sociaux numériques Facebook communautés en ligne digital nomads social capital territory digital social networks Facebook online communities, communautés en ligne digital nomads |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04738405 |
| By: | Xu, Shuanglei (School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China); Deng, Youyi (School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China); Nepal, Rabindra (School of Business, Faculty of Business and Law, University of Wollongong, New South Wales, Australia); Jamasb, Tooraj (Department of Economics, Copenhagen Business School) |
| Abstract: | Since the Russian-Ukrainian conflict, the European Union (EU)’s energy imports have faced challenges, and energy security has come to the fore. Focusing on the EU and its relations with major energy trading countries, we adopt a social network approach (SNA) and exponential random graph model (ERGM) to analyze the energy trade impact of the conflict. We use data from a sample of 47 countries from 2014-2023 to explore the characteristics of the structural evolution of the EU’s conventional and renewable trade networks and the influencing mechanisms behind them. As a result of the conflict and the global trend towards decoupling, the EU’s conventional trade network is undergoing a contraction. Meanwhile, its renewable trade network is thriving, indicating a shift in energy structures; the core-periphery undergoing restructuring, Russia fading out of the core circle of the trade, and the US becoming a key hub connecting all parties. Germany, France, and the Netherlands play the role of important importers as core nodes of the network. Mechanistic analysis shows that mutual plays an important role in multilateral trade; rising geopolitical risks, while posing a barrier to energy imports, have facilitated a boom in renewable trade; economic size and trade openness have positively driven energy trade. Foreign investment, intellectual property rights, and levels of population and urbanization have had a differentiated impact on the two types of energy trade; geographic proximity, linguistic commonality, and free trade agreements positively contribute to the construction and maintenance of energy trade networks. This study depicts the dynamics of EU energy trade under geopolitical turbulence, expands the research methodology in this area, deepens the understanding of energy geopolitics, and informs the transformation of the EU’s energy structure. |
| Keywords: | European Union; Conventional energy trade; Renewable energy trade; Social network; Exponential random graph model |
| JEL: | F18 Q43 |
| Date: | 2024–10–30 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:cbsnow:2024_014 |
| By: | Di Addario, Sabrina (Bank of Italy); Feng, Zhexin (University of Essex); Serafinelli, Michel (King's College London) |
| Abstract: | This paper presents direct evidence on how firms' innovation is affected by access to knowledgeable labor through co-worker network connections. We use a unique dataset that matches patent data to administrative employer - employee records from "Third Italy" - a region with many successful industrial clusters. Establishment closures displacing inventors generate supply shocks of knowledgeable labor to firms that employ the inventors' previous co-workers. We estimate event-study models where the treatment is the displacement of a "connected" inventor (i.e., a previous coworker of a current employee of the focal firm). We show that the displacement of a connected inventor significantly increases connected inventors' hiring. Moreover, the improved access to knowledgeable workers raises firms innovative activity. We provide evidence supporting the main hypothesized channel of knowledge transfer through firm-to-firm labor mobility by estimating IV specifications where we use the displacement of a connected inventor as an instrument to hire a connected inventor. Overall, estimates indicate that firms exploit displacements to recruit connected inventors and the improved capacity to employ knowledgeable labor within the network increases innovation. |
| Keywords: | social connections, firm-to-firm labor mobility, patents, establishment closure |
| JEL: | J60 O30 J23 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17398 |
| By: | Li, Jiangtao (Singapore Management University); Tang, Rui (Department of Economics, Hong Kong University of Science and Technology); Zhang, Mu (Department of Economics, University of Michigan) |
| Abstract: | We present a model of associative networks that captures how a decision maker expands her consideration set through mental associations between alternatives. This model serves as a tool to understand the influence of association on decision making. As a proof of concept, we characterize this model within a random attention framework and demonstrate that all the relevant parameters are uniquely identifiable. Notably, in a novel choice domain where not all observable alternatives are available, the presence of unavailable alternatives can affect the choice frequencies of other alternatives through association. |
| Keywords: | associative network; random attention; consideration set; random choice; availability and observability |
| JEL: | D01 D91 |
| Date: | 2024–09–16 |
| URL: | https://d.repec.org/n?u=RePEc:ris:smuesw:2024_009 |
| By: | Simon Fuchs; Woan Foong Wong |
| Abstract: | We examine the economic and environmental impacts of improvements and disruptions in multimodal transport networks. Our quantitative spatial equilibrium model incorporates routing over multiple modes and congestion at intermodal terminals. We estimate a modal substitution elasticity with highway and rail data, and a terminal congestion elasticity with vessel-positioning data. Calibrated to the U.S. freight network, our model identifies key bottlenecks and quantifies $300-700 million in additional real GDP gains from intermodal terminal improvements. These gains are 2.5 times higher without congestion, and substitution away from roads yield additional environmental benefits. Losing rail network access, factoring in modal substitution and general equilibrium effects, is estimated to reduce real GDP by $230 billion. |
| Keywords: | multimodal transport, transport network, spatial equilibrium, endogenous transport costs, infrastructure investments, disruptions, bottlenecks |
| JEL: | F11 R12 R42 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11362 |
| By: | Tekilu Tadesse Choramo; Jemal Abafita; Yerali Gandica; Luis E C Rocha |
| Abstract: | Global and regional integration has grown significantly in recent decades, boosting intra-African trade and positively impacting national economies through trade diversification and sustainable development. However, existing measures of economic integration often fail to capture the complex interactions among trading partners. This study addresses this gap by using complex network analysis and dynamic panel regression techniques to identify factors driving economic integration in Africa, based on data from 2002 to 2019. The results show that economic development, institutional quality, regional trade agreements, human capital, FDI, and infrastructure positively influence a country's position in the African trade network. Conversely, trade costs, the global financial crisis, and regional overlapping memberships negatively affect network based integration. Our findings suggest that enhancing a country's connectivity in the African trade network involves identifying key economic and institutional factors of trade partners and strategically focusing on continent-wide agreements rather than just regional ones to boost economic growth. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.21019 |
| By: | Jung HUR (Sogang University); Chin Hee HAHN (Gachon University) |
| Abstract: | This paper examines the impact of the 2011 Japanese earthquake on the sales and purchases of firms that have an intra-firm network with Japan. Using unique firm-level data of the Republic of Korea (henceforth, Korea) and applying a difference-in-differences model, we find two results. First, following the 2011 Japanese earthquake, Japanese subsidiaries in Korea switched their intra-firm sales patterns with a reduction in intra-firm export and an increase in intra-firm domestic sales, compared to non-Japan foreign subsidiaries in Korea. Second, however, the sales or purchases of Korean mother firms with subsidiaries in Japan were negatively affected, compared to either non-foreign direct investment (FDI) firms or FDI firms without subsidiaries in Japan. The results imply that the Japanese subsidiaries in Korea had a relatively resilient and flexible intra-firm network, whilst the Korean firms with subsidiaries in Japan did not. |
| Keywords: | FDI firms, Intra-firm Sales and Purchases |
| JEL: | F10 F23 E32 |
| Date: | 2024–09–26 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-25 |
| By: | Victor Le Coz; Nolwenn Allaire; Michael Benzaquen; Damien Challet |
| Abstract: | Using the secured transactions recorded within the Money Markets Statistical Reporting database of the European Central Bank, we test several stylized facts regarding interbank market of the 47 largest banks in the eurozone. We observe that the surge in the volume of traded evergreen repurchase agreements followed the introduction of the LCR regulation and we measure a rate of collateral re-use consistent with the literature. Regarding the topology of the interbank network, we confirm the high level of network stability but observe a higher density and a higher in- and out-degree symmetry than what is reported for unsecured markets. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.16021 |
| By: | Antonio Cabrales; Manu García; David Ramos Muñoz; Angel Sánchez |
| Abstract: | We study the evolution of interest in climate change among different actors within the population and how the interest of these actors affects one another. First, we document the evolution of interest for each actor individually, and then we provide a model of cross-influences between them. We estimate this model using a Vector Autoregression (VAR). We measure interest among the general public, the European Parliament, central banks, general interest science journals, and economics journals by creating a Climate Change Index (CCI) based on mentions of climate change in these domains. Except for general interest science journals, the index for all other domains has started showing significant values only recently, and it tends to fluctuate considerably. In terms of influence, the European Parliament and the media affect one another, but the trend in science remains relatively independent of the others. |
| Keywords: | climate change; social norms; text analysis; social networks |
| JEL: | Q54 Q58 D85 A13 |
| Date: | 2024–11–08 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedlwp:99043 |
| By: | Chang, Pao-li (School of Economics, Singapore Management University); MAKIOKA, Ryo (School of Economics and Business, Hokkaido University); Ng, Bo Lin (School of Economics, Singapore Management University); Yang, Zhenlin (School of Economics, Singapore Management University) |
| Abstract: | This paper proposes a three-stage efficient GMM estimation algorithm for estimating firm-level production functions given spatial dependence across firms due to supplier-customer relationships, sharing of input markets, or knowledge spillover. The procedure builds on Ackerberg, Caves and Frazer (2015) and Wooldridge (2009), but in addition, allows the productivity process to depend on the lagged output levels and lagged input usages of related firms, and spatially correlated productivity shocks across firms, where the set of related firms can differ across the three dimensions of spatial dependence. We establish the asymptotic properties of the proposed estimator, and conduct Monte Carlo simulations to validate these properties. The proposed estimator is consistent under DGPs with or without spatial dependence, and with strong/weak or positive/negative spatial dependence. In contrast, the conventional estimators lead to biased estimates of the production function parameters if the underlying DGPs have spatial dependence structure, and the magnitudes of the bias increase with the strength of spatial dependence in the underlying DGPs. We apply the proposed estimation algorithm to a Japanese firm-to-firm dataset of 14, 178 firms during the period 2009–2018. We find significant and positive spatial coefficients in the Japanese firm-level productivity process via all three channels proposed above. |
| Keywords: | productivity estimation; spatial dependence; supplier-customer network; factor market pooling; knowledge spillover |
| JEL: | C31 D24 |
| Date: | 2024–10–15 |
| URL: | https://d.repec.org/n?u=RePEc:ris:smuesw:2024_010 |