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on Network Economics |
| By: | Andreoni, Antonio; Anzolin, Guendalina; Labrunie, Mateus; Spinola, Danilo |
| Abstract: | This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramatic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial policy. |
| Keywords: | Digital Production Technology (DPT); DPT Classification; Network Analysis; Bilateral Trade; Digitalisation patterns. |
| Date: | 2023–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:akf:cafewp:15064&r=net |
| By: | Tetsuji Okazaki; Tomoko Matsumoto |
| Abstract: | Modern state-building brings profound political and economic transformations, challenging established elites and opening doors for emerging ones. While previous empirical studies have explored feudal elites persistence and emerging elites struggles, limited research has examined how emerging elites integrate into existing elite networks. This study investigates the responses of old and new elites during modernization. By constructing a unique dataset detailing kinship connections among Japanese elites in 1902, 1914, and 1927, we revealed shifts in elite kinship networks and their influence on controlling political and economic resources. The findings indicate that modernization transformed the Japanese elite community, with many commoners becoming elite by 1902. Nonetheless, these new elites often found themselves isolated within that community as they lacked kinship ties with other elites. Conversely, peerage political elites already held centrality in the elite kinship network in 1902, and their influence continued to grow over time. However, by 1927, the new economic elites, initially without kinship networks, had managed to establish connections within the elite community, leading to the emergence of an expanded and hierarchical elite community, blending the old and new elites, in which an individuals centrality in the network became closely linked to his/her political or economic position. Keywords : Modern state-building, Elite, Kinship network, Modernization, Network analysis |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:cnn:wpaper:23-017e&r=net |
| By: | Andrea Auconi |
| Abstract: | A minimal stochastic dynamical model of the interbank network is introduced, with linear interactions mediated by an integral of recent variations. Defining stress as the variance over the banks' states, the interaction correction to the stress expectation is derived and studied on the short-medium timescale in an expansion. It is shown that, while different interaction matrices can amplify or absorb fluctuations, on average interactions increase the stress expectation. More in general, this analytical framework enables to estimate the impact of uncertainty about financial exposures, and to draw conclusions about the importance of disclosure. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.17875&r=net |
| By: | Nevermann, Daniel; Heckmann, Lotta |
| Abstract: | Despite the ongoing consolidation trend in the banking industry and the attention some mergers (in particular between large banks) have been receiving, there is no consistent picture of the impact of mergers on the stability of the financial system. In this paper, we aim to provide a universal framework to study the generic effect of mergers and acquisitions on the resilience of financial systems based on different network models. We investigate the impact of a wide variety of model assumptions, e.g. connectivity, contagion channel and the merger process, on different static and dynamic stability measures. We provide a range of theoretical results highlighting the mechanisms that influence systemic risk in consolidated financial systems. Our main finding is that merger activities can stabilize or destabilize the modelled financial network, depending on various details such as the connectivity of the network and the assumed merger process. Merger activities can increase diversification of single banks and support their resilience to shocks, and may slow down contagious default. However, merger activities can also decrease stability if, for example, the network is driven into the contagion window or insufficiently stable banks emerge in key positions in the network. |
| Keywords: | Financial network model, Mergers and Acquisitions, Financial Stability, Contagion |
| JEL: | G01 G21 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:280415&r=net |
| By: | Deborah Miori; Constantin Petrov |
| Abstract: | Starting from a corpus of economic articles from The Wall Street Journal, we present a novel systematic way to analyse news content that evolves over time. We leverage on state-of-the-art natural language processing techniques (i.e. GPT3.5) to extract the most important entities of each article available, and aggregate co-occurrence of entities in a related graph at the weekly level. Network analysis techniques and fuzzy community detection are tested on the proposed set of graphs, and a framework is introduced that allows systematic but interpretable detection of topics and narratives. In parallel, we propose to consider the sentiment around main entities of an article as a more accurate proxy for the overall sentiment of such piece of text, and describe a case-study to motivate this choice. Finally, we design features that characterise the type and structure of news within each week, and map them to moments of financial markets dislocations. The latter are identified as dates with unusually high volatility across asset classes, and we find quantitative evidence that they relate to instances of high entropy in the high-dimensional space of interconnected news. This result further motivates the pursued efforts to provide a novel framework for the systematic analysis of narratives within news. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.14419&r=net |
| By: | Lucas Paiva de Carvalho; Tanya Araújo |
| Abstract: | Using a metric related to the returns correlation, a method is applied to the reconstruction of an economic space from Exchange-Traded Funds (ETFs) data. In the past, the same method was used in a geometrical analysis of times series of stock returns implying that the most of the systematic information of that market is contained in a space of small dimension. Here we have worked with ten years of daily returns of 85 ETF securities and the same dimensional reduction was obtained. Having a metric defined in the space of ETF securities, a topological approach is used to define a complete network of ETFs and its corresponding Minimum Spanning Tree (MST). An outstanding separation of the two main classes of securities over the MST is uncovered. The dimensional reduction as well as the uncovered pattern in the topological structure, they both emerge from the data itself rather than from any modelling resolution. |
| Keywords: | Dimensional Reduction, Sthocastic Geometry, Market Networks, Financial Markets, ETFs, Financial Crises. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp03022023&r=net |
| By: | Jana Hlavinova; Birgit Rudloff; Alexander Smirnow |
| Abstract: | In recent years, it has become apparent that an isolated microprudential approach to capital adequacy requirements of individual institutions is insufficient. It can increase the homogeneity of the financial system and ultimately the cost to society. For this reason, the focus of the financial and mathematical literature has shifted towards the macroprudential regulation of the financial network as a whole. In particular, systemic risk measures have been discussed as a risk measurement and mitigation tool. In this spirit, we adopt a general approach of multivariate, set-valued risk measures and combine it with the notion of intrinsic risk measures. In order to define the risk of a financial position, intrinsic risk measures utilise only internal capital, which is received when part of the currently held assets are sold, instead of relying on external capital. We translate this methodology into the systemic framework and show that systemic intrinsic risk measures have desirable properties such as the set-valued equivalents of monotonicity and quasi-convexity. Furthermore, for convex acceptance sets we derive a dual representation of the systemic intrinsic risk measure. We apply our methodology to a modified Eisenberg-Noe network of banks and discuss the appeal of this approach from a regulatory perspective, as it does not elevate the financial system with external capital. We show evidence that this approach allows to mitigate systemic risk by moving the network towards more stable assets. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.14588&r=net |