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on Network Economics |
| By: | Abhijit Banerjee; Olivier Compte |
| Abstract: | We explore a model of non-Bayesian information aggregation in networks. Agents non-cooperatively choose among Friedkin-Johnsen type aggregation rules to maximize payoffs. The DeGroot rule is chosen in equilibrium if and only if there is noiseless information transmission, leading to consensus. With noisy transmission, while some disagreement is inevitable, the optimal choice of rule amplifies the disagreement: even with little noise, individuals place substantial weight on their own initial opinion in every period, exacerbating the disagreement. We use this framework to think about equilibrium versus socially efficient choice of rules and its connection to polarization of opinions across groups. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.08256&r=net |
| By: | Luca Paolo Merlino; Paolo Pin; Nicole Tabasso |
| Abstract: | We study the diffusion of a true and a false message (the rumor) in a social network. Upon hearing a message, individuals may believe it, disbelieve it, or debunk it through costly verification. Whenever the truth survives in steady state, so does the rumor. Communication intensity in itself is irrelevant for relative rumor prevalence, and the effect of homophily depends on the exact verification process and equilibrium verification rates. Our model highlights that successful policies in the fight against rumors increase individuals’ incentives to verify. (JEL D83, D85, L82, Z13) |
| Date: | 2023–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:ulb:ulbeco:2013/365073&r=net |
| By: | Kozo Kiyota (Keio University, Research Institute of Economy, Trade and Industry (RIETI), and Tokyo Center for Economic Research (TCER)) |
| Abstract: | In light of the importance of the machinery trade in global trade, this study examines whether the patterns of machinery exports changed significantly after the COVID19 pandemic. Frameworks of network analysis and structural break analysis are applied to monthly level bilateral export data from January 2016 to March 2022. The main findings are threefold. First, positive structural change is found in exports in major machinery-exporting countries. Second, negative structural change in centrality is found in Japan and some ASEAN Member States (AMS), which implies a decline in the relative importance of these countries in the global machinery network. Third, the decline in Japanese centrality was not caused by the decline in export values or number of destination countries. Rather, it is attributable to the decline in the centrality of Japan's export destination countries such as AMS. Noting that Japan has a relatively strong trade relationship with AMS, these results together suggest that the negative shock of the pandemic spread throughout the supply chain, which led to the decline in the relative importance of some countries - such as Japan - in the global machinery trade network. |
| Keywords: | Machinery trade; COVID-19 pandemic; Network; Centrality |
| JEL: | F14 F40 |
| Date: | 2023–08–16 |
| URL: | http://d.repec.org/n?u=RePEc:era:wpaper:dp-2023-10&r=net |
| By: | Antonio Andreoni (Department of Economics, SOAS University of London); Guendalina Anzolin (Centre for Science, Technology and Innovation Policy, Institute for Manufacturing, University of Cambridge); Mateus Labrunje (Centre of Development Studies and Cambridge Industrial Innovation Policy, University of Cambridge); Danilo Spinola (College of Accounting, Finance and Economics, Birmingham City Business School; Maastricht Economic Research Institute for Innovation and Technology (UNU-Merit); and South African Research Chair in Industrial Development, University of Johannesburg) |
| 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. |
| JEL: | O14 O33 F14 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:soa:wpaper:261&r=net |
| By: | Miguel Risco |
| Abstract: | In today’s world, social networks have a significant impact on information processes, shaping individuals’ beliefs and influencing their decisions. This paper proposes a model to understand how boundedly rational (DeGroot) individuals behave when seeking information to make decisions in situations where both social communication and private learning take place. The model assumes that information is a local public good, and individuals must decide how much effort to invest in costly information sources to improve their knowledge of the state of the world. Depending on the network structure and agents’ positions, some individuals will invest in private learning, while others will free-ride on the social supply of information. The model shows that multiple equilibria can arise, and uniqueness is controlled by the lowest eigenvalue of a matrix determined by the network. The lowest eigenvalue roughly captures how two-sided a network is. Two-sided networks feature multiple equilibria. Under a utilitarian perspective, agents would be more informed than they are in equilibrium. Social welfare would be improved if influential agents increased their information acquisition levels. |
| Keywords: | Information Acquisition, Learning, Public Goods, Network Effects, Information Diffusion, Bounded Rationality |
| JEL: | C72 D61 D83 D85 H41 |
| Date: | 2023–04 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2023_420v2&r=net |