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on Network Economics |
| By: | John Higgins (Department of Economics, University of Wisconsin, Madison, WI 53706, USA); Tarun Sabarwal (Department of Economics, University of Kansas, Lawrence, KS 66045, USA) |
| Abstract: | We study proliferation of an action in binary action network coordination games that are generalized to include global effects. This captures important aspects of proliferation of a particular action or narrative in online social networks, providing a basis to understand their impact on societal outcomes. Our model naturally captures complementarities among starting sets, network resilience, and global effects, and highlights interdependence in channels through which contagion spreads. We present new, natural, and computationally tractable algorithms to define and compute equilibrium objects that facilitate the general study of contagion in networks and prove their theoretical properties. Our algorithms are easy to implement and help to quantify relationships previously inaccessible due to computational intractability. Using these algorithms, we study the spread of contagion in scale-free networks with 1,000 players using millions of Monte Carlo simulations. Our analysis provides quantitative and qualitative insight into the design of policies to control or spread contagion in networks. The scope of application is enlarged given the many other situations across different fields that may be modeled using this framework. |
| Keywords: | Network games, coordination games, contagion, algorithmic computation |
| JEL: | C62 C72 |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:kan:wpaper:202211&r= |
| By: | Benny Kleinman (Princeton University); Ernest Liu (Princeton University); Stephen J. Redding (Princeton University) |
| Abstract: | We examine whether as countries become more economically dependent on a trade partner, they realign politically towards that trade partner. We use network measures of economic exposure to foreign productivity growth derived from the class of trade models with a constant trade elasticity. We establish causality using two different sources of quasi-experimental variation: China's emergence into the global economy and the reduction in the cost of air travel over time. In both cases, we find that increased economic friendship causes increased political friendship, and that our theory-based network measures dominate simpler measures of trading relationships between countries. |
| Keywords: | international relations, trade, productivity growth, real income |
| JEL: | F14 F15 F50 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:pri:cepsud:292&r= |
| By: | Swati Sharma (Institute of Economic Growth, Delhi) |
| Abstract: | Workplace interactions have been identified as a valuable source of information and career advancement. This study examines workplace interaction by looking at personal ties of 1744 blue-collar workers in 2 garment manufacturing units in the National Capital Region (NCR) of Delhi, India. Data analysis shows that men have a more expansive set of personal ties, even after controlling for variation in interpersonal and workplace-related characteristics. Women’s personal networks are smaller, clustered within their functional units and more homogeneous. While supervisors do not figure in personal networks of either gender, women are significantly less likely to mobilize interactions with supervisors for professional or personal purposes. Thus, women’s personal ties at the workplace exhibit patterns that are opposite of those identified by existing literature as instrumental for career advancement. |
| Keywords: | gender, workplace ties, social networks, garment manufacturing, India |
| JEL: | D21 D22 J40 M51 Z13 |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:awe:wpaper:426&r= |
| By: | Zheng Zhang; Yingsheng Ji; Jiachen Shen; Xi Zhang; Guangwen Yang |
| Abstract: | Risk assessment is a substantial problem for financial institutions that has been extensively studied both for its methodological richness and its various practical applications. With the expansion of inclusive finance, recent attentions are paid to micro and small-sized enterprises (MSEs). Compared with large companies, MSEs present a higher exposure rate to default owing to their insecure financial stability. Conventional efforts learn classifiers from historical data with elaborate feature engineering. However, the main obstacle for MSEs involves severe deficiency in credit-related information, which may degrade the performance of prediction. Besides, financial activities have diverse explicit and implicit relations, which have not been fully exploited for risk judgement in commercial banks. In particular, the observations on real data show that various relationships between company users have additional power in financial risk analysis. In this paper, we consider a graph of banking data, and propose a novel HIDAM model for the purpose. Specifically, we attempt to incorporate heterogeneous information network with rich attributes on multi-typed nodes and links for modeling the scenario of business banking service. To enhance feature representation of MSEs, we extract interactive information through meta-paths and fully exploit path information. Furthermore, we devise a hierarchical attention mechanism respectively to learn the importance of contents inside each meta-path and the importance of different metapahs. Experimental results verify that HIDAM outperforms state-of-the-art competitors on real-world banking data. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.11849&r= |
| By: | Daoju Peng (International School of Economics and Management, Capital University of Economics and Business, Beijing); Kang Shi (Department of Economics, Chinese University of Hong Kong); Juanyi Xu (Department of Economics, Hong Kong University of Science and Technology) |
| Abstract: | A salient feature of recent globalization is the emergence of global value chain, along which countries specialize in different positions. These difference of positions along the global production network may affect the business cycle comovement of two countries. Based on influence matrix derived from input-output linkage, a novel measure of distance is proposed to capture the heterogeneity between two countries in output response to country-specific technology shocks that propagate through global production network. We then show theoretically this distance is negatively correlated with output correlation across countries. To empirically test this conclusion, we relate the model to the data and calculate the distance and position measure using the world input-output table. The empirical result confirms a robust and significantly negative relationship between distance along the global value chain and business cycle synchronization. The closer the two countries' distance, the more comoved their output is. This result is robust to alternative distance measures and alternative output correlations. These findings thus offer new insights regarding international transmission of shocks through trade linkage. |
| Keywords: | Global Value Chain, Distance, Business Cycle Comovement |
| JEL: | F14 F44 F62 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:hke:wpaper:wp2020-05&r= |