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on Network Economics |
| By: | Yann Bramoullé (Aix-Marseille Univ, CNRS, AMSE, Marseille, France.); Rachel E Kranton (Duke University, Durham, US) |
| Abstract: | What patterns of economic relations arise when people are altruistic rather than strategically self-interested? This paper introduces an altruism network into a simple model of choice among partners for economic activity. With concave utility, agents effectively become inequality averse towards friends and family. Rich agents preferentially choose to work with poor friends despite productivity losses. Hence, network inequality-the divergence in incomes within sets of friends and family-is key to how altruism shapes economic relations and output. Skill homophily also plays a role; preferential contracts and productivity losses decline when rich agents have poor friends with requisite skills. |
| Date: | 2022–02 |
| URL: | https://d.repec.org/n?u=RePEc:aim:wpaimx:2202&r= |
| By: | Konda, Bruhan (UNU-MERIT, Maastricht University); González‐Sauri, Mario (UNU-MERIT, Maastricht University); Cowan, Robin (UNU-MERIT, Maastricht University); Yashodha, Yashodha (International Rice Research Institute (IRRI), India); Chellattan Veettil, Prakashan (International Rice Research Institute (IRRI), India) |
| Abstract: | Most network studies in agriculture examine uni-dimensional connections between individuals to understand the effect of social networks on outcomes. However, in most real-world scenarios, network members' exchanges happen through multiple relationships and not accounting for such multi-dimensional interconnections may lead to biased estimate of social network effects. This study aims to unravel the consequences of not accounting such multidimensional networks by investigating the individual and joint effects of multiple connections (relationships) that exist among households on agricultural output. We use census data from three villages of Odisha, India that enables us to account for three types of relationships viz. information networks (knowledge sharing), credit networks (resource sharing) and friendship (social bonding) between households. We estimate the social network effect by combining both econometric (IV regression) and network (directed networks) techniques to address the problems of endogeneity. The joint effect of multiple networks is estimated using the multiplex network framework. We find that information flows are crucial to improve agricultural output when networks are accounted individually. However, the joint effect of all three networks using multiplex shows a significantly positive influence, indicating complementarity across relationships. In addition, we found evidence for the mediating role of interpersonal relationships (friendship network) in enhancing gains from the information flow. |
| Keywords: | Agriculture production, Social network, Multiplex networks, knowledge sharing, Resource sharing, Friendship |
| JEL: | C26 D83 O13 Q12 |
| Date: | 2021–07–21 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2021030&r= |
| By: | Stern, Samuel; Livan, Giacomo |
| Abstract: | We investigate the impact of noise and topology on opinion diversity in social networks. We do so by extending well-established models of opinion dynamics to a stochastic setting where agents are subject both to assimilative forces by their local social interactions, as well as to idiosyncratic factors preventing their population from reaching consensus. We model the latter to account for both scenarios where noise is entirely exogenous to peer influence and cases where it is instead endogenous, arising from the agents' desire to maintain some uniqueness in their opinions. We derive a general analytical expression for opinion diversity, which holds for any network and depends on the network's topology through its spectral properties alone. Using this expression, we find that opinion diversity decreases as communities and clusters are broken down. We test our predictions against data describing empirical influence networks between major news outlets and find that incorporating our measure in linear models for the sentiment expressed by such sources on a variety of topics yields a notable improvement in terms of explanatory power. |
| Keywords: | network science; opinion dynamics; social networks; PSRC Early Career Fellowship in Digital Economy (grant no. EP/ N006062/1 |
| JEL: | C1 |
| Date: | 2021–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:113424&r= |
| By: | Leonardo Costa Ribeiro (Cedeplar/UFMG); Jorge Nogueira de Paiva Britto (Universidade Federal Fluminense); Eduardo da Motta e Albuquerque (Cedeplar/UFMG) |
| Abstract: | The unit of analysis of this paper is an international knowledge link (IKL), a knowledge flow that leaves a trace and connects two nodes – different institutions, firms and universities, in different countries. We present and analyze 17,240,834 international knowledge links (data from 2017). These international knowledge links form three basic networks. These three international layers overlap and interweave, forming a network of networks. The contribution of this paper is the identification and preliminary analysis of this overlapping and intertwinement. These networks are robust and their properties suggest a hierarchical structure of a multilayer network that is asymmetric. These networks are interpreted as new layers of innovation systems, with implications for the dynamic of innovation – a reorganization of different levels of innovation systems, now a more complicated structure with interaction between local, sectoral and national levels, as well as these overlapping international networks. |
| Keywords: | International Knowledge flows; Innovation Systems; Networks of networks |
| JEL: | O32 O34 O39 |
| Date: | 2022–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdp:texdis:td640&r= |
| By: | Manuela Pedio |
| Abstract: | The Great Financial Crisis of 2008 – 2009 has raised the attention of policy-makers and researchers about the interconnectedness among the volatility of the returns of financial assets as a potential source of risk that extends beyond the usual changes in correlations and include transmission channels that operate through the higher order co-moments of returns. In this paper, we investigate whether a newly developed, forward-looking measure of volatility spillover risk based on option implied volatilities shows any predictive power for stock returns. We also compare the predictive performance of this measure with that of the volatility spillover index proposed by Diebold and Yilmaz (2008, 2012), which is based on realized, backward-looking volatilities instead. While both measures show evidence of in-sample predictive power, only the option-implied measure is able to produce out-of-sample forecasts that outperform a simple historical mean benchmark. |
| Keywords: | connectedness, volatility networks, implied volatility, realized volatility, equity return predictability, spillover risk |
| JEL: | G12 G17 |
| Date: | 2021 |
| URL: | https://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp21154&r= |
| By: | Rute Martins Caeiro |
| Abstract: | This paper analyses the pathways of technology diffusion through social networks, following the experimental introduction of new technologies in Guinea-Bissau. In the context of an agricultural extension project, we document both the direct effects of this intervention and subsequent diffusion from trainees to the wider community. In order to test for social learning, we exploit a detailed census of households and social connections across different social dimensions. |
| Keywords: | Agriculture, Technology, Knowledge diffusion, Social networks, Technological innovations, Learning |
| Date: | 2022 |
| URL: | https://d.repec.org/n?u=RePEc:unu:wpaper:wp-2022-7&r= |