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on Network Economics |
| By: | Rediet Abebe; Nicole Immorlica; Jon Kleinberg; Brendan Lucier; Ali Shirali |
| Abstract: | The tendency for individuals to form social ties with others who are similar to themselves, known as homophily, is one of the most robust sociological principles. Since this phenomenon can lead to patterns of interactions that segregate people along different demographic dimensions, it can also lead to inequalities in access to information, resources, and opportunities. As we consider potential interventions that might alleviate the effects of segregation, we face the challenge that homophily constitutes a pervasive and organic force that is difficult to push back against. Designing effective interventions can therefore benefit from identifying counterbalancing social processes that might be harnessed to work in opposition to segregation. In this work, we show that triadic closure -- another common phenomenon that posits that individuals with a mutual connection are more likely to be connected to one another -- can be one such process. In doing so, we challenge a long-held belief that triadic closure and homophily work in tandem. By analyzing several fundamental network models using popular integration measures, we demonstrate the desegregating potential of triadic closure. We further empirically investigate this effect on real-world dynamic networks, surfacing observations that mirror our theoretical findings. We leverage these insights to discuss simple interventions that can help reduce segregation in settings that exhibit an interplay between triadic closure and homophily. We conclude with a discussion on qualitative implications for the design of interventions in settings where individuals arrive in an online fashion, and the designer can influence the initial set of connections. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.13658&r= |
| By: | Giacomo Vaccario; Luca Verginer; Antonios Garas; Mario V. Tomasello; Frank Schweitzer |
| Abstract: | Firms' innovation potential depends on their position in the R&D network. But details on this relation remain unclear because measures to quantify network embeddedness have been controversially discussed. We propose and validate a new measure, coreness, obtained from the weighted k-core decomposition of the R&D network. Using data on R&D alliances, we analyse the change of coreness for 14,000 firms over 25 years and patenting activity. A regression analysis demonstrates that coreness explains firms' R&D output by predicting future patenting. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.07677&r= |
| By: | Anantha Divakaruni; Peter Zimmerman |
| Abstract: | The Lightning Network (LN) is a means of netting Bitcoin payments outside the blockchain. We find a significant association between LN adoption and reduced blockchain congestion, suggesting that the LN has helped improve the efficiency of Bitcoin as a means of payment. This improvement cannot be explained by other factors, such as changes in demand or the adoption of SegWit. We find mixed evidence on whether increased centralization in the Lightning Network has improved its efficiency. Our findings have implications for the future of cryptocurrencies as a means of payment and their environmental footprint. |
| Keywords: | bitcoin; blockchain; cryptocurrency; Lightning Network; payments |
| JEL: | E42 G10 |
| Date: | 2022–06–21 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedcwq:94363&r= |
| By: | Massfeller, Anna; Storm, Hugo |
| Abstract: | Farmers' decisions to adopt novel technologies are likely to be influenced by the behaviour of other farmers. Those effects are typically described as peer effects and are intensively studied. What remains unclear from the existing literature, however, is the general mechanism underlying those peer effects. Specifically, existing literature does not seem to clearly distinguish between 1) peer effects that result from information exchange, i.e. farmers talking to each other and 2) from the possibility of field observation, i.e. the possibility to observe the application of technology, the outcomes of the application, and the general state of the fields. We aim to study if information exchange and field observations are indeed two different mechanisms both leading to “peer effects”. Therefore, we extend the existing theoretical assumptions on social learning and empirically explore the relationship between the two sources, hypothesizing that each provides complementary information due to the different underlying mechanisms. To study those two mechanisms, we focus on the example of mechanical weeding in sugar beets in Germany. We conduct an online survey among sugar beet farmers on the use of mechanical weeding in early 2022. Distinguishing between information exchange and field observation as two different mechanisms that drive peer effects, and understanding how they relate to each other, is crucial for designing effective extension services and policies to promote the adoption of desired farming practices. |
| Keywords: | Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aesc22:321154&r= |
| By: | Shayegheh Ashourizadeh; Mehrzad Saeedikiya |
| Abstract: | The authors hypothesised that export develops in the network of business collaborations that are embedded in migration status. In that, collaborative networking positively affects export performance and immigrant entrepreneurs enjoy higher collaborative networking than native entrepreneurs due to their advantage of being embedded in the home and the host country. Moreover, the advantage of being an immigrant promotes the benefits of collaborative networking for export compared to those of native entrepreneurs. A total of 47,200 entrepreneurs starting, running and owning firms in 71 countries were surveyed by Global Entrepreneurship Monitor and analysed through the hierarchical linear modelling technique. Collaborative networking facilitated export and migration status influenced entrepreneur networking, in that, immigrant entrepreneurs had a higher level of collaborative networking than native entrepreneurs. Consequently, immigrant entrepreneurs seemed to have benefited from their network collaborations more than their native counterparts did. This study sheds light on how immigrant entrepreneur network collaborations can be effective for their exporting. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.13171&r= |
| By: | Darryl V. Hill; Rodney P. Hughes; Matthew A. Lenard; David D. Liebowitz; Lindsay C. Page |
| Abstract: | Policy makers periodically consider using student assignment policies to improve educational outcomes by altering the socio-economic and academic skill composition of schools. We exploit the quasi-random reassignment of students across schools in the Wake County Public School System to estimate the academic and behavioral effects of being reassigned to a different school and, separately, of shifts in peer characteristics. We rule out all but substantively small effects of transitioning to a different school as a result of reassignment on test scores, course grades and chronic absenteeism. In contrast, increasing the achievement levels of students' peers improves students' math and ELA test scores but harms their ELA course grades. Test score benefits accrue primarily to students from higher-income families, though students with lower family income or lower prior performance still benefit. Our results suggest that student assignment policies that relocate students to avoid the over-concentration of lower-achieving students or those from lower-income families can accomplish equity goals (despite important caveats), although these reassignments may reduce achievement for students from higher- income backgrounds. |
| JEL: | H75 I21 I24 I28 J24 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30085&r= |
| By: | Yash Deshpande; Elchanan Mossel; Youngtak Sohn |
| Abstract: | Bayesian models of group learning are studied in Economics since the 1970s and more recently in computational linguistics. The models from Economics postulate that agents maximize utility in their communication and actions. The Economics models do not explain the "probability matching" phenomena that are observed in many experimental studies. To address these observations, Bayesian models that do not formally fit into the economic utility maximization framework were introduced. In these models individuals sample from their posteriors in communication. In this work, we study the asymptotic behavior of such models on connected networks with repeated communication. Perhaps surprisingly, despite the fact that individual agents are not utility maximizers in the classical sense, we establish that the individuals ultimately agree and furthermore show that the limiting posterior is Bayes optimal. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.11561&r= |