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on Network Economics |
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Issue of 2018‒12‒24
four papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Frattini, Tommaso; Meschi, Elena |
| Abstract: | This paper provides new evidence on how the presence of immigrant peers in the classroom affects native student achievement. The analysis is based on longitudinal administrative data on two cohorts of vocational training students in Italy's largest region. Vocational training institutions provide the ideal setting for studying these effects because they attract not only disproportionately high shares of immigrants but also the lowest ability native students. We adopt a value added model, and exploit within-school variation both within and across cohorts for identification. Our results show small negative average effects on maths test scores that are larger for low ability native students, strongly non-linear and only observable in classes with a high (top 20%) immigrant concentration. These outcomes are driven by classes with a high average linguistic distance between immigrants and natives, with no apparent additional role played by ethnic diversity. |
| Keywords: | education; ethnic diversity; Immigration; linguistic distance; peer effects |
| JEL: | I20 J15 |
| Date: | 2018–11 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13305&r=net |
| By: | Goldberg, Jessica (University of Maryland); Macis, Mario (Johns Hopkins University); Chintagunta, Pradeep (University of Chicago) |
| Abstract: | Peer referrals are a common strategy for addressing asymmetric information in contexts such as the labor market. They could be especially valuable for increasing testing and treatment of infectious diseases, where peers may have advantages over health workers in both identifying new patients and providing them credible information, but they are rare in that context. In an experiment with 3,182 patients at 128 tuberculosis (TB) treatment centers in India, we find peers are indeed more effective than health workers in bringing in new suspects for testing, and low-cost incentives of about $US 3 per referral considerably increase the probability that current patients make referrals that result in the testing of new symptomatics and the identification of new TB cases. Peer outreach identifies new TB cases at 25%-35% of the cost of outreach by health workers and can be a valuable tool in combating infectious disease. |
| Keywords: | tuberculosis, referrals, social networks, case finding, incentives, India, health |
| JEL: | O1 I1 |
| Date: | 2018–11 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp11942&r=net |
| By: | Cortes-Corrales, Sebastián; Gorny, Paul M. |
| Abstract: | We investigate the behaviour of agents in bilateral contests within arbitrary network structures when valuations and efficiencies are heterogenous. These parameters are interpreted as measures of strength. We provide conditions for when unique, pure strategy equilibria exist. When a player starts attacking one player more strongly, others join in on fighting the victim. Different efficiencies in fighting make players fight those of similar strength. Centrality of a player (having more enemies) makes a player weaker and her opponents are more likely to attack with more effort. |
| Keywords: | Contest, conflict, networks, games on networks |
| JEL: | C72 D74 D85 |
| Date: | 2018–11–13 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:90001&r=net |
| By: | Fogli, Alessandra (Federal Reserve Bank of Minneapolis); Veldkamp, Laura (Columbia Graduate School of Business) |
| Abstract: | Does the pattern of social connections between individuals matter for macroeconomic outcomes? If so, where do these differences come from and how large are their effects? Using network analysis tools, we explore how different social network structures affect technology diffusion and thereby a country's rate of growth. The correlation between high-diffusion networks and income is strongly positive. But when we use a model to isolate the effect of a change in social networks, the effect can be positive, negative, or zero. The reason is that networks diffuse ideas and disease. Low-diffusion networks have evolved in countries where disease is prevalent because limited connectivity protects residents from epidemics. But a low-diffusion network in a low-disease environment needlessly compromises the diffusion of good ideas. In general, social networks have evolved to fit their economic and epidemiological environment. Trying to change networks in one country to mimic those in a higher-income country may well be counterproductive. |
| Keywords: | Growth; Development; Technology diffusion; Economic networks; Social networks; Pathogens; Disease |
| JEL: | E02 I1 O1 O33 |
| Date: | 2018–11–19 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedmsr:572&r=net |