Germs, Social Networks and Growth

A. Fogli, Laura L. Veldkamp
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引用次数: 78

Abstract

Does the pattern of social connections between individuals matter for macroeconomic outcomes? If so, where do differences in these patterns 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 on growth, the effect can be positive, negative, or zero. The reason is that networks diffuse both 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 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.
细菌,社会网络和增长
个人之间的社会联系模式对宏观经济结果有影响吗?如果是这样,这些模式的差异从何而来?它们的影响有多大?使用网络分析工具,我们探讨了不同的社会网络结构如何影响技术扩散,从而影响一个国家的增长率。高扩散网络与收入之间呈显著正相关。但是,当我们使用一个模型来分离社交网络变化对增长的影响时,这种影响可以是正的、负的,也可以是零。原因是网络传播思想和疾病。低扩散网络在疾病流行的国家得到了发展,因为有限的连通性保护了居民免受流行病的侵害。但是,在低疾病环境中的低扩散网络会损害好思想的传播。一般来说,社交网络已经进化到适应其经济和流行病学环境。试图改变一个国家的网络以模仿高收入国家的网络很可能适得其反。
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