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.

中文翻译：

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细菌，社交网络和成长

个人之间的社会联系方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？其影响有多大？使用网络分析工具，我们探索了不同的社交网络结构如何影响技术扩散，进而影响一个国家的增长率。高扩散网络与收入之间的相关性很强。但是，当我们使用模型来隔离社交网络变化对增长的影响时，该影响可以是正的，负的或零。原因是网络传播思想和疾病。低传播网络在疾病盛行的国家得到了发展，因为有限的连通性可以保护居民免受流行病的侵袭。但是，在低疾病环境中的低扩散网络会损害好想法的传播。一般来说，社会网络已经发展到适合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可能会适得其反。