标题： 看到树木看到森林？ 网络知识的调查 显示英文标题

标题： Seeing the forest for the trees? An investigation of network knowledge

摘要： 本文评估了网络经济学文献中最普遍的假设之一的实证内容，即决策者对其所参与的网络有完全了解的假设。 使用来自75个村庄的网络数据，我们询问了4,554名个体，让他们评估其村庄中五个随机选择的家庭对是否通过金融、社会和信息关系相连。 我们发现网络知识较低且高度局部化，随着配对与受访者之间的网络距离增加而急剧下降。 46%的受访者甚至无法对给定的一对个体之间潜在联系的状态做出猜测。 即使愿意做出猜测，受访者也只能在37%的情况下正确识别这些联系。 我们还发现，与配对的社会距离增加一步会导致误判联系的概率增加10个百分点。 随后，我们通过展示如果代理人在更现实的不完全网络知识假设下行为，各种模型的预测会发生显著变化，来探讨该假设的理论影响。 综上所述，我们的结果表明，完全网络知识的假设（i）可能是对现实世界的不良近似，（ii）并非无害：允许不完全网络知识可能对各种情境下的定性和定量结果产生一阶影响。 显示英文摘要

摘要： This paper assesses the empirical content of one of the most prevalent assumptions in the economics of networks literature, namely the assumption that decision makers have full knowledge about the networks they interact on. Using network data from 75 villages, we ask 4,554 individuals to assess whether five randomly chosen pairs of households in their village are linked through financial, social, and informational relationships. We find that network knowledge is low and highly localized, declining steeply with the pair's network distance to the respondent. 46% of respondents are not even able to offer a guess about the status of a potential link between a given pair of individuals. Even when willing to offer a guess, respondents can only correctly identify the links 37% of the time. We also find that a one-step increase in the social distance to the pair corresponds to a 10pp increase in the probability of misidentifying the link. We then investigate the theoretical implications of this assumption by showing that the predictions of various models change substantially if agents behave under the more realistic assumption of incomplete knowledge about the network. Taken together, our results suggest that the assumption of full network knowledge (i) may serve as a poor approximation to the real world and (ii) is not innocuous: allowing for incomplete network knowledge may have first-order implications for a range of qualitative and quantitative results in various contexts.