  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.
