Seeing the Forest for the Trees? An Investigation of Network Knowledge

36 Pages Posted: 28 Feb 2018 Last revised: 22 Jan 2023

See all articles by Emily Breza

Emily Breza

Harvard University

Arun G. Chandrasekhar

Stanford University - Department of Economics

Alireza Tahbaz-Salehi

Northwestern University - Kellogg School of Management; Centre for Economic Policy Research (CEPR)

Date Written: February 2018

Abstract

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.

Suggested Citation

Breza, Emily and Chandrasekhar, Arun G. and Tahbaz-Salehi, Alireza, Seeing the Forest for the Trees? An Investigation of Network Knowledge (February 2018). NBER Working Paper No. w24359, Available at SSRN: https://ssrn.com/abstract=3131138

Emily Breza (Contact Author)

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Arun G. Chandrasekhar

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

Alireza Tahbaz-Salehi

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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