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

Author

Listed:
  • Emily Breza
  • Arun G. Chandrasekhar
  • Alireza Tahbaz-Salehi

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

  • Emily Breza & Arun G. Chandrasekhar & Alireza Tahbaz-Salehi, 2018. "Seeing the Forest for the Trees? An Investigation of Network Knowledge," NBER Working Papers 24359, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24359
    Note: DEV IO LS POL TWP
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    Cited by:

    1. Lori Beaman & Niall Keleher & Jeremy Magruder & Carly Trachtman, 2021. "Urban Networks and Targeting: Evidence from Liberia," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 572-576, May.
    2. Mira Frick & Ryota Iijima & Yuhta Ishii, 2018. "Dispersed Behavior and Perceptions in Assortative Societies," Cowles Foundation Discussion Papers 2128R2, Cowles Foundation for Research in Economics, Yale University, revised Oct 2021.
    3. Nathan Canen & Jacob Schwartz & Kyungchul Song, 2020. "Estimating local interactions among many agents who observe their neighbors," Quantitative Economics, Econometric Society, vol. 11(3), pages 917-956, July.
    4. Crès, Hervé & Tvede, Mich, 2022. "Aggregation of opinions in networks of individuals and collectives," Journal of Economic Theory, Elsevier, vol. 199(C).
    5. Battigalli, Pierpaolo & Panebianco, Fabrizio & Pin, Paolo, 2023. "Learning and selfconfirming equilibria in network games," Journal of Economic Theory, Elsevier, vol. 212(C).
    6. Edoardo Gallo & Joseph Lee & Yohanes Eko Riyanto & Erwin Wong, 2023. "Cooperation and Cognition in Social Networks," Papers 2305.01209, arXiv.org.
    7. Simone Cerreia-Vioglio & Roberto Corrao & Giacomo Lanzani, 2020. "Robust Opinion Aggregation and its Dynamics," Working Papers 662, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Zenou, Yves & Bochet, Olivier & Faure, Mathieu & Long, Yan, 2020. "Perceived Competition in Networks," CEPR Discussion Papers 15582, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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