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Lost in Transmission

Thomas Graeber (), Shakked Noy () and Christopher Roth
Additional contact information
Thomas Graeber: Harvard Business School
Shakked Noy: Massachusetts Institute of Technology

No 272, ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany

Abstract: For many decisions, people rely on information received from others by word of mouth. How does the process of verbal transmission distort economic information? In our experiments, participants listen to audio recordings containing economic forecasts and are paid to accurately transmit the information via voice messages. Other participants listen either to an original recording or a transmitted version and then state incentivized beliefs. Our main finding is that, across a variety of transmitter incentive schemes, information about the reliability of a forecast is lost in transmission more than twice as much as information about theforecast’s level. This differential information loss predictably distorts listeners’ belief updates: following transmission, reliable and unreliable messages converge in influence and average belief updates from new information are weakened. Mechanism experiments show that the differential loss is not driven by transmitters deliberately trading off the costs and benefits of transmitting different kinds of information. Instead, it results from memory constraints during transmission, which can be overcome through targeted reminders.

Keywords: Information Transmission; Word-of-mouth; Narratives; Reliability (search for similar items in EconPapers)
Pages: 87 pages
Date: 2024-01
New Economics Papers: this item is included in nep-cbe and nep-exp
References: View references in EconPapers View complete reference list from CitEc
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https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_272_2024.pdf Second version, 2024 (application/pdf)

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Working Paper: Lost in Transmission (2024) Downloads
Working Paper: Lost in Transmission (2024) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:ajk:ajkdps:272

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