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Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption

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  • Emerick, Kyle
  • Kelley, Erin
  • De Janvry, Alain
  • Sadoulet, Elisabeth

Abstract

Can agents in a social network be induced to obtain information from outside their peer groups? Using a field experiment in rural Bangladesh, we show that demonstration plots in agriculture - a technique where the first users of a new variety cultivate it in a side-by-side comparison with an existing variety - facilitate social learning by inducing conversations and information sharing outside of existing social networks. We compare these improvements in learning with those from seeding new technology with more central farmers in village social networks. The demonstration plots - when cultivated by randomly selected farmers - improve knowledge by just as much as seeding with more central farmers. Moreover, the demonstration plots only induce conversations and facilitate learning for farmers that were unconnected to entry points at baseline. Finally, we combine this diffusion experiment with an impact experiment to show that both demonstration plots and improved seeding transmit information to farmers that are less likely to benefit from the new innovation.

Suggested Citation

  • Emerick, Kyle & Kelley, Erin & De Janvry, Alain & Sadoulet, Elisabeth, 2019. "Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption," CEPR Discussion Papers 13507, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:13507
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    Cited by:

    1. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    2. Chowdhury, Shyamal & Satish, Varun & Sulaiman, Munshi & Sun, Yi, 2022. "Sooner rather than later: Social networks and technology adoption," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 466-482.
    3. Alain de Janvry & Elisabeth Sadoulet, 2019. "Transforming developing country agriculture: Removing adoption constraints and promoting inclusive value chain development," Working Papers hal-02287668, HAL.
    4. Kijima, Yoko, 2020. "Japanese Agricultural ODA and Its Economic Impacts: Technological Assistance for the Rice Green Revolution in Sub-Saharan Africa," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 22.
    5. Islam, Asadul & Ushchev, Philip & Zenou, Yves & Zhang, Xin, 2019. "The Value of Information in Technology Adoption," IZA Discussion Papers 12672, Institute of Labor Economics (IZA).
    6. repec:cdl:agrebk:qt2xb9r9pf is not listed on IDEAS
    7. Shikuku, Kelvin Mashisia & Tran, Nhuong & Joffre, Olivier M. & Islam, Abu Hayat Md Saiful & Barman, Benoy Kumar & Ali, Shawquat & Rossignoli, Cristiano M., 2021. "Lock-ins to the dissemination of genetically improved fish seeds," Agricultural Systems, Elsevier, vol. 188(C).
    8. Chowdhury, Shyamal & Satish, Varun & Sulaiman, Munshi & Sun, Yi, 2021. "Sooner Rather Than Later: Social Networks and Technology Adoption," IZA Discussion Papers 14307, Institute of Labor Economics (IZA).
    9. de Janvry, Alain & Sadoulet, Elisabeth, 2020. "How experimental research in agriculture has gone from lab to field," World Development, Elsevier, vol. 127(C).

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