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Effects of social network structure on the diffusion and adoption of agricultural technology: Evidence from rural Ethiopia

Author

Listed:
  • Yasuyuki Todo

    (Faculty of Political Science and Economics, Waseda University)

  • Petr Matous

    (Complex Systems Research Group, School of Engineering, University of Sydney)

  • Dagne Mojo

    (Holetta Agricultural Research Center, Ethiopian Institute of Agricultural Research, Holetta, Ethiopia)

Abstract

This paper investigates the effects of social network structure on the diffusion of agricultural technologies using household-level panel data from Ethiopia. We correct for possible biases due to the endogeneity of social networks using a social experiment in which we provide mobile phones to randomly selected households. We find that the effect of social networks varies depending on the network structure and characteristics of the technologies considered. The diffusion of information on a simple technology is determined by whether farmers know an agricultural extension agent. However, the diffusion of information on a more complex technology is not promoted by simply knowing an extension agent but by knowing an agent that a particular household can rely on and by clustered networks in which most friends of the household are friends of each other. This finding suggests that knowing and understanding more complex technologies require strong external ties and flows of the same information from multiple sources.

Suggested Citation

  • Yasuyuki Todo & Petr Matous & Dagne Mojo, 2015. "Effects of social network structure on the diffusion and adoption of agricultural technology: Evidence from rural Ethiopia," Working Papers 1505, Waseda University, Faculty of Political Science and Economics.
    • Handle: RePEc:wap:wpaper:1505
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    References listed on IDEAS

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    1. Caselli, Francesco, 2005. "Accounting for Cross-Country Income Differences," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 9, pages 679-741, Elsevier.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    4. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    5. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    6. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    7. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    8. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    9. Caselli, Francesco, 2005. "Accounting for cross-country income differences," LSE Research Online Documents on Economics 5266, London School of Economics and Political Science, LSE Library.
    10. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    11. Amrit Tiwana, 2008. "Do bridging ties complement strong ties? An empirical examination of alliance ambidexterity," Strategic Management Journal, Wiley Blackwell, vol. 29(3), pages 251-272, March.
    12. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    13. Caselli, Francesco, 2005. "Accounting for cross-country income differences," LSE Research Online Documents on Economics 3567, London School of Economics and Political Science, LSE Library.
    14. Rost, Katja, 2011. "The strength of strong ties in the creation of innovation," Research Policy, Elsevier, vol. 40(4), pages 588-604, May.
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    Citations

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    Cited by:

    1. Dengke Yu & Rong Zhou, 2017. "Coordination of Cooperative Knowledge Creation for Agricultural Technology Diffusion in China’s “Company Plus Farmers” Organizations," Sustainability, MDPI, vol. 9(10), pages 1-15, October.
    2. Sintayehu Hailu Alemu & Luuk Kempen & Ruerd Ruben, 2018. "The Long Shadow of Faith-based Social Networks on Agricultural Performance: Evidence from Ethiopian Apple Growers," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(2), pages 297-319, April.
    3. Matous, Petr, 2017. "Complementarity and substitution between physical and virtual travel for instrumental information sharing in remote rural regions: A social network approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 61-79.
    4. WALTHER Olivier, 2012. "Regional trade and economic networks in West Africa," LISER Working Paper Series 2012-07, Luxembourg Institute of Socio-Economic Research (LISER).
    5. Mulu Debela Ofolsha & Fekadu Beyene Kenee & Dawit Alemu Bimirew & Tesfaye Lemma Tefera & Aseffa Seyoum Wedajo, 2022. "The Effect of Social Networks on Smallholder Farmers’ Decision to Join Farmer-Base Seed Producer Cooperatives (FBSc): The Case of Hararghe, Oromia, Ethiopia," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    6. Tiéfigué Pierrette Coulibaly & Jianguo Du & Daniel Diakité & Olivier Joseph Abban & Elvis Kouakou, 2021. "A Proposed Conceptual Framework on the Adoption of Sustainable Agricultural Practices: The Role of Network Contact Frequency and Institutional Trust," Sustainability, MDPI, vol. 13(4), pages 1-12, February.
    7. Takahashi, R. & Todo, Y., 2018. "When do consumers stand up for the environment? Evidence from a large-scale social experiment to promote environmentally friendly coffee," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277507, International Association of Agricultural Economists.
    8. Matous, Petr & Todo, Yasuyuki & Mojo, Dagne, 2013. "Boots are made for walking: interactions across physical and social space in infrastructure-poor regions," Journal of Transport Geography, Elsevier, vol. 31(C), pages 226-235.
    9. Petr Matous & Yasuyuki Todo & Ayu Pratiwi, 2015. "The role of motorized transport and mobile phones in the diffusion of agricultural information in Tanggamus Regency, Indonesia," Transportation, Springer, vol. 42(5), pages 771-790, September.

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    More about this item

    Keywords

    knowledge diffusion; technology adoption; agriculture; social network; Ethiopia;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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