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Leveling with friends: Social networks and indian farmers’ demand for agricultural custom hire services:

  • Magnan, Nicholas
  • Spielman, David J.
  • Lybbert, Travis J.
  • Gulati, Kajal

This research was undertaken to understand how information about a new agricultural technology is transmitted through social networks, and what effect information gained through social networks has on technology demand at the household level. The technology in question is laser land leveling (LLL)-a resource-conserving technology-which we introduced in eastern Uttar Pradesh, India as part of the study. Using an experimental auction, we obtain farmers’ willingness-to-pay for the technology and identify potential adopters. We then randomly select half of these farmers to actually receive LLL services on their land, creating random variation in the number of adopters in each farmer’s social network. We conduct a second auction one year later with the same sample of farmers and estimate network effects on farmers’ updated willingness-to-pay. Four main results emerge: First, exposure to LLL through networks occurs primarily through visits to adopting farmers’ fields. Second, having a first-generation adopter in a farmer’s network increases the farmer’s valuation of LLL by nearly 30 percent on average. Third, the network effects on demand are importantly conditioned on benefits associated with LLL, which implies that learning-rather than mimicry-is driving increases in demand. Fourth, network effects are strongest between poor farmers.

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Paper provided by International Food Policy Research Institute (IFPRI) in its series IFPRI discussion papers with number 1302.

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Date of creation: 2013
Date of revision:
Handle: RePEc:fpr:ifprid:1302
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  1. Emmanuel Saez & Esther Duflo, 2003. "The role of information and social interactions in retirement plan decisions: Evidence from a randomized experiment," Framed Field Experiments 00141, The Field Experiments Website.
  2. Timothy G. Conley & Christopher R. Udry, 2000. "Learning About a New Technology: Pineapple in Ghana," Working Papers 817, Economic Growth Center, Yale University, revised May 2004.
  3. Birner, Regina & Davis, Kristin & Pender, John & Nkonya, Ephraim & Anandajayasekeram, Pooniah & Ekboir, Javier M. & Mbabu, Adiel N. & Spielman, David J. & Horna, Daniela & Benin, Samuel & Kisamba-Muge, 2006. "From "best practice" to "best fit": a framework for designing and analyzing pluralistic agricultural advisory services," Research briefs 4, International Food Policy Research Institute (IFPRI).
  4. 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.
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  8. Mark Rosenzweig & Andrew D. Foster, . "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Home Pages _068, University of Pennsylvania.
  9. Sabina Alkire and Maria Emma Santos, 2010. "Acute Multidimensional Poverty: A New Index for Developing Countries," OPHI Working Papers ophiwp038, Queen Elizabeth House, University of Oxford.
  10. Kathryn Vasilaky, 2013. "Female Social Networks and Farmer Training: Can Randomized Information Exchange Improve Outcomes?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 376-383.
  11. Emily Oster & Rebecca Thornton, 2012. "Determinants Of Technology Adoption: Peer Effects In Menstrual Cup Take-Up," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1263-1293, December.
  12. Annemie Maertens & Christopher B. Barrett, 2013. "Measuring Social Networks' Effects on Agricultural Technology Adoption," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 353-359.
  13. Lybbert, Travis J. & Magnan, Nicholas & Spielman, David J. & Bhargava, Anil K. & Gulati, Kajal, 2013. "Targeting technology to reduce poverty and conserve resources: Experimental delivery of laser land leveling to farmers in Uttar Pradesh, India:," IFPRI discussion papers 1274, International Food Policy Research Institute (IFPRI).
  14. Timothy Besley & Anne Case, 1994. "Diffusion as a Learning Process: Evidence from HYV Cotton," Working Papers 228, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
  15. Santos, Paulo & Barrett, Christopher B., 2010. "Identity, Interest and Information Search in a Dynamic Rural Economy," World Development, Elsevier, vol. 38(12), pages 1788-1796, December.
  16. repec:att:wimass:9127 is not listed on IDEAS
  17. Esther Duflo & Emmanuel Saez, 2002. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," NBER Working Papers 8885, National Bureau of Economic Research, Inc.
  18. Philip S. Babcock & John L. Hartman, 2010. "Networks and Workouts: Treatment Size and Status Specific Peer Effects in a Randomized Field Experiment," NBER Working Papers 16581, National Bureau of Economic Research, Inc.
  19. Manski, Charles F, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Wiley Blackwell, vol. 60(3), pages 531-42, July.
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