[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/deveco/v125y2017icp1-20.html
   My bibliography  Save this article

Seeing is believing? Evidence from an extension network experiment

Author

Listed:
  • Kondylis, Florence
  • Mueller, Valerie
  • Zhu, Jessica
Abstract
Extension is designed to enable lab-to-farm technology diffusion. Decentralized models assume that information flows from researchers to extension workers, and from extension agents to contact farmers (CFs). CFs should then train other farmers in their communities. Such a modality may fail to address informational inefficiencies and accountability issues. We run a field experiment to measure the impact of augmenting the CF model with a direct CF training on the diffusion of a new technology. All villages have CFs and access the same extension network. In treatment villages, CFs additionally receive a three-day, central training on the new technology. We track information transmission through two nodes of the extension network: from extension agents to CFs, and from CFs to other farmers. Directly training CFs leads to a large, statistically significant increase in adoption among CFs. However, higher levels of CF adoption have limited impact on the behavior of other farmers.

Suggested Citation

  • Kondylis, Florence & Mueller, Valerie & Zhu, Jessica, 2017. "Seeing is believing? Evidence from an extension network experiment," Journal of Development Economics, Elsevier, vol. 125(C), pages 1-20.
    • Handle: RePEc:eee:deveco:v:125:y:2017:i:c:p:1-20
    DOI: 10.1016/j.jdeveco.2016.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304387816300827
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jdeveco.2016.10.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    2. Davis, K. & Nkonya, E. & Kato, E. & Mekonnen, D.A. & Odendo, M. & Miiro, R. & Nkuba, J., 2012. "Impact of Farmer Field Schools on Agricultural Productivity and Poverty in East Africa," World Development, Elsevier, vol. 40(2), pages 402-413.
    3. Dercon, Stefan & Christiaensen, Luc, 2011. "Consumption risk, technology adoption and poverty traps: Evidence from Ethiopia," Journal of Development Economics, Elsevier, vol. 96(2), pages 159-173, November.
    4. Feder, Gershon & Savastano, Sara, 2006. "The role of opinion leaders in the diffusion of new knowledge: The case of integrated pest management," World Development, Elsevier, vol. 34(7), pages 1287-1300, July.
    5. Rosenzweig, Mark R & Wolpin, Kenneth I, 1993. "Credit Market Constraints, Consumption Smoothing, and the Accumulation of Durable Production Assets in Low-Income Countries: Investment in Bullocks in India," Journal of Political Economy, University of Chicago Press, vol. 101(2), pages 223-244, April.
    6. Florence Kondylis & Valerie Mueller & S. Zhu, 2015. "Measuring agricultural knowledge and adoption," Agricultural Economics, International Association of Agricultural Economists, vol. 46(3), pages 449-462, May.
    7. 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.
    8. Jock R. Anderson, 2004. "Agricultural Extension: Good Intentions and Hard Realities," The World Bank Research Observer, World Bank, vol. 19(1), pages 41-60.
    9. 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.
    10. Bekele A. Shiferaw & Tewodros A. Kebede & Liang You, 2008. "Technology adoption under seed access constraints and the economic impacts of improved pigeonpea varieties in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 39(3), pages 309-323, November.
    11. Anderson, Jock R. & Feder, Gershon, 2007. "Agricultural Extension," Handbook of Agricultural Economics, in: Robert Evenson & Prabhu Pingali (ed.), Handbook of Agricultural Economics, edition 1, volume 3, chapter 44, pages 2343-2378, Elsevier.
    12. Martina Björkman & Jakob Svensson, 2009. "Power to the People: Evidence from a Randomized Field Experiment on Community-Based Monitoring in Uganda," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(2), pages 735-769.
    13. Rosenzweig, Mark R & Binswanger, Hans P, 1993. "Wealth, Weather Risk and the Composition and Profitability of Agricultural Investments," Economic Journal, Royal Economic Society, vol. 103(416), pages 56-78, January.
    14. 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.
    15. Dean Karlan & Aishwarya Lakshmi Ratan & Jonathan Zinman, 2014. "Savings by and for the Poor: A Research Review and Agenda," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(1), pages 36-78, March.
    16. Thompson, Peter, 2010. "Learning by Doing," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 429-476, Elsevier.
    17. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    18. Sylvie Moulin & Michael Kremer & Paul Glewwe, 2009. "Many Children Left Behind? Textbooks and Test Scores in Kenya," American Economic Journal: Applied Economics, American Economic Association, vol. 1(1), pages 112-135, January.
    19. Bindlish, Vishva & Evenson, Robert E, 1997. "The Impact of T&V Extension in Africa: The Experience of Kenya and Burkina Faso," The World Bank Research Observer, World Bank, vol. 12(2), pages 183-201, August.
    20. Amir K. Abadi Ghadim & David J. Pannell & Michael P. Burton, 2005. "Risk, uncertainty, and learning in adoption of a crop innovation," Agricultural Economics, International Association of Agricultural Economists, vol. 33(1), pages 1-9, July.
    21. Glewwe, Paul & Kremer, Michael & Moulin, Sylvie & Zitzewitz, Eric, 2004. "Retrospective vs. prospective analyses of school inputs: the case of flip charts in Kenya," Journal of Development Economics, Elsevier, vol. 74(1), pages 251-268, June.
    22. Dean Karlan & Aishwarya Lakshmi Ratan & Jonathan Zinman, 2014. "Savings by and for the Poor: A Research Review and Agenda," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(1), pages 36-78, March.
    23. de Brauw, Alan, 2014. "Gender, control, and crop choice in northern Mozambique:," IFPRI discussion papers 1333, International Food Policy Research Institute (IFPRI).
    24. Steven D. Levitt & John A. List & Chad Syverson, 2013. "Toward an Understanding of Learning by Doing: Evidence from an Automobile Assembly Plant," Journal of Political Economy, University of Chicago Press, vol. 121(4), pages 643-681.
    25. Tavneet Suri, 2009. "Selection and Comparative Advantage in Technology Adoption," NBER Working Papers 15346, National Bureau of Economic Research, Inc.
    26. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 1071-1102.
    27. Gemo, H. R., 2013. "Why did Mozambique\u2019s public extension halt the implementation of the National Agrarian Extension Program (PRONEA)?," IWMI Working Papers H046296, International Water Management Institute.
    28. Tan, Jee-Peng & Lane, Julia & Lassibille, Gerard, 1999. "Student Outcomes in Philippine Elementary Schools: An Evaluation of Four Experiments," The World Bank Economic Review, World Bank, vol. 13(3), pages 493-508, September.
    29. Seema Jayachandran, 2006. "Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 538-575, June.
    30. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    31. 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.
    32. BenYishay, Ariel & Mobarak, A. Mushfiq, 2013. "Communicating with Farmers through Social Networks," Working Papers 121, Yale University, Department of Economics.
    33. Magnan, Nicholas & Spielman, David J. & Lybbert, Travis J. & Gulati, Kajal, 2013. "Leveling with Friends: Social Networks and Indian Farmers' Demand for Agricultural Custom Hire Services," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150711, Agricultural and Applied Economics Association.
    34. Heidi Hogset & Christopher B. Barrett, 2010. "Social Learning, Social Influence, and Projection Bias: A Caution on Inferences Based on Proxy Reporting of Peer Behavior," Economic Development and Cultural Change, University of Chicago Press, vol. 58(3), pages 563-589, April.
    35. McKenzie, David, 2012. "Beyond baseline and follow-up: The case for more T in experiments," Journal of Development Economics, Elsevier, vol. 99(2), pages 210-221.
    36. Benedito Cunguara & Karl Moder, 2011. "Is Agricultural Extension Helping the Poor? Evidence from Rural Mozambique," Journal of African Economies, Centre for the Study of African Economies, vol. 20(4), pages 562-595, August.
    37. Douglas Gollin & Michael Morris & Derek Byerlee, 2005. "Technology Adoption in Intensive Post-Green Revolution Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(5), pages 1310-1316.
    38. Steven Levitt & John List & Chad Syverson, 2012. "Toward an Understanding of Learning by Doing: Evidence from an Automobile Plant," Natural Field Experiments 00463, The Field Experiments Website.
    39. Robert Evenson & Prabhu Pingali (ed.), 2007. "Handbook of Agricultural Economics," Handbook of Agricultural Economics, Elsevier, edition 1, volume 3, number 1.
    40. Pamuk, Haki & Bulte, Erwin & Adekunle, Adewale A., 2014. "Do decentralized innovation systems promote agricultural technology adoption? Experimental evidence from Africa," Food Policy, Elsevier, vol. 44(C), pages 227-236.
    41. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kondylis, Florence & Mueller, Valerie, 2012. "Seeing is Believing? Evidence from a Demonstration Plot Experiment in Mozambique:," MSSP working papers 1, International Food Policy Research Institute (IFPRI).
    2. B Kelsey Jack, "undated". "Market Inefficiencies and the Adoption of Agricultural Technologies in Developing Countries," CID Working Papers 50, Center for International Development at Harvard University.
    3. Khushbu Mishra & Abdoul G. Sam & Gracious M. Diiro & Mario J. Miranda, 2020. "Gender and the dynamics of technology adoption: Empirical evidence from a household‐level panel data," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 857-870, November.
    4. 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.
    5. Anna Folke Larsen, 2015. "The network at work: Diffusion of banana cultivation in Tanzania," CAM Working Papers camwp2015_01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    6. Songsermsawas, Tisorn & Baylis, Kathy & Chhatre, Ashwini & Michelson, Hope, 2016. "Can Peers Improve Agricultural Revenue?," World Development, Elsevier, vol. 83(C), pages 163-178.
    7. Esther Gehrke, 2019. "An Employment Guarantee as Risk Insurance? Assessing the Effects of the NREGS on Agricultural Production Decisions," The World Bank Economic Review, World Bank, vol. 33(2), pages 413-435.
    8. Arslan, Cansın & Wollni, Meike & Oduol, Judith & Hughes, Karl, 2022. "Who communicates the information matters for technology adoption," World Development, Elsevier, vol. 158(C).
    9. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    10. Kazushi Takahashi & Yukichi Mano & Keijiro Otsuka, 2018. "Spillovers as a Driver to Reduce Ex-post Inequality Generated by Randomized Experiments: Evidence from an Agricultural Training Intervention," Working Papers 174, JICA Research Institute.
    11. Anna Folke Larsen, 2019. "When knowledgeable neighbors also share seedlings: diffusion of banana cultivation in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 50(1), pages 51-65, January.
    12. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2018. "Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania," World Development, Elsevier, vol. 105(C), pages 336-351.
    13. Shamdasani, Yogita, 2021. "Rural road infrastructure & agricultural production: Evidence from India," Journal of Development Economics, Elsevier, vol. 152(C).
    14. Kondylis, Florence & Mueller, Valerie & Sheriff, Glenn & Zhu, Siyao, 2016. "Do Female Instructors Reduce Gender Bias in Diffusion of Sustainable Land Management Techniques? Experimental Evidence From Mozambique," World Development, Elsevier, vol. 78(C), pages 436-449.
    15. Mekonnen, Daniel Ayalew & Gerber, Nicolas & Matz, Julia Anna, 2018. "Gendered Social Networks, Agricultural Innovations, and Farm Productivity in Ethiopia," World Development, Elsevier, vol. 105(C), pages 321-335.
    16. Terrance Hurley & Jawoo Koo & Kindie Tesfaye, 2018. "Weather risk: how does it change the yield benefits of nitrogen fertilizer and improved maize varieties in sub‐Saharan Africa?," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 711-723, November.
    17. Magnan, Nicholas & Spielman, David J. & Lybbert, Travis J. & Gulati, Kajal, 2015. "Leveling with friends: Social networks and Indian farmers' demand for a technology with heterogeneous benefits," Journal of Development Economics, Elsevier, vol. 116(C), pages 223-251.
    18. 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.
    19. Bonan, Jacopo & Battiston, Pietro & Bleck, Jaimie & LeMay-Boucher, Philippe & Pareglio, Stefano & Sarr, Bassirou & Tavoni, Massimo, 2021. "Social interaction and technology adoption: Experimental evidence from improved cookstoves in Mali," World Development, Elsevier, vol. 144(C).
    20. Michelson, Hope & Fairbairn, Anna & Ellison, Brenna & Maertens, Annemie & Manyong, Victor, 2021. "Misperceived quality: Fertilizer in Tanzania," Journal of Development Economics, Elsevier, vol. 148(C).

    More about this item

    Keywords

    Information failure; Technology diffusion; Agriculture; Africa;
    All these keywords.

    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:deveco:v:125:y:2017:i:c:p:1-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/devec .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.