[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/cdl/agrebk/qt8qx7m4zq.html
   My bibliography  Save this paper

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

Author

Listed:
  • Dar, Manzoor H.
  • de Janvry, Alain
  • Emerick, Kyle
  • Kelley, Erin M.
  • 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

  • Dar, Manzoor H. & de Janvry, Alain & Emerick, Kyle & Kelley, Erin M. & Sadoulet, Elisabeth, 2019. "Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt8qx7m4zq, Department of Agricultural & Resource Economics, UC Berkeley.
    • Handle: RePEc:cdl:agrebk:qt8qx7m4zq
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/8qx7m4zq.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    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. Abhijit Banerjee & Emily Brez & Arun G Chandrasekhar & Benjamin Golub, 2024. "When Less Is More: Experimental Evidence on Information Delivery During India’s Demonetisation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(4), pages 1884-1922.
    3. Dean Karlan & Robert Osei & Isaac Osei-Akoto & Christopher Udry, 2014. "Agricultural Decisions after Relaxing Credit and Risk Constraints," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(2), pages 597-652.
    4. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    5. Shawn Cole & Xavier Giné & James Vickery, 2017. "How Does Risk Management Influence Production Decisions? Evidence from a Field Experiment," The Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 1935-1970.
    6. Birkhaeuser, Dean & Evenson, Robert E & Feder, Gershon, 1991. "The Economic Impact of Agricultural Extension: A Review," Economic Development and Cultural Change, University of Chicago Press, vol. 39(3), pages 607-650, April.
    7. 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.
    8. 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.
    9. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017. "Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Papers 1712.04802, arXiv.org, revised Oct 2023.
    10. , & , & ,, 2014. "Dynamics of information exchange in endogenous social networks," Theoretical Economics, Econometric Society, vol. 9(1), January.
    11. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    12. 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.
    13. Bruce Sacerdote, 2001. "Peer Effects with Random Assignment: Results for Dartmouth Roommates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 681-704.
    14. 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.
    15. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2018. "Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," NBER Working Papers 24678, National Bureau of Economic Research, Inc.
    16. Leonardo Bursztyn & Florian Ederer & Bruno Ferman & Noam Yuchtman, 2014. "Understanding Mechanisms Underlying Peer Effects: Evidence From a Field Experiment on Financial Decisions," Econometrica, Econometric Society, vol. 82(4), pages 1273-1301, July.
    17. Calvó-Armengol, Antoni & , & ,, 2015. "Communication and influence," Theoretical Economics, Econometric Society, vol. 10(2), May.
    18. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    19. 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.
    20. Szeidl, Adam & Mobius, Markus & Phan, Tuan, 2015. "Treasure Hunt: Social Learning in the Field," CEPR Discussion Papers 10493, C.E.P.R. Discussion Papers.
    21. Jing Cai & Alain De Janvry & Elisabeth Sadoulet, 2015. "Social Networks and the Decision to Insure," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 81-108, April.
    22. Rema Hanna & Sendhil Mullainathan & Joshua Schwartzstein, 2014. "Learning Through Noticing: Theory and Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1311-1353.
    23. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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).
    3. 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.
    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. 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).
    6. Alain de Janvry & Elisabeth Sadoulet, 2019. "Transforming developing country agriculture: Removing adoption constraints and promoting inclusive value chain development," Working Papers hal-02287668, HAL.
    7. Nirmala Bandumula & Santosha Rathod & Gabrijel Ondrasek & Muthuraman Pitchiah Pillai & Raman Meenakshi Sundaram, 2022. "An Economic Evaluation of Improved Rice Production Technology in Telangana State, India," Agriculture, MDPI, vol. 12(9), pages 1-12, September.
    8. de Janvry, Alain & Sadoulet, Elisabeth, 2020. "How experimental research in agriculture has gone from lab to field," World Development, Elsevier, vol. 127(C).
    9. 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).

    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. 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).
    2. 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).
    3. Ram Fishman & Stephen C. Smith & Vida Bobic & Munshi Sulaiman, 2022. "Can Agricultural Extension and Input Support Be Discontinued? Evidence from a Randomized Phaseout in Uganda," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1273-1288, November.
    4. Shikuku, K.M., 2018. "Information exchange links, knowledge exposure, and adoption of agricultural technologies in Northern Uganda," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275974, International Association of Agricultural Economists.
    5. Annemie Maertens & Hope Michelson & Vesall Nourani, 2021. "How Do Farmers Learn from Extension Services? Evidence from Malawi," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 569-595, March.
    6. Elisabeth SADOULET, 2016. "Review of Theories of Learning for Adopting," Working Papers P163, FERDI.
    7. Arslan, Cansın & Wollni, Meike & Oduol, Judith & Hughes, Karl, 2022. "Who communicates the information matters for technology adoption," World Development, Elsevier, vol. 158(C).
    8. 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.
    9. 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.
    10. Ayalew, Hailemariam & Chamberlin, Jordan & Newman, Carol, 2022. "Site-specific agronomic information and technology adoption: A field experiment from Ethiopia," Journal of Development Economics, Elsevier, vol. 156(C).
    11. David Atkin & Azam Chaudhry & Shamyla Chaudry & Amit K. Khandelwal & Eric Verhoogen, 2017. "Organizational Barriers to Technology Adoption: Evidence from Soccer-Ball Producers in Pakistan," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1101-1164.
    12. 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).
    13. Niu, Chiyu & Ragasa, Catherine, 2018. "Selective attention and information loss in the lab-to-farm knowledge chain: The case of Malawian agricultural extension programs," Agricultural Systems, Elsevier, vol. 165(C), pages 147-163.
    14. Dominik Naeher, 2022. "Technology Adoption Under Costly Information Processing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(2), pages 699-753, May.
    15. Shamdasani, Yogita, 2021. "Rural road infrastructure & agricultural production: Evidence from India," Journal of Development Economics, Elsevier, vol. 152(C).
    16. Heitzig, Chris & O’Keeffe-O’Donovan, Rossa, 2024. "Spillover Effects and Diffusion of Savings Groups," World Development, Elsevier, vol. 173(C).
    17. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    18. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Working Papers hal-03459820, HAL.
    19. repec:spo:wpmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    20. Francesco Drago & Friederike Mengel & Christian Traxler, 2020. "Compliance Behavior in Networks: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 96-133, April.
    21. 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).

    More about this item

    Keywords

    Social and Behavioral Sciences;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cdl:agrebk:qt8qx7m4zq. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/dabrkus.html .

    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.