IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/341088.html

Does the usage of online agricultural information reduce agrochemical expenses in China?

Author

Listed:
  • Hu, Junzhe
  • Kuhn, Lena
  • Bobojonov, Ihtiyor
  • Babadjanova, Mashkhura
  • Sun, Zhanli

Abstract

Motivated by growing concerns about excessive agrochemical use and the resulting environmental pollution in China, this study explores the importance of online agricultural information for chemical fertilizer and pesticide use decisions among grain farmers. In particular, we focus on the functional agricultural information used for productive purposes for smallholders. Based on a survey dataset of 1,833 family farms across five Chinese provinces, we employ a propensity score matching (PSM) approach to estimate treatment effects of online agricultural information. The results reveal that online acquisition of agricultural information does not reduce the expenses of chemical fertilizers and pesticides in our sample; rather, the opposite is true. The use of online agricultural information significantly increased agrochemical expenses, particularly among smallholders. Within our sample region, the limited evolution of online information content and the inherent challenges faced by smallholder farmers are the major barriers to the beneficial effects of online agricultural information in reducing agrochemical use. Our findings emphasize the need for targeted interventions and educational efforts to bridge the knowledge gaps of smallholders. Furthermore, there is a need to raise awareness among information providers to ensure that their recommendations avoid encouraging overdoses of agrochemicals. In addition, enhancing farmers’ digital literacy will be a future task of development policy.

Suggested Citation

  • Hu, Junzhe & Kuhn, Lena & Bobojonov, Ihtiyor & Babadjanova, Mashkhura & Sun, Zhanli, 2026. "Does the usage of online agricultural information reduce agrochemical expenses in China?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 25(6), pages 2255-2267.
  • Handle: RePEc:zbw:espost:341088
    DOI: 10.1016/j.jia.2026.04.019
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/341088/1/Hu_2026_agrochemical_expenses_China.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.jia.2026.04.019?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
    ---><---

    References listed on IDEAS

    as
    1. Jenny C. Aker, 2011. "Dial “A” for Agriculture: A Review of Information and Communication Technologies for Agricultural Extension in Developing Countries - Working Paper 269," Working Papers 269, Center for Global Development.
    2. Li, Xianmei & Yu, Guoxin & Wen, Liping & Liu, Guoyong, 2023. "Research on the effect of agricultural science and technology service supply from the perspective of farmers' differentiation," Innovation and Green Development, Elsevier, vol. 2(3).
    3. Xiaoxiao Li & Laping Wu & Han Gao & Nanyan Hu, 2024. "Can digital literacy improve organic fertilizer utilization rates?: Empirical evidence from China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(12), pages 31921-31946, December.
    4. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    5. Heidi Kaila & Finn Tarp, 2019. "Can the Internet improve agricultural production? Evidence from Viet Nam," Agricultural Economics, International Association of Agricultural Economists, vol. 50(6), pages 675-691, November.
    6. Wanglin Ma & Hongyun Zheng, 2022. "Heterogeneous impacts of information technology adoption on pesticide and fertiliser expenditures: Evidence from wheat farmers in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(1), pages 72-92, January.
    7. Yazhen Gong & Kathy Baylis & Robert Kozak & Gary Bull, 2016. "Farmers’ risk preferences and pesticide use decisions: evidence from field experiments in China," Agricultural Economics, International Association of Agricultural Economists, vol. 47(4), pages 411-421, July.
    8. Ullah, Ayat & Arshad, Muhammad & Kächele, Harald & Khan, Ayesha & Mahmood, Nasir & Müller, Klaus, 2020. "Information asymmetry, input markets, adoption of innovations and agricultural land use in Khyber Pakhtunkhwa, Pakistan," Land Use Policy, Elsevier, vol. 90(C).
    9. Wilson, Clevo & Tisdell, Clem, 2001. "Why farmers continue to use pesticides despite environmental, health and sustainability costs," Ecological Economics, Elsevier, vol. 39(3), pages 449-462, December.
    10. Emileva, Begaiym & Kuhn, Lena & Bobojonov, Ihtiyor & Glauben, Thomas, 2023. "The role of smartphone-based weather information acquisition on climate change perception accuracy: Cross-country evidence from Kyrgyzstan, Mongolia and Uzbekistan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 41, pages 1-1.
    11. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    12. Ogutu, Sylvester Ochieng & Okello, Julius Juma & Otieno, David Jakinda, 2014. "Impact of Information and Communication Technology-Based Market Information Services on Smallholder Farm Input Use and Productivity: The Case of Kenya," World Development, Elsevier, vol. 64(C), pages 311-321.
    13. Uwe Deichmann & Aparajita Goyal & Deepak Mishra, 2016. "Will digital technologies transform agriculture in developing countries?," Agricultural Economics, International Association of Agricultural Economists, vol. 47(S1), pages 21-33, November.
    14. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    15. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    16. Jenny C. Aker, 2011. "Dial “A” for agriculture: a review of information and communication technologies for agricultural extension in developing countries," Agricultural Economics, International Association of Agricultural Economists, vol. 42(6), pages 631-647, November.
    17. Liu, Elaine M. & Huang, JiKun, 2013. "Risk preferences and pesticide use by cotton farmers in China," Journal of Development Economics, Elsevier, vol. 103(C), pages 202-215.
    18. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    19. Xiaolan Fu & Shaheen Akter, 2016. "The Impact of Mobile Phone Technology on Agricultural Extension Services Delivery: Evidence from India," Journal of Development Studies, Taylor & Francis Journals, vol. 52(11), pages 1561-1576, November.
    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. Emileva, Begaiym & Kuhn, Lena & Bobojonov, Ihtiyor & Glauben, Thomas, 2023. "The role of smartphone-based weather information acquisition on climate change perception accuracy: Cross-country evidence from Kyrgyzstan, Mongolia and Uzbekistan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 41, pages 1-1.
    2. Jianxin Guo & Songqing Jin & Lei Chen & Jichun Zhao, 2018. "Impacts of Distance Education on Agricultural Performance and Household Income: Micro-Evidence from Peri-Urban Districts in Beijing," Sustainability, MDPI, vol. 10(11), pages 1-19, October.
    3. Nawab Khan & Ram L. Ray & Hazem S. Kassem & Farhat Ullah Khan & Muhammad Ihtisham & Shemei Zhang, 2022. "Does the Adoption of Mobile Internet Technology Promote Wheat Productivity? Evidence from Rural Farmers," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    4. Duong, Pham Bao & Thanh, Pham Tien, 2019. "Adoption and effects of modern rice varieties in Vietnam: Micro-econometric analysis of household surveys," Economic Analysis and Policy, Elsevier, vol. 64(C), pages 282-292.
    5. Ali, Akhter & Hussain, Imtiaz & Rahut, Dil Bahadur & Erenstein, Olaf, 2018. "Laser-land leveling adoption and its impact on water use, crop yields and household income: Empirical evidence from the rice-wheat system of Pakistan Punjab," Food Policy, Elsevier, vol. 77(C), pages 19-32.
    6. Zhu, Xiaoke & Hu, Ruifa & Zhang, Chao & Shi, Guanming, 2021. "Does Internet use improve technical efficiency? Evidence from apple production in China," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    7. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    8. Wantchekon, Leonard & Riaz, Zara, 2019. "Mobile technology and food access," World Development, Elsevier, vol. 117(C), pages 344-356.
    9. Ashok K. Mishra & Anjani Kumar & Pramod K. Joshi & Alwin D'Souza, 2018. "Cooperatives, contract farming, and farm size: The case of tomato producers in Nepal," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 865-886, October.
    10. Anupam Nanda, 2005. "Property Condition Disclosure Law: Does 'Seller Tell All' Matter in Property Values?," Working papers 2005-47, University of Connecticut, Department of Economics, revised Jul 2006.
    11. Aradom Gebrekidan Abbay & Roel Rutten, 2016. "Does spatial proximity to small towns matter for rural livelihoods? A propensity score matching analysis in Ethiopia," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 287-307, October.
    12. Eliasson, Kent, 2006. "How Robust is the Evidence on the Returns to College Choice? Results Using Swedish Administrative Data," Umeå Economic Studies 692, Umeå University, Department of Economics.
    13. Melia, Elvis, 2019. "The impact of information and communication technologies on jobs in Africa: a literature review," IDOS Discussion Papers 3/2019, German Institute of Development and Sustainability (IDOS).
    14. Patrick Christian Feihle & Jochen Lawrenz, 2017. "The Issuance of German SME Bonds and its Impact on Operating Performance," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 18(3), pages 227-259, August.
    15. Coulibaly, Yacouba & Diallo, Askandarou Cheik, 2025. "Can fiscal rules improve banking system stability in developing countries?," Journal of Macroeconomics, Elsevier, vol. 86(C).
    16. Ignacio Lozano-Espitia & Lina Ma. Ramírez-Villegas, 2016. "How Productive is Rural Infrastructure? Evidence on Some Agricultural Crops in Colombia," Borradores de Economia 948, Banco de la Republica de Colombia.
    17. Honghao Ren & Henk Folmer & Arno J. Van der Vlist, 2018. "The Impact of Home Ownership on Life Satisfaction in Urban China: A Propensity Score Matching Analysis," Journal of Happiness Studies, Springer, vol. 19(2), pages 397-422, February.
    18. Stefan Denzler & Jens Ruhose & Stefan C. Wolter, 2022. ""The Double Dividend of Training" - Labor Market Effects of Work-Related Continuous Education in Switzerland," CESifo Working Paper Series 10009, CESifo.
    19. Cansino, José M. & Lopez-Melendo, Jaime & Pablo-Romero, María del P. & Sánchez-Braza, Antonio, 2013. "An economic evaluation of public programs for internationalization: The case of the Diagnostic program in Spain," Evaluation and Program Planning, Elsevier, vol. 41(C), pages 38-46.
    20. Min, Shi & Liu, Min & Huang, Jikun, 2020. "Does the application of ICTs facilitate rural economic transformation in China? Empirical evidence from the use of smartphones among farmers," Journal of Asian Economics, Elsevier, vol. 70(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:zbw:espost:341088. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.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.