IDEAS home Printed from https://ideas.repec.org/a/caa/jnlage/v70y2024i4id335-2023-agricecon.html
   My bibliography  Save this article

Unravelling the bidirectional impact of Chinese agricultural subsidy policy on agricultural efficiency and farmers' income through panel data analysis

Author

Listed:
  • Yungang Tang

    (Guangdong Provincial Key Laboratory of Public Finance and Taxation with Big Data Application, Guangdong University of Finance and Economic, Guangdong Guangzhou, P. R. China)

  • Haojie Liao

    (School of Accounting and Auditing, Guangxi University of Finance and Economics, Nanning, P. R. China)

  • Ye Wu

    (Guangdong Provincial Key Laboratory of Public Finance and Taxation with Big Data Application, Guangdong University of Finance and Economic, Guangdong Guangzhou, P. R. China)

  • Gang Lei

    (School of Management, Guangdong University of Science and Technology, Guangdong Dongguan, P. R. China)

Abstract

This study examined the bidirectional impact of Chinese agricultural subsidy policies on agricultural efficiency and farmers' income. It employed panel data from 2004 to 2020 across 31 Chinese provinces, and the three-stage least squares method was used for simultaneous estimation. Different regions and farmer types were analysed separately. The findings revealed a significant bidirectional impact of the agricultural subsidy policy on agricultural efficiency and farmers' income, signifying a strong positive feedback loop. Varied types and levels of subsidy policies differently impacted regions and farmer categories, showcasing diverse outcomes and adaptive responses to subsidy policies. The ratio of total subsidy to GDP (SUBGDP) positively impacted production efficiency and per capita disposable income. This result suggests that the subsidy policy helped enhance agricultural production efficiency and increased farmers' income levels. Conversely, the ratio of various subsidies to the total subsidy manifested different directions and degrees of impact on production efficiency and per capita disposable income, suggesting areas where the subsidy policy framework can be optimised. In addition to presenting a theoretical discussion on agricultural subsidy policies, this study provides theoretical insights and policy recommendations for the formulation and implementation of an optimal agricultural subsidy policy.

Suggested Citation

  • Yungang Tang & Haojie Liao & Ye Wu & Gang Lei, 2024. "Unravelling the bidirectional impact of Chinese agricultural subsidy policy on agricultural efficiency and farmers' income through panel data analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(4), pages 165-177.
  • Handle: RePEc:caa:jnlage:v:70:y:2024:i:4:id:335-2023-agricecon
    DOI: 10.17221/335/2023-AGRICECON
    as

    Download full text from publisher

    File URL: http://agricecon.agriculturejournals.cz/doi/10.17221/335/2023-AGRICECON.html
    Download Restriction: free of charge

    File URL: http://agricecon.agriculturejournals.cz/doi/10.17221/335/2023-AGRICECON.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.17221/335/2023-AGRICECON?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Rong-Gang Cong & Mark Brady, 2012. "How to Design a Targeted Agricultural Subsidy System: Efficiency or Equity?," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    2. Nadja El Benni & Robert Finger & Stefan Mann, 2012. "Effects of agricultural policy reforms and farm characteristics on income risk in Swiss agriculture," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(3), pages 301-324, November.
    3. Narangerel Ganbold & Shah Fahad & Hua Li & Tumendemberel Gungaa, 2022. "An evaluation of subsidy policy impacts, transient and persistent technical efficiency: A case of Mongolia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9223-9242, July.
    4. Jeremiás Máté Balogh, 2023. "The impacts of agricultural subsidies of Common Agricultural Policy on agricultural emissions: The case of the European Union," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(4), pages 140-150.
    5. Bernini, Cristina & Galli, Federica, 2024. "Economic and Environmental Efficiency, Subsidies and Spatio-Temporal Effects in Agriculture," Ecological Economics, Elsevier, vol. 218(C).
    6. D. Gale Johnson, 1948. "The Use of Econometric Models in the Study of Agricultural Policy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(1), pages 117-130.
    7. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    8. Nadja El Benni & Robert Finger & Stefan Mann, 2012. "Effects of agricultural policy reforms and farm characteristics on income risk in Swiss agriculture," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(3), pages 301-324, November.
    9. Štefan Bojnec & Imre Fertő, 2013. "Farm income sources, farm size and farm technical efficiency in Slovenia," Post-Communist Economies, Taylor & Francis Journals, vol. 25(3), pages 343-356, September.
    10. Jakub Staniszewski & Michał Borychowski, 2020. "The impact of the subsidies on efficiency of different sized farms. Case study of the Common Agricultural Policy of the European Union," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(8), pages 373-380.
    11. Tleubayev, Alisher & Bobojonov, Ihtiyor & Götz, Linde, 2022. "Agricultural policies and technical efficiency of wheat production in Kazakhstan and Russia: Evidence from a stochastic frontier approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 54(3), pages 407-421.
    12. Yinka Adetunji Adelekan & Abiodun Olusola Omotayo, 2017. "Linkage Between Rural Non-Farm Income and Agricultural Productivity in Nigeria: A Tobit-Two-Stage Least Square Regression Approach," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(3), pages 317-333, July-Sept.
    13. Tleubayev, Alisher & Bobojonov, Ihtiyor & Götz, Linde, 2022. "Agricultural Policies and Technical Efficiency of Wheat Production in Kazakhstan and Russia: Evidence from a Stochastic Frontier Approach," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 54(3), pages 407-421, August.
    14. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    15. Asraul Hoque, 1993. "Allocative Efficiency and Input Subsidy in Asian Agriculture," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 32(1), pages 87-99.
    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. Radosław PASTUSIAK & Magdalena JASINIAK & Michał SOLIWODA & Joanna STAWSKA, 2017. "What may determine off-farm income? A review," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(8), pages 380-391.
    2. Frýd, Lukáš & Sokol, Ondřej, 2021. "Relationships between technical efficiency and subsidies for Czech farms: A two-stage robust approach," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    3. Lajos Baráth & Imre Fertő & Štefan Bojnec, 2020. "The Effect of Investment, LFA and Agri‐environmental Subsidies on the Components of Total Factor Productivity: The Case of Slovenian Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 853-876, September.
    4. Kuhle Prudence Mnisi & Abdul Latif Alhassan, 2021. "Financial structure and cooperative efficiency: A pecking‐order evidence from sugarcane farmers in Eswatini," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(2), pages 261-281, June.
    5. Unknown, 2023. "Farmer’s adoption of agricultural insurance for Mediterranean crops as an innovative behavior," Economia agro-alimentare / Food Economy, Italian Society of Agri-food Economics/Società Italiana di Economia Agro-Alimentare (SIEA), vol. 25(2), October.
    6. Daria Loginova & Stefan Mann, 2022. "Institutional contributions to agricultural producer price stability," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-22, December.
    7. Duden, C. & Offermann, F., 2019. "Farmers' risk exposition and its drivers," 171st Seminar, September 5-6, 2019, Zürich, Switzerland 333722, European Association of Agricultural Economists.
    8. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    9. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    10. Todorich, Ludmila, 2018. "Эффективность Операционной Деятельности Сельскохозяйственных Предприятий," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 4(1), March.
    11. Friedrich Schneider & Mangirdas Morkunas & Erika Quendler, 2021. "Measuring the Immeasurable: The Evolution of the Size of Informal Economy in the Agricultural Sector in the EU-15 up to 2019," CESifo Working Paper Series 8937, CESifo.
    12. Wanglin Ma & Kathryn Bicknell & Alan Renwick, 2019. "Feed use intensification and technical efficiency of dairy farms in New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(1), pages 20-38, January.
    13. Harkness, Caroline & Areal, Francisco J. & Semenov, Mikhail A. & Senapati, Nimai & Shield, Ian F. & Bishop, Jacob, 2023. "Towards stability of food production and farm income in a variable climate," Ecological Economics, Elsevier, vol. 204(PA).
    14. Jean‐Paul Chavas & Doris Läpple & Bradford Barham & Emma Dillon, 2022. "An economic analysis of production efficiency: Evidence from Irish farms," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(2), pages 153-173, June.
    15. Andrzej Czyżewski & Ryszard Kata & Anna Matuszczak, 2022. "Determinants of the Agricultural Budget in Poland in the Light of Its Relation to GDP and State Budget Expenditure," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 3, pages 307-325.
    16. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2021. "Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 760-781, September.
    17. Mariarosaria Agostino & Ercan Enzo Comert & Federica Demaria & Sabrina Ruberto, 2024. "What kinds of subsidies affect technical efficiency? The case of Italian dairy farms," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 116-138, January.
    18. Galluzzo Nicola, 2020. "A Technical Efficiency Analysis of Financial Subsidies Allocated by the Cap in Romanian Farms Using Stochastic Frontier Analysis," European Countryside, Sciendo, vol. 12(4), pages 494-505, December.
    19. Petrick, Martin & Kloss, Mathias, 2013. "Identifying Factor Productivity from Micro-data: The case of EU agriculture," Working papers 144004, Factor Markets, Centre for European Policy Studies.
    20. Dragan Milić & Tihomir Novaković & Dragana Tekić & Bojan Matkovski & Danilo Đokić & Stanislav Zekić, 2023. "Economic Sustainability of the Milk and Dairy Supply Chain: Evidence from Serbia," Sustainability, MDPI, vol. 15(21), pages 1-21, October.

    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:caa:jnlage:v:70:y:2024:i:4:id:335-2023-agricecon. 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: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    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.