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How Do Rising Farmland Costs Affect Fertilizer Use Efficiency? Evidence from Gansu and Jiangsu, China

Author

Listed:
  • Yuan Qi

    (College of Land Science and Technology, China Agricultural University, Beijing 100193, China)

  • Xin Chen

    (Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China)

  • Jiaqing Zhang

    (College of Land Science and Technology, China Agricultural University, Beijing 100193, China)

  • Yaoyao Li

    (College of Land Science and Technology, China Agricultural University, Beijing 100193, China)

  • Daolin Zhu

    (College of Land Science and Technology, China Agricultural University, Beijing 100193, China
    Center for Land Policy and Law, Beijing 100193, China)

Abstract

As the farmland transfer market in China develops, moderate-scale operations increasingly grow but without much improvement in fertilizer use efficiency. This study theoretically analyzes the mechanism and effect of rising farmland costs on fertilizer use efficiency using multiple quadratic regression and mediating effects models. It empirically tests a micro-sample of 806 farmers in Gansu and Jiangsu provinces in China from two dimensions: the full samples and farmer heterogeneity. The results showed 0.544 as the average fertilizer use efficiency (hereinafter, fe ) of farmers in Gansu and Jiangsu, highlighting the severe loss of fe caused by excessive fertilizer inputs. The multiple quadratic regression model further revealed an inverted U-shaped relationship between farmland costs and fe , with the U-shaped curve showing a remarkable inflection point at the USD 708/mu mark. When farmland costs are excessive ( cost > CNY 708/mu), the increase in farmland costs inhibits the fe . An investigation of the corresponding impact mechanism for this scenario (i.e., cost > USD 708/mu) revealed that farmland costs directly suppress fe (−0.485) by distorting the fertilizer factor substitution effect and indirectly suppress fe (−0.037) by impeding the technology spillover effect of production specialization and production scale-up. We also found heterogeneity between two groups: ordinary farmers and new agricultural operators (e.g., large grain and family farmers), with the peak kernel density function of fe of new agricultural operators (0.85) being much higher than that of ordinary farmers (0.30). Moreover, the multiple quadratic regression between the groups revealed a lower inflection point for ordinary farmers (CNY 638/mu) than new agricultural operators (CNY 823/mu), highlighting that the fe of ordinary farmers was more likely to be inhibited by the excessive rise in farmland costs. To promote the sustainable development of China’s agricultural production, we propose reducing the cost of farmland, promoting service-scale operations, and fostering new agricultural operators.

Suggested Citation

  • Yuan Qi & Xin Chen & Jiaqing Zhang & Yaoyao Li & Daolin Zhu, 2022. "How Do Rising Farmland Costs Affect Fertilizer Use Efficiency? Evidence from Gansu and Jiangsu, China," Land, MDPI, vol. 11(10), pages 1-18, October.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1730-:d:934543
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    References listed on IDEAS

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    1. Martey, Edward & Kuwornu, John K.M. & Adjebeng-Danquah, Joseph, 2019. "Estimating the effect of mineral fertilizer use on Land productivity and income: Evidence from Ghana," Land Use Policy, Elsevier, vol. 85(C), pages 463-475.
    2. Xu, Yuting & Huang, Xianjin & Bao, Helen X.H. & Ju, Xiang & Zhong, Taiyang & Chen, Zhigang & Zhou, Yan, 2018. "Rural land rights reform and agro-environmental sustainability: Empirical evidence from China," Land Use Policy, Elsevier, vol. 74(C), pages 73-87.
    3. Margarita Genius & Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2014. "Information Transmission in Irrigation Technology Adoption and Diffusion: Social Learning, Extension Services, and Spatial Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 328-344.
    4. Jianqiang Wu & Chenyan Sha & Min Wang & Chunmei Ye & Peng Li & Shenfa Huang, 2021. "Effect of Organic Fertilizer on Soil Bacteria in Maize Fields," Land, MDPI, vol. 10(3), pages 1-14, March.
    5. 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.
    6. T. Brunelle & P. Dumas & F. Souty & B. Dorin & F. Nadaud, 2015. "Evaluating the impact of rising fertilizer prices on crop yields," Agricultural Economics, International Association of Agricultural Economists, vol. 46(5), pages 653-666, September.
    7. Zhang, Yingnan & Long, Hualou & Li, Yurui & Ge, Dazhuan & Tu, Shuangshuang, 2020. "How does off-farm work affect chemical fertilizer application? Evidence from China’s mountainous and plain areas," Land Use Policy, Elsevier, vol. 99(C).
    8. Yanggen, David & Kelly, Valerie A. & Reardon, Thomas & Naseem, Anwar, 1998. "Incentives for Fertilizer Use in Sub-Saharan Africa: A Review of Empirical Evidence on Fertilizer Response and Profitability," Food Security International Development Working Papers 54677, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    9. Li, Bowei & Shen, Yueqin, 2021. "Effects of land transfer quality on the application of organic fertilizer by large-scale farmers in China," Land Use Policy, Elsevier, vol. 100(C).
    10. Gao, Li & Zhang, Wendong & Mei, Yingdan & Sam, Abdoul G. & Song, Yu & Jin, Shuqin, 2018. "Do farmers adopt fewer conservation practices on rented land? Evidence from straw retention in China," Land Use Policy, Elsevier, vol. 79(C), pages 609-621.
    11. Madhu Khanna, 2001. "Sequential Adoption of Site-Specific Technologies and its Implications for Nitrogen Productivity: A Double Selectivity Model," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 35-51.
    12. Xie, Jinhua & Yang, Gangqiao & Wang, Ge & Song, Yan & Yang, Fan, 2021. "How do different rural-land-consolidation modes shape farmers’ ecological production behaviors?," Land Use Policy, Elsevier, vol. 109(C).
    13. Huarui Gong & Jing Li & Zhen Liu & Yitao Zhang & Ruixing Hou & Zhu Ouyang, 2022. "Mitigated Greenhouse Gas Emissions in Cropping Systems by Organic Fertilizer and Tillage Management," Land, MDPI, vol. 11(7), pages 1-18, July.
    14. Lampach, Nicolas & To-The, Nguyen & Nguyen-Anh, Tuan, 2021. "Technical efficiency and the adoption of multiple agricultural technologies in the mountainous areas of Northern Vietnam," Land Use Policy, Elsevier, vol. 103(C).
    15. Bambio, Yiriyibin & Bouayad Agha, Salima, 2018. "Land tenure security and investment: Does strength of land right really matter in rural Burkina Faso?," World Development, Elsevier, vol. 111(C), pages 130-147.
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