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Factors affecting farmland rental in rural China: Evidence of capitalization of grain subsidy payments

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  • Zhang, Jian
  • Mishra, Ashok K.
  • Hirsch, Stefan
  • Li, Xiaoshun

Abstract

This study investigates the factors affecting farmland rental prices in China. Special emphasis is put on the capitalization of China’s grain subsidy program into land rental rates. Using national representative farm-level data, Heckman sample selection model, and quantile regression (QR) approach, we find that a 10% increase in grain subsidy payments for contracted farmland increases the farmland rental price by about 1%. However, quantile regression results show that the capitalization rate is heterogeneous and varies across the distribution. Findings suggest that family labor input and farm location are important factors driving up farmland rental prices. Moreover, for farm size, rental experience, and natural disaster we detect a negative impact on land rental prices.

Suggested Citation

  • Zhang, Jian & Mishra, Ashok K. & Hirsch, Stefan & Li, Xiaoshun, 2020. "Factors affecting farmland rental in rural China: Evidence of capitalization of grain subsidy payments," Land Use Policy, Elsevier, vol. 90(C).
  • Handle: RePEc:eee:lauspo:v:90:y:2020:i:c:s0264837719310671
    DOI: 10.1016/j.landusepol.2019.104275
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    More about this item

    Keywords

    Farmland rental prices; Grain subsidy; Capitalization rate; Quantile regression;
    All these keywords.

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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