Agricultural mechanization and cropland abandonment in rural China

ABSTRACT

This study examines the impacts of the adoption of three mechanized farming strategies (no-mechanized, semi-mechanized, and full-mechanized farming) on cropland abandonment, using the 2016 China Labour-force Dynamics Survey data. An innovative multivalued treatment effects model is employed to address sample selection bias. The results show that relative to no-mechanized farming, the adoption of semi-mechanized farming increases the probability of cropland abandonment. However, relative to either no or semi-mechanized farming, the adoption of full-mechanized farming significantly decreases the likelihood of cropland abandonment. Thus, farmers’ decisions of cropland abandonment depend on whether mechanization can partially or fully substitute farm labour. Our findings suggest that promoting agricultural mechanization via scale and topography-appropriate farm machines and enhancing land transfer for consolidation can help alleviate cropland abandonment.

KEYWORDS:

• Agricultural mechanization
• cropland abandonment
• multivalued treatment
• China

JEL CLASSIFICATION:

• C31
• Q16
• R14

Acknowledgments

Xiaoshi Zhou acknowledges the financial support from the National Natural Science Foundation of China (No. G030802). Zhongkun Zhu acknowledges the funding support from the National Natural Science Foundation of China (Grant No. 71903062).

Data availability statement

The data that support the findings of this study are available from the leading author, Wanglin Ma, upon reasonable request.

Disclosure statement

There is no conflict of interest.

Notes

¹ The doubly-robust property of the IPWRA estimator states that either the treatment model or the outcome model is correctly specified, the treatment effects estimates are unbiased. This is different from the PSM model that only emphasizes the correct specification of the treatment model.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [71903062,G030802].