Forecast and Factor Analysis on Willingness of Moderate Scale Land Transfer-In

Hua Lin, Wen Zhang () and Zhiping Huang
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Hua Lin: School of Economics and Management, University of Chinese Academy of Sciences, Zhongguancun Nansantiao, Haidian District, Beijing 100190, China
Wen Zhang: School of Economics and Management, University of Chinese Academy of Sciences, Zhongguancun Nansantiao, Haidian District, Beijing 100190, China
Zhiping Huang: School of Economics and Management, University of Chinese Academy of Sciences, Zhongguancun Nansantiao, Haidian District, Beijing 100190, China

Sustainability, 2022, vol. 14, issue 23, 1-13

Abstract: The research on land transfer has essential theoretical and practical significance in ensuring food security and curbing the land de-graining. Based on the characteristics of large-scale and mechanized land in the H region of China, we constructed a prediction index for the willingness to transfer land in. The random forest (RF) algorithm was used to evaluate the importance of the factors affecting the land transfer-in willingness and the main factors were analyzed. The results show that: (1) The overall prediction accuracy of the RF model was 86.98% and the out-of-bag prediction error was 13.02%. (2) The factors that had an essential impact on the willingness to transfer to land were land area, the proportion of agricultural income, and crop type. The less influential factors were the size of the labor force, identity, and gender. (3) We found that 68% of the interviewed farmers wanted to increase land to expand the scale of production; this proportion was much higher than that in other parts of the country. The farmers were more willing to increase land to plant economic crops, which has a negative impact on the stability of food production. (4) Alleviating the negative impact of the Russian–Ukrainian conflict and stabilizing the production of economic crops, ensuring the safety of food production, and promoting the balanced development of food production and economic crops are topics that need to be continuously explored. This study can provide a useful reference for the development of the moderate-scale management of agriculture in China.

Keywords: food security; land transfer willingness; machine learning; random forest; land de-graining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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