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Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model—13,120 Farming Households in 26 Provinces of China as an Example

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  • Xiangdong Wang

    (School of Management, Lanzhou University, Lanzhou 730000, China
    Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou 730000, China)

  • Decheng Zhao

    (School of Management, Lanzhou University, Lanzhou 730000, China)

Abstract

Cropland abandonment is a widespread phenomenon with an increasing trend around the world, including China. Cropland abandonment is the result of a multi-scale and multifactor nested structure. In order to comprehensively identify the individual and background effects, this study explores the causes of the differences in farmland abandonment levels at two levels: farm household and village, based on a hierarchical linear model. The results show that (1) 83.63% of the differences in farm abandonment rates are differences in farm households, while 16.37% are differences in their villages; (2) several factors, including whether the head of household is healthier, per capita cropland area, ratio of transferred farmland, possession of large-scale agricultural production machinery or livestock for agricultural production, ratio of agricultural income, and whether there are village cadres, have a significant negative impact on abandonment rates at the farm household level, while at the village level, commuting distance, whether it is a suburb of a large or medium-sized city, topography of the village is plain or not, and the ratio of the number of people in agricultural production in the village have a significant positive impact on abandonment rates. Furthermore, whether it has experienced land expropriation has a significant positive effect on the abandonment rate; (3) commuting distance weakens the negative correlation between the ratio of transferred cropland and the ratio of agricultural income and the abandonment rate. In addition, whether it is a suburb of a large or medium-sized city strengthens the negative correlation between whether it owns large-scale agricultural production machinery or livestock and the abandonment rate, and whether the topography of the village is plain weakens the negative correlation between the possession of large agricultural production machinery or livestock for agricultural production and the agricultural income ratio and the abandonment rate. Furthermore, ratio of the number of people in agricultural production in the village weakens the negative correlation between the ratio of transferred cropland and abandonment rate, and whether the village has experienced land expropriation strengthens the negative correlation between the ratio of agricultural income and abandonment rate.

Suggested Citation

  • Xiangdong Wang & Decheng Zhao, 2023. "Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model—13,120 Farming Households in 26 Provinces of China as an Example," Land, MDPI, vol. 12(9), pages 1-22, September.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1791-:d:1240480
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    References listed on IDEAS

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    1. Xin Deng & Miao Zeng & Dingde Xu & Yanbin Qi, 2022. "Why do landslides impact farmland abandonment? Evidence from hilly and mountainous areas of rural China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 699-718, August.
    2. Guandong Su & Hidenori Okahashi & Lin Chen, 2018. "Spatial Pattern of Farmland Abandonment in Japan: Identification and Determinants," Sustainability, MDPI, vol. 10(10), pages 1-22, October.
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    4. Wojciech Sroka & Bernd Pölling & Tomasz Wojewodzic & Miroslaw Strus & Paulina Stolarczyk & Olga Podlinska, 2019. "Determinants of Farmland Abandonment in Selected Metropolitan Areas of Poland: A Spatial Analysis on the Basis of Regression Trees and Interviews with Experts," Sustainability, MDPI, vol. 11(11), pages 1-23, May.
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