Can Agricultural Machinery Harvesting Services Reduce Cropland Abandonment? Evidence from Rural China

Abstract

Ending hunger, achieving food security, and promoting sustainable agriculture are the main targets of sustainable development goals. It is well known that cropland resources are the most essential factor in achieving sustainable development goals. However, China has been facing the problem of a continuous reduction in cropland resources. Reducing the abandonment of cropland has become an important way to curb the reduction in cropland resources. Can agricultural machinery harvesting services reduce cropland abandonment in rural China? To answer this scientific question, this study employs the Survey for Agriculture and Village Economy data from 8345 samples of 12 provinces in rural China. The extended regression models (i.e., the extended probit regression model and the extended interval regression model) are used to empirically analyze the relationship between agricultural machinery harvesting services accessed by farmers and cropland abandonment. The results are as follows. Agricultural machinery harvesting services accessed by farmers significantly reduced the probability of cropland abandonment and the proportion of the area of abandoned cropland in farmers’ contracted cropland area decreased by 18.5% and 20.3%, respectively. Moreover, the heterogeneity analysis results showed that farmers’ access to agricultural machinery harvesting services significantly reduced cropland abandonment in small-scale groups, without elderly households, with nonagricultural income groups, and in the eastern region. This study also provides some policy implications for policymakers to reduce cropland abandonment in rural China.

Do agricultural productive services alleviate farmland abandonment? Evidence from China rural household panel survey data

“…After controlling for other variables, every 1% increase in APS and the proportion of land abandonment area will drop by 1.51 percentage points. It is consistent with the conclusions of (Yu et al, 2021;Zhang et al, 2022;Xue et al, 2022), which believe that APS plays an important role in the effective allocation of farmland resources. Farmers not only obtain green production technology and planting information by purchasing APS but also gain economies of scale (Qian et al, 2022); Especially for the farmers who have "land attachment", the emotional sustenance of the land makes the farmers unwilling to abandon the land (Zhang et al, 2022;Liu et al, 2022).…”

“…Thus, the core independent variables may be endogenous variables. In order to solve the possible endogenous problems, this study refers to a similar setting of Xue et al (2022). This study selected the average expenditure of APS purchased by farmers in the same village except for the surveyed farmers as the instrument variable, which is IVS i = (S 1 + S 2 + .…”

“…Higher agricultural production costs and lower income make scattered and small-scale land difficult to transfer for profit, and the land that cannot be transferred out will be abandoned by farmers (Lieskovský et al, 2015;Cheng et al, 2022). Moreover, some farmers still have a "land complex", so they would rather abandon the cropland than transfer it out (Whalley and Zhang, 2007;Zhang et al, 2022;Xue et al, 2022). Regarding social factors, with the rapid development of urbanization and industrialization, the non-agricultural rural population has exceeded the first turning point of Lewis (Zhou, 2017;Zhao et al, 2022).…”

“…Pest control outsourcing services significantly decrease the size of land abandonment (Zhang et al, 2022). Machinery harvesting service has a significant negative impact on land abandonment (Xue et al, 2022). A few studies explore the impact of agricultural services on land abandonment, which only focus on the mechanical services in a certain link and the issues discussed need to be more comprehensive.…”

Impacts of COVID-19 on Nutritional Intake in Rural China: Panel Data Evidence

“…We used the 2019-2020 Survey for Agriculture and Village Economy (SAVE) data collected by the Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences [53][54][55]. The 2019-2020 SAVE data record the annual production, consumption, expenditure, and income of the rural households and cover 5818 observations in the Hebei, Jilin, Heilongjiang, Anhui, Fujian, Henan, Hunan, Sichuan, and Yunnan provinces of China (Figure 1).…”