Agricultural mechanization and cropland abandonment in rural China

Ma, Wanglin; Zhu, Zhongkun; Zhou, Xiaoshi

doi:10.1080/13504851.2021.1875113

Cited by 36 publications

(21 citation statements)

References 25 publications

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“…Although labor migration contributes to rural income growth, it also generates a series of issues, such as farm labor shortage and rising farm labor wages, that challenge sustainable agricultural production. As farm machinery can substitute farm labor and potentially save production costs by improving farm production efficiency (Liu et al, 2014;Ma et al, 2021;Mano et al, 2020;Mondal et al, 2021;Olmstead and Rhode, 2014;Wang et al, 2016;Zhou et al, 2018), the development of farm machinery has been growing in recent years.…”

Section: Introductionmentioning

confidence: 99%

Interactive relationship between non-farm employment and mechanization service expenditure in rural China

Zheng

Guo

et al. 2021

CAER

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PurposeThe purpose of this study is to investigate the interactive relationship between non-farm employment and mechanization service expenditure.Design/methodology/approachThe study employs an innovative two-stage probit least squares (2SPLS) model to analyze the survey data collected from 1,148 rural households in China. This model not only simultaneously estimates the impact of non-farm employment on mechanization service expenditure and the impact of mechanization service expenditure on non-farm employment, but also addresses endogeneity issues associated with these two activities.FindingsThe empirical results show that non-farm employment and mechanization service expenditure are jointly determined. In particular, the study finds that non-farm employment significantly increases mechanization service expenditure, and vice versa. The results are confirmed by an estimation that captures a dichotomous decision of mechanization service usage. The interactive effects of non-farm employment on mechanization service expenditure are heterogeneous between male and female household heads and among households with different member sizes. Further analyses reveal that (1) mechanization service expenditure increases with increasing non-farm working time; (2) local non-farm employment, rather than provincial non-farm employment, has a larger impact on mechanization service expenditure; and (3) the number of household members employed in non-farm works does not affect mechanization service expenditure significantly.Originality/valueAlthough mechanization service markets are rapidly growing in many developing and transition countries, little is known about how service purchasing interacts with farmers' decisions to work in the non-farm sector. This study makes the first attempt by investigating the interactive effects of non-farm employment on mechanization service expenditure in rural China. The findings provide significant evidence for policymakers in China and other countries in their efforts to generate non-farm work opportunities and promote agricultural mechanization, with the aim of boosting rural development and improving farm economic performance.

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Section: Introductionmentioning

confidence: 99%

Interactive relationship between non-farm employment and mechanization service expenditure in rural China

Zheng

Guo

et al. 2021

CAER

Self Cite

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“… Cattaneo (2010) develops a theory for semiparametric estimators and applies that to analyze quantile treatment effects. The MVTE models have conditional independence and sufficient overlap assumption ( Ma et al., 2021 ). In addition, MVTE models work through observed characteristics; as a result, bias for unobservable characteristics may exist ( Kazal et al., 2020 ).…”

Section: Methodsmentioning

confidence: 99%

“…Inverse probability weighted regression adjustment (IPWRA), alternatively known as Wooldridge's ‘doubly robust’ estimator ( Wooldridge, 2010 ), ensures consistent and unbiased results since it allows the treatment and the outcome model to account for misspecification ( Ma et al., 2021 ). In the IPWRA model, ATT was estimated through two steps ( Imbens and Wooldridge, 2009 ).…”

Section: Methodsmentioning

confidence: 99%

Intensity of adoption and welfare impacts of drought-tolerant rice varieties cultivation in Bangladesh

Rahman

Sujan

Acharjee

et al. 2022

Heliyon

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“…The study found (Jin, 2013) that the new land policy inhibited the abandonment to a certain extent, but in some areas, the implementation of the benefit farming policy induced the abandonment of some farmlands. (Ma et al, 2022) found that the higher the degree of mechanization of farmland, the more cautious farmers' choice of the farmland abandonment. Therefore, the improvement of the mechanization level of farming is conducive to reducing the farmland abandonment.…”

Section: Introductionmentioning

confidence: 99%

Study on spatiotemporal evolution of farmland abandonment and its influencing factors in the developed county of China

Wang

et al. 2022

Preprint

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The protection of farmland resources is related to world food security, as well as the smooth realization of the goals of UN 2030 Agenda for Sustainable Development and China's Rural Revitalization Plan. As the most active region in the global economic development and one of the main grain producing areas, the problem of farmland abandonment in the Yangtze River Delta gradually appears with the rapid development of urbanization. Therefore, Based on the interpretation data of remote sensing images and field survey data of three periods in 2000, 2010 and 2018, this study used Moran’s I and Geographical barycenter model to reveal the spatiotemporal evolution law of farmland abandonment in Pingyang County of the Yangtze River Delta. And then, this study selected 10 indicators covering four categories: geography, proximity, distance and policy, and used random forest model to reveal the main influencing factors of farmland abandonment in the study area. The results showed that the abandoned farmland increased from 441.58 hm2 in 2000 to 5797.40 hm2 in 2018. The hot spot and barycenter of land abandonment gradually shifted from the western mountainous areas to the eastern plain areas. Altitude and slope were the main factors affecting the farmland abandonment. The high the altitude and the great the slope, the farmland abandonment in mountainous areas were serious. The proximity factors had a greater impact on the expansion of farmland abandonment from 2000 to 2010, and then the impact weakened. In view of the above analysis, the countermeasures and suggestions for maintaining food security were finally put forward.

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Agricultural mechanization and cropland abandonment in rural China

Cited by 36 publications

References 25 publications

Interactive relationship between non-farm employment and mechanization service expenditure in rural China

Interactive relationship between non-farm employment and mechanization service expenditure in rural China

Intensity of adoption and welfare impacts of drought-tolerant rice varieties cultivation in Bangladesh

Study on spatiotemporal evolution of farmland abandonment and its influencing factors in the developed county of China

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