Spatial-Temporal Pattern of Agricultural Total Factor Productivity Change (Tfpch) in China and Its Implications for Agricultural Sustainable Development

Zhang, Haonan; Chen, Zheng; Wang, Jieyong; Wang, Haitao; Zhang, Yingwen

doi:10.3390/agriculture13030718

Cited by 5 publications

(4 citation statements)

References 52 publications

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“…The DEA-Malmquist index method has been extensively utilized in agricultural economics to measure TFP, demonstrating its universality and maturity across diverse studies. Its application in analyzing agricultural TFP in both developed and developing regions, such as [41][42][43], reveals its broad adaptability and effectiveness.…”

Section: Malmquist Indexmentioning

confidence: 99%

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

Liu,

Li,

et al. 2024

Agriculture

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The urgency of enhancing agricultural productivity within the Yellow River Basin cannot be overstated, given its critical role in ensuring food security amidst the challenges posed by climate change, natural disasters, and the increasing demand for food crops. Utilizing panel data from nine provinces within the Yellow River Basin for the period 2001 to 2020, this study examines the temporal characteristics and spatial distribution of Total Factor Productivity (TFP) for key grain crops—namely wheat, corn, and soybean—through the application of the Malmquist index which can be decomposed through the DEA-Malmquist index methodology. The empirical results demonstrate that TFP growth rates for these crops have exhibited significant phase variations, with soybean recording the highest TFP growth rate in the basin. Additionally, this study underscores marked regional disparities in soybean productivity. TFP decomposition reveals that the primary drivers of TFP improvement across these crops are attributed to technical progress, with gains in overall technical efficiency largely due to scale efficiency enhancements, whereas pure technical efficiency has shown limited progress. Regional analysis indicates that Inner Mongolia leads in TFP growth for all crops, while Ningxia, Sichuan, and Shaanxi lag behind in wheat, corn, and soybean. Additionally, our analysis delineates natural disasters as a significant barrier to Total Factor Productivity (TFP), notably obstructing technological advancements in wheat cultivation. The investigation further reveals a positive relationship between regional per capita income and the growth of wheat TFP, in contrast to a negative relationship with the TFP growth of corn and soybeans. Moreover, investing in agriculture, forestry, water management, and road infrastructure supports the growth of wheat TFP, while urbanization levels pose constraints. Conclusively, an uptick in annual rural electricity usage, along with improved per capita postal and telecommunication services, exerts a favorable influence on TFP for corn and soybeans.

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Section: Malmquist Indexmentioning

confidence: 99%

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

Liu,

Li,

et al. 2024

Agriculture

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“…The Chinese government proposed building ecological agriculture and promoting organic farming and green food more than 40 years ago [6,7]. In recent years, China has been vigorously promoting green agriculture, and it is expected that a new pattern of SA development will largely be established by 2030 [8,9]. The focus of SA is to ensure a stable food supply while protecting the environment and natural resources [8,10].…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, China has been vigorously promoting green agriculture, and it is expected that a new pattern of SA development will largely be established by 2030 [8,9]. The focus of SA is to ensure a stable food supply while protecting the environment and natural resources [8,10]. However, according to data published by the Food and Agriculture Organization of the United Nations (FAO), global fertilizer use in 2020 exceeds 53 million tons, while pesticide use exceeds 4 million tons (Figure 1), and the long-term use of large amounts of pesticides poses a threat to the global environment and human health [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Game of Pesticide Reduction Management for Sustainable Agriculture: An Analysis Based on Local Governments, Farmers, and Consumers

Sun

2023

Sustainability

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Promoting pesticide reduction is a critical component of achieving sustainable agriculture. However, the challenges involved in coordinating diverse stakeholder demands pose difficulties in promoting pesticide reduction behavior. To reveal the evolutionary paths of the decision-making processes of each player under various influencing factors and optimize pesticide reduction policies, this paper proposes a three-way evolutionary game model that considers the interests of the local governments, farmers, and consumers. The study reveals six stable equilibrium strategies in the evolutionary game system of pesticide reduction for sustainable agriculture (SA). Under polycentric governance, ideal states allow local governments to regulate farmers’ pesticide reduction and consumers’ purchases of green agricultural products. Regulatory measures such as providing technical and in-kind subsidies for pesticide reduction, imposing penalties for the overuse of pesticides, and promoting public awareness influence farmers’ and consumers’ decisions when it comes to reducing pesticides and purchasing green produce. Moreover, the total benefits of pesticide reduction for farmers and the utility of green produce consumption for consumers are primary factors that influence the evolutionary game system’s eventual evolution toward different stable equilibrium strategies. These factors primarily affect the supply and demand of green products, which in turn impacts pesticide reduction. This study enhances the policy analysis of pesticide reduction and provides valuable insights into constructing a pesticide reduction policy system based on polycentric governance.

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“…On the road of agricultural transformation in China, the improvement of agricultural total factor productivity is one of the key points that need to be concerned. Existing literature on agricultural total productivity mainly measures the agricultural total productivity of various provinces and analyzes its trend in China and various provinces based on econometric methods such as Stochastic Frontier Approach (SFA) and Data Envelopment Analysis (DEA) (Gong, 2018;Zhang et al, 2023); other studies also concern specific measures to improve agricultural total productivity (Sheng et al, 2019). However, ensuring the steady improvement of agricultural production efficiency and resource utilization efficiency while successfully completing the transformation from a traditional small-scale peasant economy to a large-scale modern agricultural economy remains the focus and a difficulty for current policymakers and academics.…”

mentioning

confidence: 99%

Can development of large scale agricultural business entities improve agricultural total factor productivity in China?: an empirical analysis

Ju,

Li,

Liu

et al. 2023

Front. Sustain. Food Syst.

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Large scale agricultural business entities (hereinafter referred to as “the large scale entities”) are newly sprouted in the process of China’s agricultural transformation from traditional production to modern mode, while the improvement of agricultural total factor productivity is an important driving force to realize agricultural transformation in China. Therefore, it is of great significance to explore whether the former has a promoting effect on the latter. First of all, the effective improvement of agricultural total factor productivity by the large scale entity development is analyzed from the two aspects of scale effect and technology utilization effect, and the effect mechanism is discussed in depth in this paper. Secondly, empirical test was carried out by using the panel data of prefecture-level cities from 2015 to 2020. The benchmark regression results show that the development of large scale entities can significantly improve agricultural total factor productivity. The mechanism test results indicate that the development of large scale entities improves the agricultural total factor productivity by raising the agricultural mechanization level. The results of heterogeneity analysis show that the difference between large scale entities would affect the benchmarking results. Therefore, it is believed through the study as discussed in this paper that devoting greater effort to support the development of large scale entities is an important measure to improve agricultural total factor productivity and promote China’s agricultural transformation, but it is necessary to act according to local conditions based on the difference of entity types in the process.

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Spatial-Temporal Pattern of Agricultural Total Factor Productivity Change (Tfpch) in China and Its Implications for Agricultural Sustainable Development

Cited by 5 publications

References 52 publications

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

Decomposition and Driving Factors of Total Factor Productivity of Food Crops in the Yellow River Basin, China

Evolutionary Game of Pesticide Reduction Management for Sustainable Agriculture: An Analysis Based on Local Governments, Farmers, and Consumers

Can development of large scale agricultural business entities improve agricultural total factor productivity in China?: an empirical analysis

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