2023
DOI: 10.1590/0103-8478cr20210877
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Spatiotemporal differentiation and spatial correlation of agricultural total factor productivity in China: an estimation based on the data of prefecture-level cities

Abstract: The improvement of agricultural TFP is critical to promoting the high-quality development of agriculture. This paper described and identified the spatiotemporal differentiation characteristics and spatial correlation of China’s agricultural TFP in 283 prefecture-level cities from 2001 to 2018 using the Metafroniter-Malmquist and Moran index. The results showed that: (1) From 2001 to 2018, China’s agricultural TFP was 6.64%, and its growth was mainly driven by agricultural technological progress. The contributi… Show more

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Cited by 5 publications
(9 citation statements)
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“…According to Table 4, the individual and random errors of the model are small, the variance ratio ρ is above 0.5, the proportion of variance accounted for by the individual effect is large, and the value of the likelihood ratio (LR) is large, strongly rejecting the original hypothesis of a zero individual effect. These results suggest that using the random-effects Tobit model is a good fit [60,61].…”
Section: Benchmark Regression Resultsmentioning
confidence: 71%
“…According to Table 4, the individual and random errors of the model are small, the variance ratio ρ is above 0.5, the proportion of variance accounted for by the individual effect is large, and the value of the likelihood ratio (LR) is large, strongly rejecting the original hypothesis of a zero individual effect. These results suggest that using the random-effects Tobit model is a good fit [60,61].…”
Section: Benchmark Regression Resultsmentioning
confidence: 71%
“…Some scholars have also started with macro factors to analyse the influence mechanisms of the level of economic development, agricultural structure, agricultural resource endowment, agricultural infrastructure, environmental regulations and related policies on agri-environmental technical efficiency [ 34 ]. On the geographical level, existing studies have also carried out more detailed research [ [35] , [36] , [37] ], measured the spatial variability of interregional agri-environmental technology efficiency and clarified the main influencing factors and role of the mechanism, which leads to interregional agri-environmental technology efficiency variability of the most important influencing factors are technology and management [ 38 ]. At the same time, in the consideration of the influencing factors, the analysis is diversified from both internal and external perspectives of the region [ [39] , [40] , [41] ], and gradually focuses on the impact of carbon emissions on agri-environmental technical efficiency [ 42 ].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Qin S et al (2022) analyzed the relationship between factor mismatches and high-quality agricultural development based on China's interprovincial panel data from 2004 to 2020 and found that factor mismatches significantly inhibited improvements in high-quality agricultural development, and the inhibition effect had obvious spatialtemporal heterogeneity [23]. Du L et al (2023) and XW (2023) noted that improving agricultural total factor productivity is the key to promoting high-quality agricultural development [24,25]. Xing Deng HY (2022) noted that high-quality agricultural development requires not only the continuous growth of agricultural productivity but also green agricultural production [26].…”
Section: Study On Influencing Factors Of High-quality Agricultural De...mentioning
confidence: 99%