Abstract
In order to analyze the influencing factors of TFP (the abbreviation of Total Factor Productivity) deeply, this paper calculates and decomposes the TFP of the main grain producing provinces in China from 2006 to 2015 by the DEA-Malmquist index model. On the basis of this, the grey correlation analysis model based on super-efficiency DEA is used to quantitatively analyze the influencing factors of total factor productivity, technological progress and technical efficiency. The results show that the proportion of grain sowing, the level of food economic development, the level of grain mechanization, the average scale of operations and the level of fertilizer using have the most influence on grain total factor productivity. Finally, according to the results of the analysis, some suggestions are put forward to improve the TFP of different provinces in the main grain producing areas.
Highlights
The grain issue is always the foundation for the development of the country’s economy and social stability and an important issue concerning international livelihood for a populous country that accounts for about 20% of the world’s population with 7% of the world’s land
The results show that the proportion of grain sowing, the level of food economic development, the level of grain mechanization, the average scale of operations and the level of fertilizer using have the most influence on grain total factor productivity
According to the ranking of influencing factors on total factor productivity of the main grain producing areas, Anhui Province, Hubei Province, Inner Mongolia, Sichuan Province and Henan Province were most affected by the sown proportion of grain; Hebei Province, Heilongjiang Province, Hunan Province and Jiangsu Province, Jilin Province and Liaoning Province were most affected by the level of grain economy development; Jilin Province and Liaoning Province were most affected by the level of grain mechanization; Jiangxi Province was most affected by the average labor management scale; Shandong Province was most affected by the level of fertilizer using per unit area
Summary
The grain issue is always the foundation for the development of the country’s economy and social stability and an important issue concerning international livelihood for a populous country that accounts for about 20% of the world’s population with 7% of the world’s land. It is necessary to conduct a quantitative study on grain total factor productivity in main grain producing areas of our country. There are few papers that analyzed the influencing factors of total factor productivity and its decomposition index in the main grain-producing areas by multi-level correlation analysis. This paper measures and decomposes the TFP of main grain-producing provinces in China by the DEA-Malmquist index model. The influencing factors of TFP are quantitative ranking analyzed by the improved grey correlation analysis model based on the super efficiency DEA. The local governments of main grain-producing provinces can take more specific measures to improve the efficiency of total factor production of grain by the analysis of this paper
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