International Journal of Economy, Energy and Environment
Volume 4, Issue 6, December 2019, Pages: 106-117
Received: Oct. 15, 2019;
Accepted: Nov. 7, 2019;
Published: Dec. 4, 2019
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Wu Mingran, School of Business, Hohai University, Nanjing, China; Science and Technology System Reform Think Tank of Jiangsu Province, Nanjing, China
Zhao Min, School of Business, Hohai University, Nanjing, China; Science and Technology System Reform Think Tank of Jiangsu Province, Nanjing, China
Wu Zhaodan, School of Business Administration, Hohai University, Changzhou, China
Based on time series data from 1990 to 2016, an empirical analysis examined the factors affecting China's agricultural economic growth by developing a vector auto-regressive model (VAR), impulse response function (IRF) and variance decomposition function (VD). The results show that Chinese agriculture lacks long-term support factor. During the study period, an increase in the fixed asset investment, the total agricultural machinery power, the amount of chemical fertilizer used, and the education level of the rural labor force contributed to agricultural economic growth. However, an increase in the size of the agricultural labor force and in the total area under cultivation was not conducive to agricultural economic growth. In addition, China's agricultural economic growth was overly dependent on financial investment, while the contribution of other factors was relatively small. China's agricultural economy clearly has experienced extensive development. Hence, in the next development period, the Chinese government needs to increase agricultural fixed asset investment and strengthen its oversight. In addition, the government needs to strengthen its support of agricultural mechanization, set reasonable limits on the use of chemical fertilizers and, more importantly, focus on improvement in the quality of agricultural products and the accumulation of human capital.
The Dynamic Analysis of China's Agricultural Economic Growth, International Journal of Economy, Energy and Environment.
Vol. 4, No. 6,
2019, pp. 106-117.
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