Abstract
To explore the conducive to China’s agricultural science and technology park of input and output of the related strategy and promote agricultural supply side structural reform in China, we use cobb-douglas production function model, combined with stepwise regression and principal component regression method, the analysis of 2015–2017 China national agricultural science and technology park enterprise data. We summarized the relationship between the input and output by cobb-douglas production function. The investment of labor force and capital investment and the annual output value were positive correlation, but the elasticity coefficient of labor input three years to show the trend of increasing year by year. Elasticity coefficient of capital in three years presents a decreasing trend year by year. By stepwise regression and principal component regression method, you can see that is not the total amount of investment. The greater the output, the more technology innovation factors will become the future main factors influencing the development of the national agricultural science and technology park. Therefore, China should strengthen agricultural science and technology innovation, cultivate agricultural science and technology talents. Develop agricultural science and technology innovation projects, so as to promote China’s agricultural supply-side structural reform.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dezhi, Q., Huimin, S.: Analysis of the reason for China’s agricultural industrial structure adjustment based on the extended cobbe Douglas production function. Rural. Econ. 59–63 (2016)
Huanming, X.: Quality measurement of China’s economic growth based on green GDP. Stat. Decis. Mak. 09, 27–29 (2014)
Xiaojing, Z.: Analysis of factors influencing China’s economic growth based on cobbe Douglas production function. China Mark. 41, 117–118+133 (2013)
Pengpeng, W., Haijun, H.: Empirical study on Chongqing economic growth based on C-D production function. Market BBS 07, 20+14 (2011)
Jie, L., Yinlao, K., Yao, L.: A study of the pan-cobbe Douglas model on the relationship between investment and consumption and GDP growth. Contemp. Econ. 06, 120–121 (2007)
Xiaojie, Z., Guanglin, Y., Fulin, W.: Calculation of agricultural mechanization contribution rate by cobb Douglas production function method. Agric. Mech. Res. 03, 37–39 (2000)
Paulo, D., Diogenes, L.: Cobb-Douglas, translog stochastic production function and data envelopment analysis in total factor productivity in Brazilian agribusiness. J. Oper. Supply Chain. Manag., 20–33 (2009)
Humphrey, T.M.: Algebraic production functions and their uses before Cobb-DouglasX. FRB Richmond Econ. Q. 83(1), 51–83 (2016)
Dana, H., Jaromír, H.: Cobb-douglas production function: the case of a converging economy. Czech J. Econ. Financ. 57(9–10), 465–476 (2007)
Antràs, P.: Is the U.S. Aggregate production function Cobb-Douglas? New estimates of the elasticity of substitution. Contrib. Macroecon. 4(1), 10 (2018)
Douglas, P.H.: The Cobb-Douglas production function once again: its history, its testing, and some new empirical values. J. Polit. Econ. 84(5), 903–916 (1976)
Jichang, Z., Xun, Z.: Agricultural modernization was first realized in the construction of agricultural science and technology demonstration park. China Agric. Sci. Technol. Guid. 3, 10–13 (2001)
Tongsheng, L., Yali, L.: Technological diffusion in agricultural science and technology parks. Geogr. Res. 35(3), 419–430 (2016)
Xuexin, Z., Yujun, Z.: Study on interaction between agricultural science and technology park and regional economic and social development in Jiangsu province. Agric. Econ. 9, 72–76 (2013)
Heping, J.: Analysis of characteristics and types of agricultural science and technology parks in China. Chin. Rural. Econ. 10, 23–29 (2000)
Jianzhong, Z., Tongsheng, L., Huidong, L.: Development status and dynamic mechanism of China’s agricultural science and technology parks. Rural. Econ. 12, 56–59 (2006)
Heping, J., Kai, C.: Agricultural science and technology park: focus on effective model and demonstration. Agric. Econ. 1, 9–14 (2009)
Hongyong, S., Xiaojing, L., Zhaoqiang, J.: Discussion on development model of Cangzhou national agricultural science and technology park. J. Chin. Ecol. Agric. 8, 1145–1150 (2016)
Donghe, L., Zhilin, S., Yuanyuan, Z.: Study on evaluation index system of Heilongjiang agricultural science and technology park. China Agric. Resour. Reg. 2, 79–83 (2016)
Ou, W., Wenliang, W.: Research on evaluation index system of China agricultural science and technology park. Agric. Tech. Econ. 4, 25–28 (2003)
Wang, B., Liu, P., Chao, Z., et al.: Research on hybrid model of garlic short-term price forecasting based on big data. CMC 57(2), 283–296 (2018)
Chen, W., Feng, G., Zhang, C., et al.: Development and application of big data platform for garlic industry chain. CMC 58(1), 229–248 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Huang, A., Zhang, C., Liu, P., Wang, J., Ren, W., Zheng, Y. (2019). Input-Output Analysis of Chinese National Agricultural Science and Technology Park. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11633. Springer, Cham. https://doi.org/10.1007/978-3-030-24265-7_44
Download citation
DOI: https://doi.org/10.1007/978-3-030-24265-7_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24264-0
Online ISBN: 978-3-030-24265-7
eBook Packages: Computer ScienceComputer Science (R0)