
Application of a New Superposition CES Production Function Model
Maolin CHENG, Yun HAN
Journal of Systems Science and Information ›› 2017, Vol. 5 ›› Issue (5) : 462-472.
Application of a New Superposition CES Production Function Model
In the analysis on economic growth factors, calculating the contribution rate of influencing factor to economic growth using the CES production function model is a common and important research field. The CES production function model has a variety of forms, and the superposition CES production function model proposed in the paper is a new model. With regard to the model's parameter estimation, the paper proposes a modified particle swarm optimization which has a fast convergence rate and a high precision. With regard to the calculation of factor contribution rate, the paper offers a new scientific calculation method with the superposition CES production function model. At last, the paper makes an empirical analysis on the contribution rate of Chinese economic growth factors and the result obtained consists with the reality.
production function / economic growth / particle swarm optimization / contribution rate of factor {{custom_keyword}} /
[1] Avvakumov S N, Kiselev Y N, Orlov M V, et al. Profit maximization problem for Cobb-Douglas and CES production functions. Computational Mathematics and Modeling, 2010, 21(3):336-378.
[2] Cheng M L. China forecasting model of economic growth based on production function. Statistics and Decision, 2010, 20:34-36.
[3] Zhu Q. The influence of R&D investment to economy growth. Scientific Management Research, 2009, 27(5):95-110.
[4] Gosciniak I. A new approach to particle swarm optimization algorithm. Expert Systems with Applications, 2015, 42(2):844-854.
[5] He G, Huang N J. A modified particle swarm optimization algorithm with applications. Applied Mathematics and Computation, 2012, 219(3):1053-1060.
[6] Indira K, Kanmani S. Association rule mining through adaptive parameter control in particle swarm optimization. Computational Statistics, 2015, 30(1):251-277.
[7] Liang X L, Li W F, Zhang Y, et al. An adaptive particle swarm optimization method based on clustering. Soft Computing, 2015, 19(2):431-448.
[8] Shieh H L, Kuo C C, Chiang C M. Modified particle swarm optimization algorithm with simulated annealing behavior and its numerical verification. Applied Mathematics and Computation, 2011, 218(8):4365-4383.
[9] Cheng M L. A new measure model of factor contribution ratio for economic growth. Mathematics in Economics, 2004, 21(3):235-239.
[10] Cheng M L. Correction and empirical analysis of the CES production function model. Journal of Engineering Mathematics, 2013, 30(4):535-544.
[11] Cheng M L, Han Y. The measure model and analysis of contribution ratio of economic growth factor on Suzhou foreign capital manufacturing. Application of Statistics and Management, 2009, 28(3):381-385.
[12] Yan M, Wang W G. Estimating the contribution rate of education investment in the economic growth based on time-varying parameter. Statistics & Information Forum, 2009, 24(7):72-78.
[13] Zhou S S, Hu D L. Research on contribution rate of science and technology progress to economy growth. China Soft Science, 2010, 2:34-39.
[14] Hang B L, Wang W R, Ding L Q. An expand application to the CES production function. Quantitative & Technica Economics, 1997, 8:52-55.
[15] Kemfert C. Estimated substitution elasticities of a nested CES production function approach for Germany. Energy Economics, 1998, 20:249-264.
[16] Kmenta J. On estimation of CES production function. International Economic Review, 1997, 8:180-189.
[17] Li Z N, Pang W Q. Econometrics. Beijing:Higher Education Press, 2010.
[18] Sun J S, Ma S Q. Econometrics. Beijing:Tsinghua University Press, 2004.
Supported by the National Natural Science Foundation of China (11401418), the National Statistical Research Program (2013LY133), Scientific Research Foundation of Suzhou University of Science and Technology (XKZ201309)
/
〈 |
|
〉 |