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A New Class of Production Function Model and Its Application

Author

Listed:
  • Cheng Maolin

    (School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou215009, China)

  • Jiang Zedi

    (School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou215009, China)

Abstract

Under some circumstances, the studies on economic growth theory can be translated into the researches on production function which will beneficial for the government to analyze the pattern of economic growth and then make reasonable policies. The commonly used production functions include C-D production function, CES production function, VES production function with different elasticity of substitution. This paper will put forward to a new class of production function which elasticity of substitution σ is a non-linear function of K/L. With this new model, a calculation formula for accurately measure the influence rates of various factors to economic growth will be derived, which is significant for in-depth studies on functions and scientific measurement. The empirical analysis on the influence rates of China’s economic growth factors and its good results will be presented in the end of this paper.

Suggested Citation

  • Cheng Maolin & Jiang Zedi, 2016. "A New Class of Production Function Model and Its Application," Journal of Systems Science and Information, De Gruyter, vol. 4(2), pages 177-185, April.
    • Handle: RePEc:bpj:jossai:v:4:y:2016:i:2:p:177-185:n:6
    DOI: 10.21078/JSSI-2016-177-09
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    References listed on IDEAS

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    1. Liqun Wang & Alexandre Leblanc, 2008. "Second-order nonlinear least squares estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 883-900, December.
    2. Dennis Epple & Brett Gordon & Holger Sieg, 2010. "A New Approach to Estimating the Production Function for Housing," American Economic Review, American Economic Association, vol. 100(3), pages 905-924, June.
    3. Martin van Ittersum & Ada Wossink, 2006. "Integrating Agronomic Principles into Production Function Specification: A Dichotomy of Growth Inputs and Facilitating Inputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 203-214.
    4. Eleanor Jawon Choi & Hyungsik Roger Moon & Geert Ridder, 2014. "Estimation of an Education Production Function under Random Assignment with Selection," American Economic Review, American Economic Association, vol. 104(5), pages 206-211, May.
    5. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    6. Timo Kuosmanen & Diemuth Pemsl & Justus Wesseler, 2006. "Specification and Estimation of Production Functions Involving Damage Control Inputs: A Two-Stage, Semiparametric Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(2), pages 499-511.
    7. Mundlak, Yair, 1996. "Production Function Estimation: Reviving the Primal," Econometrica, Econometric Society, vol. 64(2), pages 431-438, March.
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