The common production functions include the Leontief production function, the Cobb-Douglas (C-D) production function, the constant elasticity of substitution (CES) production function, the variable elasticity of substitution (VES) production function and so on. With different elasticity of substitution of factor, the production functions have different ranges of applications. In the production functions, the C-D production function is used the most widely because of its simple form, while the CES production function and the VES production function have limitations in applications due to their complicated forms. However, the C-D production function has the elasticity of substitution of factors of 1, and the CES production function has the elasticity of substitution of factors which is not 1 but a constant, so the two production functions both have limitations in applications. The VES production function with the variable elasticity of substitution is more practical in some application cases. This paper studies the applications of the VES production function model and gives a method of calculating the contribution rates of economic growth factors scientifically. As for the parameter estimation of the model, this paper gives an improved Sine Cosine Algorithm (SCA) to enhance the convergence rate and precision. Finally, the paper makes an empirical analysis on the contribution rates of economic growth factors of Shanghai City, China, using the method proposed.
Citation: Maolin Cheng, Bin Liu. A novel method for calculating the contribution rates of economic growth factors[J]. AIMS Mathematics, 2023, 8(8): 18339-18353. doi: 10.3934/math.2023932
The common production functions include the Leontief production function, the Cobb-Douglas (C-D) production function, the constant elasticity of substitution (CES) production function, the variable elasticity of substitution (VES) production function and so on. With different elasticity of substitution of factor, the production functions have different ranges of applications. In the production functions, the C-D production function is used the most widely because of its simple form, while the CES production function and the VES production function have limitations in applications due to their complicated forms. However, the C-D production function has the elasticity of substitution of factors of 1, and the CES production function has the elasticity of substitution of factors which is not 1 but a constant, so the two production functions both have limitations in applications. The VES production function with the variable elasticity of substitution is more practical in some application cases. This paper studies the applications of the VES production function model and gives a method of calculating the contribution rates of economic growth factors scientifically. As for the parameter estimation of the model, this paper gives an improved Sine Cosine Algorithm (SCA) to enhance the convergence rate and precision. Finally, the paper makes an empirical analysis on the contribution rates of economic growth factors of Shanghai City, China, using the method proposed.
[1] | R. F. Harrod, An essay in dynamic theory, Econ. J., 49 (1939), 14–33. https://doi.org/10.1080/00219444.1939.10772169 doi: 10.1080/00219444.1939.10772169 |
[2] | E. D. Domer, Capital expansion, rate of growth, and employment, Econometrica, 14 (1946), 137–147. https://doi.org/10.2307/1905364 doi: 10.2307/1905364 |
[3] | R. M. Solow, A contribution to the theory of economic growth, Q. J. Econ., 70 (1956), 65–94. https://doi.org/10.5652/kokusaikeizai.1956.70 doi: 10.5652/kokusaikeizai.1956.70 |
[4] | P. M. Romer, Increasing return and long-run growth, J. Polit. Econ., 94 (1986), 1002–1037. https://doi.org/10.1086/261420 doi: 10.1086/261420 |
[5] | L. E. Jones, R. Manuelli, A convex model of equilibrium growth: theory and policy implications, J. Polit. Econ., 98 (1990), 1008–1038. https://doi.org/10.1086/261717 doi: 10.1086/261717 |
[6] | L. Rivera-Batiz, P. M. Romer, Economic integration and endogenous growth, Q. J. Econ., 106 (1991), 531–555. https://doi.org/10.2307/2904800 doi: 10.2307/2904800 |
[7] | X. K. Ma, The evolution of research topics and methods on economics: from the classical economic growth theory to the new economic growth theory, J. Northwest Univ. (Philos. Soc. Sci. Ed.), 44 (2014), 51–57. https://doi.org/10.1145/2556647.2556656 doi: 10.1145/2556647.2556656 |
[8] | D. Y. Xie, Z. X. Zhou, The historical development and future challenges of economic growth theory: From the perspective of the evolution of production functions, Econ. Rev., 217 (2019), 30–39. |
[9] | X. L. Li, J. Li, Setting of production function in theories of economic growth and its application in China, Econ. Surv., 29 (2012), 1–6. |
[10] | M. L. Cheng, Y. Han, Application of a modified CES production function model based on improved PSO algorithm, Appl. Math. Comput., 387 (2020), 125178. https://doi.org/10.1016/j.amc.2020.125178 doi: 10.1016/j.amc.2020.125178 |
[11] | A. Matsumoto, F. Szidarovszky, Delay two-sector economic growth model with a Cobb–Douglas production function, Decis. Econ. Financ., 44 (2021), 341–358. https://doi.org/10.5771/2701-4193-2021-3-341 doi: 10.5771/2701-4193-2021-3-341 |
[12] | Y. Wei, M. H. Cao, An empirical study on rural economic growth in Hubei province based on new C-D production function, Asian Agr. Res., 8 (2016), 6–8. |
[13] | H. BAŞEĞMEZ, Estimation of Cobb-Douglas production function for developing countries, J. Res. Business, 6 (2021), 54–68. |
[14] | J. Wang, H. Song, Z. Tian, J. Bei, H. Zhang, B. Ye, et al., A method for estimating output elasticity of input factors in Cobb-Douglas production function and measuring agricultural technological progress, IEEE Access, 9 (2021), 26234–26250. https://doi.org/10.1109/ACCESS.2021.3056719 doi: 10.1109/ACCESS.2021.3056719 |
[15] | V. Kojić, A note on concavity conditions of Cobb–Douglas and CES production function with at least two inputs, Stud. Microecon., 9 (2021), 1–10. |
[16] | K. H. Choi, S. Shin, A canonical constant elasticity of substitution (CES) production function, J. Econ. Theory Economet., 32 (2021), 94–102. |
[17] | J. Biddle, The origins of the CES production function, Hist. Polit. Econ., 52 (2020), 621–652. https://doi.org/10.1215/00182702-8603973 doi: 10.1215/00182702-8603973 |
[18] | M. L. Cheng, A grey CES production function model and its application in Calculating the contribution rate of economic growth factors, Complexity, 2019 (2019), 5617061. https://doi.org/10.1155/2019/5617061 doi: 10.1155/2019/5617061 |
[19] | E. Lagomarsino, Estimating elasticities of substitution with nested CES production functions: Where do we stand?, Energy Econ., 88 (2020), 104752. https://doi.org/10.1016/j.eneco.2020.104752 doi: 10.1016/j.eneco.2020.104752 |
[20] | G. Meran, Thermodynamic constraints and the use of energy-dependent CES-production functions: A cautionary comment, Energy Econ., 81 (2019), 63–69. https://doi.org/10.1016/j.eneco.2019.03.009 doi: 10.1016/j.eneco.2019.03.009 |
[21] | H. Sasaki, The Solow growth model with a CES production function and declining population, Econ. Bull., 39 (2019), 1979–1988. |
[22] | K. Li, Z. Ding, Dynamic modeling and simulation of urban domestic water supply inputs based on VES production function, Mathematics, 10 (2022), 89. |
[23] | M. L. Cheng, B. Liu, Application of a modified VES production function model, J. Ind. Manag. Optim., 17 (2021), 2889–2902. |
[24] | F. Grassetti, C. Mammana, E. Michetti, Substitutability between production factors and growth: An analysis using VES production functions, Chaos Soliton. Fract., 113 (2018), 53–62. https://doi.org/10.1016/j.chaos.2018.04.012 doi: 10.1016/j.chaos.2018.04.012 |
[25] | M. Songur, F. E. Saraç, A general evaluation on estimates of Cobb-Douglas, CES, VES and Translog production functions, B. Econ. Theory Anal., 3 (2017), 235–278. |
[26] | D. Q. Zhu, L. Yang, The contribution rate of vocational education to rural revitalization-calculation and analysis based on the Cobb-Douglas production function, Mech. Res. Appl., 42 (2021), 112–125. https://doi.org/10.23919/SAIEE.2021.9513625 doi: 10.23919/SAIEE.2021.9513625 |
[27] | K. W. Wang, H. Y. Jiang, Q. Feng, Calculation of contribution of inland river shipping to economy in Hubei province based on production function, Water Transp. Manage., 40 (2018), 4–7. |
[28] | Z. H. Lv, L. Li, Y. H. Lu, The contribution analysis of technology input to wheat output of shandong province-based on extended C-D production function model, J. Anhui Agri. Sci., 44 (2016), 260–261. https://doi.org/10.1353/wsq.2016.0053 doi: 10.1353/wsq.2016.0053 |
[29] | M. L. Cheng, G. J. Shi, Y. Han, A modified CES production function model and its application in calculating the contribution rate of energy and other influencing factors to economic growth, J. Syst. Sci. Inf., 7 (2019), 161–172. |
[30] | Y. Wei, J. Gang, Empirical analysis about the contribution rate of science and technology progress to the economic growth in Sichuan construction industry, P. Twelfth Int. C. Manage. Sci. Eng. Manage., (2019), 1009–1015. |
[31] | Q. Zhang, Study on economy growth factor in Quanzhou city of fujian province based on C-D production function, Logistics Eng. Manage., 39 (2017), 146–148. https://doi.org/10.3366/olr.2017.0216 doi: 10.3366/olr.2017.0216 |
[32] | Z. Cheng, Z. X. Lu, Regression-based correction and I-PSO-based optimization of HMCVT's speed regulating characteristics for agricultural machinery, Agriculture, 12 (2022), 580. https://doi.org/10.3390/agriculture12050580 doi: 10.3390/agriculture12050580 |
[33] | M. L. Cheng, M. Y. Xiang, Application of a modified CES production function model based on improved firefly algorithm, J. Ind. Manag. Optim., 16 (2020), 1571–1584. https://doi.org/10.3934/jimo.2019018 doi: 10.3934/jimo.2019018 |
[34] | Z. Cheng, Z. X. Lu, Two novel reconstruction methods of sparsity adaptive adjustment for road roughness compressive signal based on I-SA and GSM, Mech. Syst. Signal Process., 16 (2020), 1571–1584. https://doi.org/10.1016/j.ymssp.2022.108915 doi: 10.1016/j.ymssp.2022.108915 |
[35] | S. Gupta, Enhanced sine cosine algorithm with crossover: A comparative study and empirical analysis, Expert Syst. Appl., 198 (2022), 116856. https://doi.org/10.1016/j.eswa.2022.116856 doi: 10.1016/j.eswa.2022.116856 |
[36] | H. Karmouni, M. Chouiekh, S. Motahhir, H. Qjidaa, M. O. Jamil, M. Sayyouri, Optimization and implementation of a photovoltaic pumping system using the sine–cosine algorithm, Eng. Appl. Artif. Intel., 114 (2022), 105104. https://doi.org/10.1016/j.engappai.2022.105104 doi: 10.1016/j.engappai.2022.105104 |
[37] | A. K. Saha, Multi-population-based adaptive sine cosine algorithm with modified mutualism strategy for global optimization, Knowl. Based Syst., 251 (2022), 109326. https://doi.org/10.1016/j.knosys.2022.109326 doi: 10.1016/j.knosys.2022.109326 |
[38] | R. J. Kuo, M. R. Setiawan, T. P. Q. Nguyen, Sequential clustering and classification using deep learning technique and multi-objective sine-cosine algorithm, Comput. Ind. Eng., 173 (2022), 108695. https://doi.org/10.1016/j.cie.2022.108695 doi: 10.1016/j.cie.2022.108695 |
[39] | S. Gupta, Y. Zhang, R. Su, Urban traffic light scheduling for pedestrian–vehicle mixed-flow networks using discrete sine–cosine algorithm and its variants, Appl. Soft Comput., 120 (2022), 108656. https://doi.org/10.1016/j.asoc.2022.108656 doi: 10.1016/j.asoc.2022.108656 |
[40] | T. Kuo, K. J. Wang, A hybrid k-prototypes clustering approach with improved sine-cosine algorithm for mixed-data classification, Comput. Ind. Eng., 169 (2022), 108164. https://doi.org/10.1016/j.cie.2022.108164 doi: 10.1016/j.cie.2022.108164 |
[41] | H. Ma, C. Zhang, T. Peng, M. S. Nazir, Y. Li, An integrated framework of gated recurrent unit based on improved sine cosine algorithm for photovoltaic power forecasting, Energy, 256 (2022), 124650. https://doi.org/10.1016/j.energy.2022.124650 doi: 10.1016/j.energy.2022.124650 |
[42] | X. Zhang, J. Jiang, H. Zheng, J. Zhang, Optimization scheme of integrated community energy utilization system based on improved sine-cosine algorithm, Energy Eng., 119 (2022), 1117–1140. https://doi.org/10.32604/ee.2022.017288 doi: 10.32604/ee.2022.017288 |