Application of differential evolution algorithm for solving the Solow model with the addition of human capital
DOI:
https://doi.org/10.26577/jmmcs-2018-2-406Кілттік сөздер:
economical model, inverse problems, optimization, differential evolution, Solow modelАннотация
This paper is devoted to a numerical study of defining of parameters of dynamical systems arising
in financial and economic problems. The importance of parameters that are difficult to measure is
great, so defining them will help to make forecasts and a work plan for the future at the governmental
level. An effective way to restore parameters is to solve the inverse problem. The method
of coefficient recovery using the algorithm of differential evolution, which was proposed by Rainer
Storn and Kenneth Price, is presented in this paper. On the example of solving the direct problem
of the mathematical model of neoclassical economic growth of Robert Solow and the results
obtained, the inverse problem was solved and unknown parameters were determined. The Solow
model is based on the Cobb-Douglas production function, taking into account labor, capital and
exogenous neutral technical progress. Also, for further calculations, the economic model proposed
by Mankiw-Romer-Weil based on the Solow model was considered, but with the addition of human
capital, where the number of variables and coefficients that need to be restored has already
increasing. A direct problem was also solved, results were obtained that were applied in the algorithm
of differential evolution for parameters recovery.
Библиографиялық сілтемелер
[2] Berndt E. R. and Christensen L. R., ”The Translog Function and the Substitution of Equipment, Structures, and Labor in U.S. manufacturing 1929–68.” Journal of Econometrics. 1 (1973): 81–113.
[3] Cobb C. W. and Douglas P. H., ”A Theory of Production.” American Economic Review. 18 (1928): 139–165.
[4] Douglas P. H., ”The Cobb-Douglas Production Function Once Again: Its History, Its Testing, and Some New Empirical
Values.” Journal of Political Economy. 84 (1976): 903–916.
[5] Durlauf S. N., Johnson P. A. and Temple J.R.W., ”Chapter 8 Growth Econometrics” Handbook of Economic Growth. 1 (2005): 555–677.
[6] Houthakker H. S., ”The Pareto Distribution and the Cobb–Douglas Production Function in Activity Analysis” The Review of Economic Studies. 23 (1955): 27–31.
[7] Storn R., Price K. and Lampinen R., Differential Evolution: A Practical Approach to Global Optimization. (Springer, 2005), 539 p.
[8] Mankiw G. N., Romer D. and Weil D. N., ”A Contribution to the Empirics of Economic Growth” The Quarterly Journal of Economics. 107 (1992): 407–437.
[9] Nazrul I., ”Growth Empirics: A Panel Data Approach” The Quarterly Journal of Economics. 110 (1995): 1127-1170.
[10] Solow R. M., ”A contribution to the theory of economic growth” Quarterly Journal of Economics. Oxford Journals. 70 (1956): 65–94.
[11] Storn R. and Price K., ”Differential Evolution — A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces.” Technical Report TR-95-012, ICSI. 95 (1995): 1–12.
[12] Storn R. and Price K., ”Differential Evolution — A Simple and Efficient Differential Evolution — A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces.” Journal of Global Optimization, ICSI. 11 (1997): 341–359.
[13] Swan T. W., ”Economic growth and capital accumulation.” Economic Record. Wiley. 32 (1956): 334–361.
[14] Temple J., ”The New Growth Evidence.” Journal of Economic Literature 37 (1999): 112–156.
[15] Yang XS., Nature-Inspired Optimization Algorithms. (Elsevier, 2014), 300 p.