ПРИМЕНЕНИЕ ПРОИЗВОДСТВЕННОЙ ФУНКЦИИ КОББА — ДУГЛАСА ДЛЯ АНАЛИЗА ПРОМЫШЛЕННОГО КОМПЛЕКСА РЕГИОНА
Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry

Summary/Abstract: The industry plays a key role in Russia’s economic security. Significant interregional gaps in the level of socio-economic development made topical the issue of optimizing the distribution of production forces in the constituent entities of the Russian Federation through increasing the efficiency of investment and industrial policy at the meso-level. In our opinion, the efficiency of such policy is impossible without modern methods of economic and mathematical modelling and information technologies. The Cobb-Douglas production function is still an adequate method for an accurate assessment of production capacities of the industry both in the whole country and it’s regions. At present, such method is being actively developed in two directions: the function’s modification through “saturation” with different factors and improvement of the approaches to determining its dynamic (changing in time) parameters. In this study, we hypothesized the possibility of building an adequate Cobb-Douglas production function with static and dynamic parameters, using the case of the Republic of Bashkortostan’s industry for the period from 2006 to 2016. The first hypothesis about using static parameters for building Cobb-Douglas production function was empirically rejected. In contrast, we have confirmed the second hypothesis. We defined dynamic parameters of the Cobb-Douglas production function using the alternative method of linear regression (AMLR). This method accurately assesses production capacities of the Republic of Bashkortostan. The choice of the method is not random. First of all, its use allows, in any case, ensuring a correct economic sign of parameters with factor indicators (labour and capital). Secondly, the original method of calculations, using the growth rates of the indicators, ensures high accuracy of verifying the model parameters. Thus, the conducted calculations have shown that the dynamics of the regular component explains 57.4 % of variance of the initial time series (remainder functions after defining the model parameters using the AMLR). Combined with other econometric methods, the application of the developed model will also enable an accurate forecast of the production capacities of the industry in regions. The study’s results can be applied for developing the investment and industrial policy of the Republic of Bashkortostan.

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