Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry

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 eff...

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Main Authors: Nikolay Vladimirovich Suvorov, Rustem Rinatovich Akhunov, Roman Vladimirovich Gubarev, Evgeniy Ivanovich Dzyuba, Fanil’ Saitovich Fayzullin
Format: Article
Language:English
Published: Russian Academy of Sciences, Institute of Economics of the Ural Branch 2020-03-01
Series:Экономика региона
Subjects:
Online Access:https://www.economyofregion.com/data/jarticles/3255.pdf
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author Nikolay Vladimirovich Suvorov
Rustem Rinatovich Akhunov
Roman Vladimirovich Gubarev
Evgeniy Ivanovich Dzyuba
Fanil’ Saitovich Fayzullin
author_facet Nikolay Vladimirovich Suvorov
Rustem Rinatovich Akhunov
Roman Vladimirovich Gubarev
Evgeniy Ivanovich Dzyuba
Fanil’ Saitovich Fayzullin
author_sort Nikolay Vladimirovich Suvorov
collection DOAJ
description 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 mode l parameter s using the AMLR) . Combine d 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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spelling doaj.art-a2931b2a0eeb4c35acdd922cf34499772023-08-02T01:46:49ZengRussian Academy of Sciences, Institute of Economics of the Ural BranchЭкономика региона2072-64142411-14062020-03-01161187200https://doi.org/10.17059/2020-1-14Applying the Cobb-Douglas Production Function for Analysing the Region’s IndustryNikolay Vladimirovich Suvorov0Rustem Rinatovich Akhunov1Roman Vladimirovich Gubarev2Evgeniy Ivanovich Dzyuba3Fanil’ Saitovich Fayzullin4Institute of Economic Forecasting of RASUfa Federal Research Center of RAS Plekhanov Russian University of Economics Division of All-Russia People’s Front in Republic of BashkortostanInstitute of Social and Economic Research of the Ufa Federal Research Center of RAS 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 mode l parameter s using the AMLR) . Combine d 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.https://www.economyofregion.com/data/jarticles/3255.pdfrussian regionindustryassessment of production capacitiescobb-douglas production functionlabourcapitalgrowth ratesstatic and dynamic parametersalternative method of linear regressiontime seriesregular and random
spellingShingle Nikolay Vladimirovich Suvorov
Rustem Rinatovich Akhunov
Roman Vladimirovich Gubarev
Evgeniy Ivanovich Dzyuba
Fanil’ Saitovich Fayzullin
Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
Экономика региона
russian region
industry
assessment of production capacities
cobb-douglas production function
labour
capital
growth rates
static and dynamic parameters
alternative method of linear regression
time series
regular and random
title Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
title_full Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
title_fullStr Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
title_full_unstemmed Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
title_short Applying the Cobb-Douglas Production Function for Analysing the Region’s Industry
title_sort applying the cobb douglas production function for analysing the region s industry
topic russian region
industry
assessment of production capacities
cobb-douglas production function
labour
capital
growth rates
static and dynamic parameters
alternative method of linear regression
time series
regular and random
url https://www.economyofregion.com/data/jarticles/3255.pdf
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