DEVELOPMENT OF THE REGION'S INDUSTRY IN THE CONDITIONS OF THE FORMATION OF AN INNOVATIVE ECONOMY OF TASHKENT REGION

Batirova Nilufar Sherkulovna

Date of publication: December 25, 2021 DOI: 10.52270/26585561_2021_12_14_101

Economical Sciences

DEVELOPMENT OF THE REGION'S INDUSTRY IN THE CONDITIONS OF THE FORMATION OF AN INNOVATIVE ECONOMY OF TASHKENT

REGION

Batirova, Nilufar Sherkulovna1

1PhD in Economics, Senior lecturer, International Islamic Academy of Uzbekistan, Tashkent,

Uzbekistan

Abstract

The article is devoted to the study of the influence of innovation and technological costs on the development of the region's industry. The purpose of this article is to calculate forecast indicators along with the study of the impact of costs on innovation and industrial development in the region. In addition, the Tashkent region differs from other regions in its priority characteristics. The efficiency of the innovation industry in the region is analyzed. Forecasts for the development of the region's industry for 2021-2030 are given taking into account the influence of a number of factors, in particular, the cost of innovation.

The step-by-step work carried out to achieve the forecast indicators was especially noted. In conclusion, many proposals were given for the development of a high-tech industry in the region.

Keywords: innovation, industry, region, forecast, investment, model.

I. INTRODUCTION

The transformation of the industry into one of the leading industries is considered to be a complex and constant process. At some degree most of the countries of the world can be called industrial. However, in order for a country to be considered "industrial", it is necessary that in the economy, in particular, in the structure of gross production and gross national product, there is a high contribution of industry, the possibility of applying advanced technologies to all production sectors. An important feature of the industrial complex is that in all its branches, means of labor and consumer goods are to be created, a significant part of the national income, scientific and technological progress is to be achieved.

One of the largest sectors of the economy of Uzbekistan is industry, which has more than a hundred sectors. In 2020, the volume of industry per capita amounted to 10,723.2 thousand soum. The industrial sector grew by 100.7 percent, as well as the volume of products amounted to 235.3 trillion. soum. In 2020, the industrial sector accounted for 27.4 percent of GDP (excluding construction). It indicates that due to result of the development of a market economy, the country's economy is developing towards an industrial economy.

101

II. METHODOLOGY AND DISCUSSION

The analysis of the research of the industrial complex of Tashkent region including its districts and cities showed that despite the fact that the current development of the industrial complex is extensive, the existing potential allows to produce high-tech products. It increases competitiveness in the industry. The current market-oriented management mechanism is aimed at generating income, which indicates the need to optimize and harmonize the process of development of the industrial complex, as well as the implementation of various projects in the industrial production industry. Therefore, it requires the need to develop a strategy for the development of the region's industry. The chronological data, comparative and quantitative methods, as well as statistical data were used in the article. Prediction, correlation, anticorrelation, as well as various tests were also used.

At determining the innovative way of development of industrial production in the region and the innovative development strategy, it is advisable to assess the resource capabilities of the region. The transformation of new scientific knowledge, ideas, discoveries, developments, as well as the improvement of existing technologies for the production of new products in accordance with market demand is an important issue in modern competitive conditions. At the same time, the industrial enterprises of the region should have an innovative potential to achieve innovative goals. In the scientific researches of A. Nikolaeva, innovation potential is considered as a system of factors and conditions necessary for the implementation of innovative processes [1, 25]]. The innovation opportunity of the region is assessed on the basis of an assessment of the innovation potential. In the works of such scientists as O.A.Romanova, F.V.Vazagova, V.I.Zinchenko, R.E.Preobrazhensky [2, 33], A.Lewis, R.Solow, A.Voltes, V.N.Gunin, V.P.Barancheev, N.P.Maslennikova, V.M.Mishin [3, 12], B.A.Begalov, H.T.Muhitdinov, A.Kenjabaev, the concept of innovation potential is described from the point of view of a systematic approach, and the degree of preparation for the implementation of an innovative program of strategic changes or a project is described as preparation for sustainable industrial production and innovation. These definitions show that innovation and investment costs and technologies have a special influence on the development of the region's industry.

III. RESULTS

The advantage of the current stage of economic development is the transition of the region's industry to an innovative way. This direction involves the formation of an effective management mechanism for industrial enterprises. Innovation-oriented industrial development increases economic efficiency and labor productivity, saves resources, as well as it ensures the competitiveness of local producers [5,124]. The investment and innovation way of development provides maximum growth rates based not only on the quantitative aspect of production, but also on the qualitative modernization of the technologies used [6, 58]. In all regions, economic reforms in the field of industry are aimed at creating complex high-tech types of production with the involvement of domestic and foreign investments. Additionally, one of the main tasks is determined by the orientation of foreign investments and advanced technologies to the implementation of industrial production based on high technological structural requirements. In recent years, a special attention has been paid to the development of scientific and technical cooperation with foreign countries, taking into account the growing pace of scientific and technical development of the republic and its regions. In order to ensure the growth of the level and efficiency of industrial production, the work is being carried out to expand import substitution sectors, increase export potential, develop basic industries, and increase the science-based share of industries. These processes are also observed in Tashkent region, which is considered one of the most important regions for the country. The basis of the region's economy is metallurgy, processing and food industry, as well as the cultivation of agricultural products. Also, the industry of production of building materials is developing rapidly. According to our calculations, the macroeconomic indicators of the region, namely the value of GDP, industry, agriculture and investments per capita, the change compared to the previous period is higher than the indicators of the republic,

102

as well as the change compared to the previous period is higher than the indicators of the republic and the high proportion of these indicators in the republic reflects the priority of the region. That is why this region continues to occupy one of the leading places in the republic according to the main macroeconomic indicators. The gross regional product (GRP) of the region is 10.8 percent of the gross domestic product of the country and 21113.1 thousand soum per capita. This figure is 124.6 percent of the national average. The share of industry in the GRP structure is increasing. Its share remains at a high level, its share is higher than the country's share in GDP (up to 20.5 percent). Also, according to calculations, the region will produce 10.0 percent of all agricultural products of the republic [7, 24].

Along with the implementation of the directions of development of the industrial complex of the region, it seems appropriate to forecast the production volumes of the industrial sectors of the region for 2021-2030. It embodies several requirements, such as forecasting and the right choice of factors affecting it. As variables, we chose the factor of industrial production in the region, investment, the number of jobs in the industry and the cost of technological innovation. In this case, the indicators from 2000 to 2019 were selected [8, 25].

Table 1

Visual statistics of variables to be included in the model

Variable Average Standard deviation Minimum

Production of industrial products, billion soum 10141,74 13762,02 310,4

Investments, billion soum 3162,24 4887,995 60,5

Number of employed people in the industry, thousand people 218.40 29,88 170

Costs of technological innovations, million soum 258890,4 284837,4 26112

As it can be seen from the Table 1, the standard deviation of all variables is greater than the average. Thus, we can conclude that the volatility of variables remains at a high level over time. According to correlation between the volume of industrial production, the volume of investments as well as the costs of technological innovations in the Tashkent region, we see a strong correlation between the production of industrial products and investments. This conclusion can also be supported by the result of the correlation table in the Table No.2. It indicates, that the correlation ratio is 0.988. It implies that there is a very strong connection. Also, there is a relatively strong correlation between industrial production and the number of employed people in the industry (the correlation ratio is 0.741).

Table 2

Correlation matrix between the volume of industrial production in Tashkent region, the volume of investments and the costs of technological innovations

Production of industrial products, billion soum Investments, billion soum Number of employed people in the industry, thousand people Costs of technological innovations, million soum

Production of industrial products, billion soum 1 Producti on of industria l products , billion soum

Investments, billion soum 0.988 1 Investme nts, billion soum

Number of employed people in the industry 0.741 0.682 1 Number of employe d people in the industry

Costs of technological innovations, million soum 0.928 0.887 0.777 1 Costs of technolo gical innovati ons, million soum

Overall, there is a strong relationship between all the variables included in this model. The fact that the lowest correlation indicator is 0.682 which proves it.

Table 3

The results of the analysis of factors affecting the volume of industrial production

Source SS Df MS Number of obs. = 20

Model 3.56*109 3 1.18*109 F(3,16) = 554.3

Residual 34279203.5 16 2142450.22 Prob>F = 0.000

Total 3.59*109 19 1.89*108 Adj. R-squared = 0.989

Coef. Std. err. T P>|t| 95 % Conf. Interval

104

h 2.187 0.149 14.70 0.000 1.871 2.502

29.21 17.836 1.64 0.121 -8.604 67.017

0.009 0.003 3.09 0.007 0.003 0.015

Cons. -5524.103 3547.088 -1.56 0.139 -13043.59 1995.39

Note: It was calculated, using the STATA 16 program. The table uses the following abbreviations for variables: It- investment volume, billion soum, Bt- the number of people employed in industry, thousand people, technological and innovative costs, million soum

The results of the regression equation reflecting investments in the volume of industrial production in Tashkent region, the number of employed people in the industry, as well as the impact of technological and innovative costs are shown in the Table 3. Whereas, overall, the equation is statistically significant at the significance level of 5 percent, since the p-value of the F-statistics is less than 0.05. In addition, the impact of investments, as well as technological and innovative costs on industrial production is also statistically significant at the level of 5 percent. By virtue of both variables are less than 0.05 p-values of t-statistics. However, despite this, we have to leave this variable in the model. Because, the lack of statistical significance can be affected by multicollinearity between independent variables. And in relatively small samples, multicollinearity cannot be eliminated. In addition, the number of employed people in the industry is an important factor affecting the volume of industrial production [9, 36]. Whereas a multifactorial analysis was given, we will use the modified coefficient of determination. The coefficient of changeable determination is 0.989. Consequently, the obtained independent variables illustrate 98.9 percent of the change in the interrelated variable. Considering that the data used in this analysis was a set of temporary data, an autocorrelation problem may have been observed here. Hence, we check for autocorrelation using the Breusch-Godfrey test. According to the results of the Breusch-Godfrey given in Table 4, there is an autocorrelation in the regression equation given in Table 3. Because, in the Breusch-Godfrey test, the null hypothesis states that there is no autocorrelation, while in the square of x(i), the value of p is less than 0.05. Therefore, we reject this null hypothesis [10, 45].

It was calculated using the STATA 16 program. The results of the Breusch-Godfrey test.

Breusch-Godfrey LM test for autocorrelation

lags(p) chi2 df Prob > chi2

1 7.965 1 0.0048

H0: no serial correlation

20000 40000 60000

Fitted values

Figure 1. Dot diagram of excess and theoretical values

105

The results of the dot diagram in the Figure 1 also indicate the presence of autocorrelation. Because the excess and the points denoting the theoretical values of the associated variable corresponding to them are distributed unevenly around zero.

Based on the data in the Figure 1, we can conclude that there is an autocorrelation. In this regard, we need to use a method of testing hypotheses resistant to autocorrelation. In this analysis, we use Newey-West standard Errors.

Table 4

Calculated using Newey-West standard Errors

Regression with Newey-West standard Errors Number of obs= 20

maximum lag: 1 F( 3,16)= 1161.03

Prob >F= 0.0000

Coef. Std. Err. T P>t [95% Conf. Interval]

h 2.187125 .1671037 13.09 0.000 1.832881 2.541369

Tt 0.009159 .0037373 2.45 0.026 .0012359 0.0170811

29.20627 26.80926 1.09 0.292 -27.62682 86.03935

Cons. -5524.103 5074.679 -1.09 0.292 -16281.94 5233.735

If we pay attention to the data in Table 4, the regression equation calculated using the Newey-West method is generally statistically significant at the significance level of 5 percent, since the p-value of the F-statistics is less than 0.05. In addition, the impact of investments, as well as technological and innovative costs on the production of industrial products is also statistically significant at the level of 5 percent. Only the influence of the number of employed people in the industry on the production of industrial products is not statistically significant even at 5 percent and 10 percent levels of significance. [11, 33].

Figure 1 illustrates a histogram of the excess of the regression equation, which clearly shows that the distribution of excess is close to the ideal normal distribution. Based on the data in Tables 3 and 4, we compile the following regression equation:

= -55Z4 :: - : ::::". (1)

From equation 1, it can be concluded that the average increase in the annual volume of investments by one billion soum contributes to an average increase in industrial production by 2.19 billion soum. The increase in the number of employed on average per thousand people led to an increase in industrial production by an average of 29.21 billion soum. An increase in technological investments by one million soum will increase the volume of industrial production by an average of 0.001 billion. soum. Using equation 1, we will make a forecast of industrial production for 2021-2030. To do this, we need to develop forecast scenarios.

106

Table 5

Description of the average growth rates of independent variables for inertial, optimistic and pessimistic scenarios obtained for the development of forecast indicators of industrial production in

Tashkent region in 2021-2030

Forecast scenario Dynamics of independent variables in forecast scenarios

Inertial scenario It is identified that the average growth rates of investments will make 8.9 percent, the average growth rate of employed population in industry will be 1.2 percent, as well as the growth rate of innovation and technological costs will average 12.3 percent.

Optimistic scenario It is provided that the average growth rates of investments will be 12.7 percent, the average growth rate of the employed population in industry will be 1.1 percent, and the growth rate of costs for innovation and technology will average 16.2 percent.

Pessimistic scenario It is stipulated that the average growth rates of investments will be 5.7 percent, the average growth rate of the employed population in industry will be 1.0 percent, and the growth rate of costs for innovation and technology will average 6.6 percent.

The scenarios developed in the Table 5 were based on the dynamics of independent variables in the model in 2000-2020, as well as the regression equation given in Equation 1. At the same time, the scenarios vary mainly depending on the growth rates of investments and the costs of technological innovations. That is, the optimistic scenario assumes a more active investment policy than the main and pessimistic scenario, as well as a rapid (by 16.2 percent) increase in innovation costs.

Table 6

Forecasts of the main, optimistic and pessimistic scenarios for 2021-2030 indicators of industrial

production of Tashkent region (billion soum)

Years The main scenario Optimistic scenario Pessimistic scenario

2021 (forecast) 77488,70358 72419,2201 63218,07533

2022 (forecast) 89648,76629 88653,02271 71167,21062

2023 (forecast) 101609,0511 105808,8771 79044,49812

2024 (forecast) 114527,9194 123620,0233 87382,88654

2025 (forecast) 128213,1705 143772,1361 95728,6019

2026 (forecast) 143101,1411 168656,8823 104404,6505

2027 (forecast) 158551,5088 195244,9995 113339,7092

2028 (forecast) 175107,4105 226068,1695 123086,747

2029 (forecast) 192637,6523 257349,6871 133618,1812

2030 (forecast) 210160,7087 289116,7908 143712,4532

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

Table 6 and Figure 1 show forecasts of industrial production in Tashkent region for 2021-2030. Additionally, we see that the volume of industrial production, calculated according to an optimistic scenario and a pessimistic scenario, will almost double by 2030. That is, by 2030, according to an optimistic scenario, the production of industrial products in the amount of 289116.8 billion soum is expected, while according to the pessimistic scenario, it is expected that this figure will reach 143712.5 billion. soum.

107

350000 300000 250000 200000 150000 100000 50000 0

2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Figure 2. Forecasts of the main, optimistic and pessimistic scenarios of industrial production volumes of Tashkent region for 2021-2030

The description of forecast scenarios in Table 5 and the analysis of forecast values in Table 6 empirically confirm that the development of technological innovations and innovations in the further development of industrial production in Tashkent region, as well as an active investment policy by 2030 will contribute to a doubling of results compared to the pessimistic scenario.

IV. CONCLUSION

In summary, the main engine of the development of the industrial sector in Tashkent region is the introduction of innovative technologies into the economy of the region and further active investment policy at the regional level.

Achieving this goal requires the gradual development of the region's industry. In our opinion, at the same time, it is necessary to divide the industry into 2 main stages of innovative development. The first stage involves solving a number of priority tasks. Successful implementation of this stage will allow to stabilize the situation in the industrial complex of the region, industrial clusters will be created aimed at the production of new high-tech products. Achieving strategic goals aimed at the formation of a high-tech industrial complex based on the use of the innovative potential of the region requires a differentiated approach in choosing priority areas of industrial policy for different regions of the region, developing the production of competitive industrial products, creating favorable conditions for environmental and social development.

The main part of the technological modernization strategy should include a number of important programs aimed at the formation of sectoral programs for the formation of high-tech and new industrial sectors, the development of basic industries. The planning process alone cannot ensure sustainable economic growth. Most regions have already developed their own socio-economic development strategies. It indicates that the main efforts of regional government bodies, business communities, and the expert community should be aimed at ensuring the implementation of the developed strategies for the socio-economic development of the regions. Otherwise, the process of innovative development of the region's industry can only become formal.

The second stage is characterized by the consistent development of the industrial complex of the region and the constant growth of industrial production. In the framework of this stage, the active development of hightech production will continue, production clusters and innovatively active enterprises will be formed. The investment attractiveness of all branches of the industrial complex of the region will increase, the innovative infrastructure of regional production will be actively developed. To do this, the development of high-tech production at industrial enterprises in the region should be identified as the main priority.

The proposed group of measures provides an opportunity to support structural changes in industrial production, implement scientific, technical and innovative policies aimed at mastering the production of competitive high-tech products in the region, and introduce them into the production of advanced technologies

[13]. This, in turn, imposes an obligation on the region to perform several tasks. Clearly defined directions of development of the industrial complex in the region should be implemented not only in cities specializing in industry, but also in areas specializing in agriculture, including Yangiyul, Angren, Bekabad, Buka, Ahangaran, Akkurgan, Parkent, Pskent, Chinaz, Kuyuchirchik, Kibray, Yukorichirchik and Yangiyul district.

Based on the above, first of all, it is necessary to develop industrial production in the region. In order to coordinate innovation activities based on a project-based approach to the development of high-tech industrial production, the need to develop innovative infrastructure in production requires the implementation of works supported by the governing bodies of the region, namely:

- financing of scientific research, development and technological works, financing of the activities of infrastructure entities;

- execution of the state order for the purchase of products according to the list of regional priority projects;

- the introduction of subsidies for the implementation of priority projects and organizational measures, the provision of incentives to subjects engaged in innovative activities, as well as subjects of industrial innovation infrastructure for taxes and customs duties and other payments;

- to act as a guarantor to creditors on the obligations of companies engaged in innovative activities and subjects of industrial innovation infrastructure;

- ensuring the inflow of investments into priority sectors of the economy;

- increasing the investment attractiveness of the regions;

- creating an institutional framework for sustainable economic growth;

- conducting an effective regional industrial policy;

- creation of various centers that contribute to the development of the region's industry.

REFERENCE LIST

Audretsch D. B. (1995). Innovation and industry evolution. Mit Press.

Barancheev V. P., Maslennikova, N. P., & Mishin, V. M. (2015). Innovation management. Pp. 124-125.

Batirova N. S. (2019). ANALYSIS OF THE INNOVATIVE LEVEL OF INDUSTRY IN THE TASHKENT REGION. Economics and Finance Vol. 12. Pp. 47-70. doi.org/10.34920/ivm.12.2019.63-70

Batirova, Nilufar Sherkulovna (2021) "Measures to Stabilize the Socio-Economic Development of Regions in a Pandemic (on the Example of the Industrial Complex of the Tashkent Region)" Journal «Bulletin Social-Economic and Humanitarian Research», Vol 9. Number 11 Pp. 2 - 14. doi: 10.5281/zenodo.4263353

Bergman, E.M. (2000). National industry cluster emplates: a framework for applied regional cluster analysis. Regional Studies. Vol. 34 (1). Pp. 1-19.

Block, F. (2015). Innovation and the invisible hand of government. In State of innovation. Pp. 9-34.

Hâkansson, H., & Waluszewski, A. (Eds.). (2007). Knowledge and innovation in business and industry: The importance of using others. Vol. 5.

Hertz R. (2010). Innovation policy presupposes an innovative enterprise. Element, Vol. 2. P. 62-71.

Kolmakov V. V. and Polyakova, A. G. Karpova, S. V. and Golovina, A. N. (2019). Cluster development based on competitive specialization of regions. Economy of Region, Vol. 15. Pp. 270-284. doi: 10.17059/20191-21.

109

Maslennikov M. I. (2017). The technological innovations and their impact on the economy. Economy of Region. Vol. 4. Pp. 1221-1225. doi: 10.17059/2017-4-20.

Neganova V. P. and Dudnik, A. V. (2019). Openness to innovations of the regional agro-industry as a subjective factor of innovative activity. Economy of Region. Vol. 15. Pp. 880-892. doi: 10.17059/2019-3-19.

Soluttseva, S. (2020) Socio-economic problems of the region. The economy of the region. Vol. 1. Pp. 2842.

Rjapuhina V. N., & Zarkovic A. V. (2015). Problem formiranja inovacione kulture kao faktora pozitivne inovacione klime-uloga obrazovanja. Godisnjak Uciteljskog fakulteta u Vranju, Vol. 6. Pp. 435-448.

Rodrik D. (2010). The return of industrial policy. project Syndicate. 12.

Romanova O.A. (2018) Priorities of Russia's Industrial Policy in the context of the Challenges of the Fourth Industrial Revolution. The economy of the region. Vol. 14. Pp. 806-819.

Soluttseva S.N. (2020) An innovative way to change the trajectory of the previous development of the region's economy. Economy of the region. Vol. 16. Pp. 28-42.

Traill W. B., & Meulenberg, M. (2002). Innovation in the food industry. Agribusiness: an International Journal. 18(1). Pp. 1-21.

Utterback, J. M. (1974). Innovation in industry and the diffusion of technology. Science. Vol. 183(4125). Pp. 620-626.

Vazagova F.V., Kilchukov Z.H. (2015) The role of the branches of the industrial complex in the implementation of a new model of economic development. Fundamental research. Pp. 343-346.

Zavadskiy M. (2010). Kak eto sdelali na Tayvane. Ekspert. Vol. 36 (720). Pp. 66-68.

Zinchenko V.I. (2009) Regional Innovation Monitoring system. Innovations. P. 27.

110

РАЗВИТИЕ ПРОМЫШЛЕННОСТИ РЕГИОНА В УСЛОВИЯХ ФОРМИРОВАНИЯ ИННОВАЦИОННОЙ ЭКОНОМИКИ ТАШКЕНТСКОЙ

ОБЛАСТИ

Батирова Нилуфар Шеркуловна1

1PhD in Economics, старший преподаватель, Международная исламская академия Узбекистана, Ташкент, Узбекистан

Аннотация

Статья посвящена исследованию влияния инновационных и технологических затрат на развитие промышленности региона. Целью данной статьи является расчет прогнозных показателей наряду с исследованием влияния затрат на инновации и развитие промышленности в регионе. Кроме того, Ташкентская область отличается от других регионов своими приоритетными характеристиками. Проанализирована эффективность инновационной отрасли в регионе. Прогнозы развития промышленности региона на 2021-2030 годы даны с учетом влияния ряда факторов, в частности затрат на инновации.

Особо отмечена поэтапная работа, проводимая для достижения прогнозных показателей. В заключении было дано множество предложений по развитию высокотехнологичной индустрии в регионе.

Ключевые слова: инновация, отрасль, регион, прогноз, инвестиции, модель.

СПИСОК ЛИТЕРАТУРЫ