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7ASSESSMENT OF THE iMPACT OF ECONOMiC GROWTH IN THE PTOCESSING
INDUSTRY IN AZERBAIJAN Tagiyeva T.A. (Republic of Azerbaijan) Email: Tagiyeva250@scientifictext.ru
Tagiyeva Turan Aliaga gizi - doctoral Student, AZERBAIJAN STATE UNIVERSITY OIL AND INDUSTRY, BAKU, REPUBLIC OF AZERBAIJAN
Abstract: the article examines the influence of commercial products in the processing industry of the Republic of Azerbaijan and investments in fixed assets on economic growth. Using the EVievs software package, a regression equation was established between these indicators and the impact of the industrial sector on GDP was estimated. As a result, it was estimated by the econometric method the ways of constructing the regression equation between the indicators and checking the adequacy of the model.
Keywords: software package. value added, correlation, regression, investment, elasticity coefficient, fixed capital, gross domestic product.
ОЦЕНКА ВЛИЯНИЯ ЭКОНОМИЧЕСКОГО РОСТА ПЕРЕРАБАТЫВАЮЩЕЙ ПРОМЫШЛЕННОСТИ В АЗЕРБАЙДЖАНЕ Тагиева Т.А. (Азербайджанская Республика)
Тагиева Туран Алиага кызы - докторант, Азербайджанский государственный университет нефти и промышленности, г. Баку, Азербайджанская Республика
Аннотация: в статье исследуется влияние товарный продукци в перерабатывающей промышленности Азербайджанской Республики и инвестиций в основной капитал на экономический рост. С помощью программного пакета EVievs было установлено уравнение регрессии между этими показателями и оценено влияние промышленного сектора на ВВП. В результате было оценено эконометрическим методом пути построения уравнения регрессии между показателями и проверки адекватности модели. Ключевые слова: пакет программного обеспечения, добавленная стоимость, корреляция, регрессия, инвестиции, коэффициент эластичности, основной капитал, валовой внутренний продукт.
UDC 338. 24. 01.
Introduction. Sustainable, dynamic and stable development of countries in a globalized world economy is based on their well-thought-out strategy for the future. Research shows that the Buffett Ratio, which is the ratio of the capitalization of global companies to GDP, has already reached its highest point. The basis of the strategy of capitalization of enterprises in the world economy is determined by ensuring the financial stability of enterprises operating in each country. The implementation of large-scale energy projects in the socio-economic life of Azerbaijan in recent years has further increased the economic power of our country. The development of the liberal economic system established in the republic ensured the dynamic development of the country's economy, regulating the development of entrepreneurship and creating conditions for increasing the competitiveness of local products. The creation of modern production facilities in the country that meet international standards and the improvement of the production infrastructure have created a transition to a new stage in the development of industry, including processing industry [2, p. 4].
Main part. The added value created by economic activity regulates economic growth in a country and leads to an increase in GDP. Since the economy of Azerbaijan is based on oil and gas production, it is important to assess the impact of the added value of oil refineries on GDP. Economic growth policy is directly related to the increase in the volume of work and services in all sectors of the economy. The development of industry, which occupies a high share in the economy of Azerbaijan, including the processing industry, has laid a solid foundation for the development of all sectors of the economy. The development of the processing industry due to the successful economic reforms carried out in our country has led to an increase in GDP due to an increase in value added through investments in this area. This can be seen more clearly in the diagram below [5].
14 12 10
..............
90 80 70 60 50 40 30 20 10
0 Mm Mm Mm Mm Mm Mm Mm Mm Mm Mm Mm Mm Mm Mm 0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
1 Investment in fixed assets in industry
" Manufacturing output
Gross Domestic Product
4.3 4,6 4,2 3,2 4,3 5,4 6 7,5 7,6 8,5 9,9 10,6 8,5 9,3
4.4 4,9 5,6 4,83 5,7 6,3 6,97 7,2 8,3 7,8 8,8 9,6 10,3 11,8 15,6 22,5 24,1 25,8 27,8 30,6 34,2 38,5 44,4 51,7 61,3 70,1 80,1 81,7
Fig. 1. Income from the manufacturing industry in the Republic of Azerbaijan for 2006-2019, investments in fixed assets and the volume of GDP, billion in manats Source: Compiled by the author based on (5)
As can be seen from the graph, the volume of investments in fixed assets in the industrial sector was observed with an increasing dynamic in 2006-2017, but in subsequent years it decreased and in 2019 amounted to 9.3 billion manat. This is 12.3% or 1.3 billion manat less than in 2017. The increase in investment in fixed assets has led to an increase in value added in the manufacturing industry. As can be seen from Figure 1, production in the manufacturing industry increased over all the periods studied. In this regard, an econometric assessment of the impact of value added on GDP in the manufacturing industry is important. If we use the EViews software package for this purpose, we get the following result based on the data in Figure 1.
Table 1. The result of the EViews software package
Dependent Variable: Y
Method: Least Squares
Date: 08/04/21 Time: 13:13
Sample: 2006 2019
Included observations: 14
Variable Coefficient Std. Error t-Statistic Prob.
X2 8.693609 1.437015 6.049770 0.0001
X1 0.957890 1.321166 0.725034 0.4836
C -26.61721 5.009948 -5.312871 0.0002
R-squared 0.951877 Mean dependent var 43.45714
Adjusted R-squared 0.943127 S.D. dependent var 22.05705
S.E. of regression 5.260177 Akaike info criterion 6.345616
Sum squared resid 304.3641 Schwarz criterion 6.482557
Log likelihood -41.41931 Hannan-Quinn criter. 6.332940
F-statistic 108.7898 Durbin-Watson stat 1.609784
Prob(F-statistic) 0.000000
Source: Eviews application was developed by the author based on the software package.
Based on the results obtained from the EViews application software package, the regression equation will be as follows:
Estimation Command:
LS Y X2 X1 C
Estimation Equation:
Y = C(1)*X2 + C(2)*X1 + C(3) Substituted Coefficients:
Y = 8.69360942989*X2 + 0.95789035517*X1 - 26.6172050653 (1)
According to the Eviews application suite, the covariance between the free variables included in model (1) and the dependent variable will be as follows:
Table 2. Covariance matrix
X2 X1 Y
X2 4.63381224489796 4.489561224489795 44.5850612244898
X1 4.489561224489795 5.482091836734694 44.28173469387755
Y 44.5850612244898 44.28173469387755 451.7624489795918
Source: Eviews application was developed by the author based on the software package.
Between the variables Y and X as shown in the Eviews application software package Y = 0.9579 * X1 + 8.6936 * X2 - 26.617 expressed by the model has a high correlation (R2=0.952). This means that, according to the Chaddock scale, the qualitative characteristic of the strength of dependence is high due to the fact that the quantitative value of the contact density is in the range of 0.7-0.9 [4, p.136].
Since it is important to check the adequacy of the established model, this adequacy can be defined as one of the traditional methods using the Fisher criterion. To check the statistical significance of the model (1), which expresses the regression equation as a whole, the F-Fisher test must be compared with the value Ftab \ e (a; m ; n — m — 1 ) [3, p. 332]. According to Table 1, which reflects the results of the EViews software package, F-statistic (Fisher's test) = 108.8
If we set the value of table F to EXCEL by the formula F_table (a; m; n-m-1) = Fraspobr,
Stable (a; m; n - m - 1) = F(0.05; 2; 11) = 9.4 When the F-Fisher test is compared with the Ftab j e valu e (a; m ; n — m — 1 ) , it turns out that the F-Fi§er test > . This means that the regression equation as a whole is statistically significant, and model (1) is
an adequate model.
The autocorrelation result in the model can be determined based on the Darbon-Watson statistics in Table 1 obtained from the EViews application suite. As you can see from the table, DW is 1.6098. In this case, the points of the Darbon-Watson crisis for observing 2 explanatory variables m = 2 and n = 14 up to the significance level a = 0.05 will be as follows [3, p. 337].
dt = 0,905, du = 1,551 du = 1,551 < DW = 1,6098 <4 - du = 2,449 there is no autocorrelation [4, p.171]. This means that the regression equation as a whole is statistically significant, and the constructed model Y = 0.9579 * X1 + 8.6936 * X2 - 26.617 is an adequate model.
The following graph shows the annual estimates and standard errors of GDP determined by the regression equation obtained from the EViews application suite, as well as a number of characteristics of the use of the equation for forecasting purposes.
Forecast: YF Actual: Y
Forecast sample: 2006 2019 Included observations: 14
Root Mean Squared Error 4.662649
Mean Absolute Error 3.807134
Mean Abs. Percent Error 9.520483
Theil Inequality Coefficient 0.048304
Bias Proportion 0.000000
Variance Proportion 0.012329
Covariance Proportion 0.987671
06 07 08 09 1 0
13 14 15 16
YF ± 2 S.E.
Fig. 2. Characteristics of UDM in the Republic of Azerbaijan for forecasting. Source: EViews application was developed by
the author based on the software package
It should be noted that with the help of the graph, it is possible to determine the forecasted prices of GDP in the Republic of Azerbaijan, as well as the income of processing enterprises by year.
As a result of the study, it is possible to determine the percentage change in the outcome factor by calculating the elasticity coefficient, which represents the percentage change in the dependent variable as a result of a 1% increase in the free variables included in the linear regression equation. This ratio is calculated according to the following formula [3, 137].
a, x x,
E = _ (2)
y
Here are the coefficients of the above contact equation. -is the calculated average value of the income of processing enterprises and the volume of investments in fixed assets for the study periods, is the calculated average value of GDP in the Republic of Azerbaijan for the study periods. The elasticity coefficients calculated on the basis of these indicators for the constructed model will be as follows.
oqxx7 0,9579 x 2709,721 ~ -=0,1398
D/or investments in fixed asset
y
43,457
0C4XX^
8,6936 X 7,3214
c/or commodity products intUe processing industry
= 1,465
y 43,457
Calculations show that an increase in investment in fixed assets by 1% in the Republic of Azerbaijan leads to an increase in GDP by 0.14%, to an increase in the output of the manufacturing industry by 1%, to an increase in GDP by 1.465%.
The graph of incomes in the manufacturing industry of the Republic of Azerbaijan for 2006-2019, investments in fixed assets and dynamic changes in GDP is as follows.
90 80 70 60 50 40 30
20 10 0
EI
rri
Xn
id
id
id
id
id
id
id
Id
06 07 08 09 10 11 12 13 14 15
17 18 19
I I X2 X1 Y
Fig. 3. Income from the manufacturing industry in the Republic of Azerbaijan for 2006-2019, investments in fixed assets and
dynamics of changes in GDP
Source: EViews application was developed by the author based on the software package.
80
40
0
According to the EViews software package, the multiplicity correlation coefficient R2 = 0.943 according to Table 1 shows a high correlation between the dependent variable Y, which represents the volume of GDP in the Republic of Azerbaijan, and the free variables (X1 and X2). The fact that R2 = 0.943 means that the corresponding regression equation is explained by 94.3% of the variance results and 5.7% by other factors. A high coefficient of determination indicates that the regression equation is well expressed in the original data and that most of the resulting factor (94.3%) is explained by the factors included in the model.
The dynamics of the fitted and actual values, as well as the residuals between them, according to the regression equation of the established model (1) and the EViews application package, is presented in the graph below.
I_Residual - Actual - Fitted |
Fig. 4. Dynamics of actual values and residuals obtained by the regression equation Source: The Eviews application was developed by the author based on the software package.
Thus, the study shows that there is a high correlation between the production of goods in the manufacturing industry in the Republic of Azerbaijan, investment in fixed assets and GDP, and, using the established model 1, GDP revenues in the Republic of Azerbaijan, as well as processing enterprises. It is also possible to determine forecast prices by year.
The result. As a result of assessing the impact of commodity production and investment in fixed assets on GDP in the manufacturing sector of Azerbaijan on the basis of the EViews application package, it was determined that among these indicators the maximum is expressed by the regression equation Y = 0.9579 * X1 + 8.6936 * X2 -26.617 Exists correlation: an increase in production in the manufacturing industry of Azerbaijan by 1%, GDP growth by 1.465% and an increase in investments in fixed assets by 1% lead to an increase in GDP by 0.14%.
References / Список литературы
1. Aziz Kutlar Eviews is a very balanced time series that should be heard. Uuttepe Publications, Kochaeli University, 2017. Р. 166.
2. Aliyev Tarbiz, Abdurrakhmanova Ayten. Management of oil engineering enterprises. Improving the mechanisms of control over the system. "PUBLICATION MSV". Baku, 2018. 160 p.
3. Yadigarov T.A. (2020 a). Operations Research and Econometric Problem Solving in MS Excel and Eviews Software Packages: Theory and Practice (Monograph). Baku, Europe Publishing House. 352 p.
4. Yadigarov T.A. (2020 b). "Customs statistics and modern information technologies" (Monograph). Baku. Publishing House Europe, 2020. 520 p.
5. [Electronic Resource]. URL: https://www.stat.gov.az/ (date of access: 04.07.2021).
