Identification of impacting factors of foreign-economic activity of Russian Federation on economic growth using econometrics modeling
Автор: Lomakin M.I.
Журнал: Экономика и социум @ekonomika-socium
Рубрика: Основной раздел
Статья в выпуске: 3 (34), 2017 года.
Бесплатный доступ
The article is dedicated to the determination of indicators of foreign-economic activity, such as export, import, taxes in international trade, also Brent oil prices and exchange rate to USD, so as defining of their impact on the economic growth of Russian Federation represented by the GDP per capita and GDP in the period of 2000-2015 years (all factors except oil prices are in LCU). Results were compared with the overall economic situation in Russian Federation and growth prespectives.
Russia, econometric modeling, financial indicators, economic growth
Короткий адрес: https://sciup.org/140122872
IDR: 140122872
Текст научной статьи Identification of impacting factors of foreign-economic activity of Russian Federation on economic growth using econometrics modeling
Russian economy is defined as a developing, with a huge oil and gas structure which are the main drivers of economic growth of the country. This is due to the estimated total value of natural resources. In 2015, the Russian economy was the sixth largest in the world by PPP and twelfth largest at market exchange rates.
Low oil prices and sanctions over Ukraine have been taking their toll in the Russian economy. Russia has also been feeling the pinch from sanctions imposed by the US and EU over the Ukraine crisis, which have limited its access to international capital markets. In response, Russia placed import bans on various food and agricultural products, leading to further price rises.
In order to reveal which factors are more reliable for identification Russian Federation economic growth the econometric model was created. Here is the data and factors that were used for this model (Table 1)
Table 1. Statistics for econometric model1
|
Series Name |
GDP |
GDPPERCAEXPTOIMP |
EXP |
IMP |
TAXONINTTRAD EXCHRATETO$ |
OILPRBRENT |
||
|
VAR |
Y1 |
Y2 |
X1 |
X2 |
X3 |
X4 |
X5 |
X6 |
|
2000 |
35728520714325,70 |
49834,73 |
5185514438846,39 |
3218900000000,00 |
1755800000000,00 |
230808000000,00 |
28,13 |
28,40 |
|
2001 |
37547811355166,90 |
61267,57 |
5115502734147,24 |
3299600000000,00 |
2165900000000,00 |
333073000000,00 |
29,17 |
24,40 |
|
2002 |
39328955579345,30 |
74458,10 |
5545217766031,68 |
3813700000000,00 |
2646200000000,00 |
325604000000,00 |
31,35 |
24,60 |
|
2003 |
42198338888365,10 |
91312,78 |
6662672728157,23 |
4655900000000,00 |
3153900000000,00 |
452798042900,00 |
30,69 |
29,10 |
|
2004 |
45226470246967,30 |
118189,35 |
8641571040311,76 |
5860400000000,00 |
3773900000000,00 |
859734732500,00 |
28,81 |
37,80 |
|
2005 |
48110194575644,10 |
150571,26 |
10619174983978,50 |
7607300000000,00 |
4648300000000,00 |
1622844600000,00 |
28,28 |
53,80 |
|
2006 |
52032826562391,30 |
188167,01 |
12640313232391,20 |
9079300000000,00 |
5653400000000,00 |
2306400000000,00 |
27,19 |
65,00 |
|
2007 |
56473870044700,00 |
232817,33 |
13908396574952,80 |
10028800000000,00 |
7162200000000,00 |
2346100000000,00 |
25,58 |
73,80 |
|
2008 |
59437592502500,00 |
289169,96 |
16174612623071,50 |
12923600000000,00 |
9111000000000,00 |
3555300000000,00 |
24,85 |
99,30 |
|
2009 |
54789046730100,00 |
271787,00 |
10817654415830,50 |
10842000000000,00 |
7954300000000,00 |
2599200000000,00 |
31,74 |
62,40 |
|
2010 |
57256595067800,00 |
324176,96 |
13798017388021,60 |
13529300000000,00 |
9789600000000,00 |
3163500000000,00 |
30,37 |
80,60 |
|
2011 |
59698117376500,00 |
417583,62 |
16865200000000,00 |
16865200000000,00 |
12010800000000,00 |
4587700000000,00 |
29,38 |
113,50 |
|
2012 |
61798262440600,00 |
467360,89 |
17509501976513,90 |
18324800000000,00 |
13786900000000,00 |
5032500000000,00 |
30,84 |
112,60 |
|
2013 |
62588942726300,00 |
494866,26 |
17300332224597,70 |
18909300000000,00 |
14920900000000,00 |
4974300000000,00 |
31,84 |
110,30 |
|
2014 |
63031052591800,00 |
533539,22 |
16617960204094,20 |
21464300000000,00 |
16296400000000,00 |
5406493442469,40 |
38,38 |
100,10 |
|
2015 |
60682091095900,00 |
551919,64 |
13059998266756,20 |
23863000000000,00 |
17135500000000,00 |
3385631138101,04 |
60,94 |
53,80 |
Dependent varibles:
-
• GDP (Y1) – GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products
-
• GDPPERCAP (Y2) - GDP per capita is gross domestic product divided by midyear population
Independent variables:
-
• EXPTOIMP (X1) - Exports as a capacity to import equals the current price value of exports of goods and services deflated by the import price index. Data are in constant local currency
World bank // Data bank – URL:
-
• EXP (X2) - Exports of goods and services represent the value of all goods and other market services provided to the rest of the world
-
• IMP (X3) - Imports of goods and services represent the value of all goods and other market services received from the rest of the world
-
• TAXOINTTRADE (X4) - Taxes on international trade include import duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes
-
• EXCHRATETO$ (X5) - Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market
-
• OILPRBRENT (X6) – the price for 1 barrel of oil in USD
The system describing the impact of these financial and economic indicators on GDP and GDP per capita level is following:
Y1 = a 0 +a 1 *Y2+a 2 X1+ a 3 *X2+a 4 *X3+e
Y2 = a 5 +a 6 *X2+a 7 *X4+a8*X5+a 9 *X6+z
M(u | X t ) = 0
D(u 2 | X t ) = 5t 2
According to the regression analysis the following results are obtained for equations of the system as they appear (Table 2):
Table 2. Regression analysis summary for EQ1 .
SUMMARY OUTPUT
Regression Statistics
Multiple R 0,983654
|
R Square |
0,967576 |
|
Adjusted R |
|
|
Square |
0,954606 |
|
Standard Error |
2,04E+12 |
|
Observations |
15 |
ANOVA
|
df |
SS |
MS |
F |
Significance F |
|
|
Regression |
4 |
1,25E+27 |
3,12E+26 |
74,60222 |
2,09E-07 |
|
Residual |
10 |
4,18E+25 |
4,18E+24 |
||
|
Total |
14 |
1,29E+27 |
|||
|
Standard |
|||||
|
Coefficients |
Error |
t Stat |
P-value |
||
|
Intercept |
2,96E+13 |
2,21E+12 |
13,37902 |
1,04E-07 |
|
|
X Variable 1 |
11768535 |
75057529 |
0,156794 |
0,878528 |
|
|
X Variable 2 |
1,796327 |
0,424505 |
4,231585 |
0,001739 |
|
|
X Variable 3 |
-0,84322 |
1,629212 |
-0,51757 |
0,616017 |
|
|
X Variable 4 |
0,906463 |
2,523469 |
0,359213 |
0,726905 |
According to the results the estimated model looks like the equation:
Y1 = 29563254009570,00 + 11768534,65*Y2 + 1,80*X1 - 0,84*X2 + 0,91*X3 + e
The strong correlation between endogenous and exogenous variables is described with high coefficient of determination R2 value (0, 0,967) identifying regressors’ ability to indicate the value of endogenous variable accurately. In order to evaluate adequacy of specification F-test was taken. As F = 74,6 is higher than F cr = 5,96 the specification may be counted as adequate.
As for the second equation, the results of regression analysis are following (Table 3):
Table 3 Regression analysis summary for EQ2 .
SUMMARY OUTPUT
|
Regression Statistics |
|||||
|
Multiple R |
0,9976779 |
||||
|
R Square |
0,9953611 |
||||
|
Adjusted R Square |
0,9935055 |
||||
|
Standard Error |
13385,57 |
||||
|
Observations |
15 |
||||
|
ANOVA |
|||||
|
Significance |
|||||
|
df |
SS |
MS |
F |
F |
|
|
Regression |
4 |
3,84E+11 |
9,61E+10 |
536,4208 |
1,28E-11 |
|
Residual |
10 |
1,79E+09 |
1,79E+08 |
||
|
Total |
14 |
3,86E+11 |
|||
|
Standard |
|||||
|
Coefficients |
Error |
t Stat |
P-value |
||
|
Intercept |
-209942,01 |
145085 |
-1,44703 |
0,178499 |
|
|
X Variable 1 |
0,00 |
9,21E-09 |
2,334169 |
0,041752 |
|
|
X Variable 2 |
0,00 |
3,4E-08 |
-0,20067 |
0,84498 |
|
|
X Variable 3 |
5598,07 |
4439,058 |
1,261095 |
0,235901 |
|
|
X Variable 4 |
1204,93 |
1458,487 |
0,826153 |
0,427988 |
|
According to the results the estimated model looks like the equation:
Y2 = - 209942,00 + 0,0000000215*X2 - 0,0000000068*X4 + 5598,07*X5 + 1204,93*X6 + e
R2 value (0, 0, 0,995) is very high, which is showing high relation of dependent and independent variables, describing accurateness of the regressors.
To check whether mathematical expectation is equal zero the values of disturbance terms were summed. The amount equals zero showing up that assumption is correct.
In order to check disturbance terms for homoscedasticity the Goldfeld–Quandt test was performed for both equations. GQ value equals to -0,312 and GQ-1 value is -3,205, that is lower than F cr (5,964) for the EQ1. GQ value equals to -0,064 and GQ-1 value is -15,69, that is lower than F cr (5,964) for the EQ2. Residuals of the model are homoscedastic and therefore the second Gauss-Markov theorem did not confirm.
In accordance with Durbin-Watson test results EQ1 DW (1,216) value is between the dl(0,49) and du(1,70) meaning further research is needed and autocorrelation could not be defined. EQ2 DW ( ) value is between 4-du ( ) and 4-dl ( ) meaning there is no autocorrelation which does not confirm the third Gauss-Markov theorem.
To sum up, the analysis performed shows a significant impact of foreign-economic activity factors such as export, import, export as capacity to import, taxes in international trade, oil prices and exchange rate to USD on the GDP and GDP per capita as indicators of economic growth of Russian Federation. It is obvious that due to the structure of Russian economy foreign activity has a serious role in the overall performance of the country. The fact that large share of Russia’s wealth is based on usage of raw materials and natural resources such as gas, oil and following products made of them largely sold out to other countries.
The model needs a further research with addition of Dummy variables in several cases.
The imperfection of the model is significant, though can be explained by external factors that strongly influenced the figures of the chosen parameters, i.e. economic sanctions (2014), political changes, etc.
Список литературы Identification of impacting factors of foreign-economic activity of Russian Federation on economic growth using econometrics modeling
- Doing business report 2016//World bank -URL: http://www.worldbank.org/
- Ministry of Economic development of the Russian Federation//Official portal of Ministry of Economic development of the Russian Federation -URL: http://economy.gov.ru
- The Central Bank of the Russian Federation//Official website of The Central Bank of the Russian Federation -URL: https://www.cbr.ru/
- Tregub I.V. Econometrics. Model of real system -monography, М.: 2016
- World bank//Data bank -URL: http://www.worldbank.org/
