Analysis of possible availability of the “Dutch disease” in economy of Iran
Автор: Zherebyatyeva N.D., Tregub I.V.
Журнал: Экономика и социум @ekonomika-socium
Рубрика: Основной раздел
Статья в выпуске: 3 (34), 2017 года.
Бесплатный доступ
This article is devoted to the analysis of the possible presence of “ Dutch disease” effect in the Iranian economy through analysis of correlation between gross domestic product and selected parameters. The goal of the model was to reveal correlation between selected parameters in order to investigate to what extent changes in oil production, oil prices and volume of export and import affects GDP. However, results of the first model showed that there is a need to rearrange indicators in order to see “clear picture” and make conclusions concerning such phenomena as “Dutch disease” in Iran.
Dutch disease, oil production, iran, iran economy, econometrics model, oil export
Короткий адрес: https://sciup.org/140122614
IDR: 140122614
Текст научной статьи Analysis of possible availability of the “Dutch disease” in economy of Iran
In order to analyze model 4 exogenous (independent) variables were taken: real oil prices, relation of USD/IRR, total exports and total imports; and 2 endogenous (dependent) variables – GDP and General government revenue. Model has following specification:
fYt = С(1) + С(2) * X1t + С(3) * X2t + С(4) * X3t + ^t {X1t = C(5) + C(6) * Yt + C(7) * X4t + C(8) * X5t + 8t
Where:
-
• Yt- GDP at market prices (current US$ billions);
-
• X1t - General government revenue (current US$ billions);
-
• X2t- Real oil prices (USD per barrel);
-
• X3t - Official exchange rate (IRR per US$, period average);
-
• X4t-Exports of goods and services (current US$ billions);
-
• X5t-Imports of goods and services (current US$ billions).
Data collected for the period from 1997 to 2015 from the open and reliable statistical resources. 1
Estimation was made using Two-Stage Least Squares method and following results were obtained:
System: UNTITLED
Estimation Method: Two-Stage Least Squares
Date: 02/16/17 Time: 10:19
Sample: 1997 2015
Included observations: 19
Total system (balanced) observations 38
|
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
|
C(1) |
-23.67697 |
28.91083 |
-0.818965 |
0.4193 |
|
C(2) |
3.288337 |
1.087492 |
3.023780 |
0.0051 |
|
C(3) |
1.522979 |
1.070179 |
1.423106 |
0.1650 |
|
C(4) |
0.004834 |
0.002181 |
2.216207 |
0.0344 |
|
C(5) |
15.14811 |
16.55602 |
0.914961 |
0.3675 |
|
C(6) |
-0.874649 |
1.037574 |
-0.842975 |
0.4059 |
|
C(7) |
2.553758 |
2.355801 |
1.084029 |
0.2870 |
|
C(8) |
1.845610 |
2.362658 |
0.781158 |
0.4408 |
|
Determinant residual covariance |
1016183. |
Equation: Y=C(1)+C(2)*X1+ C(3)*X2+C(4)*X3
Instruments: X2 X3 X4 X5 C
Observations: 19
R-squared
0.916446 Mean dependent var
0.899735 S.D. dependent var
54.31246 Sum squared resid
0.752381
296.3264
171.5238
44247.64
Adjusted R-squared
S.E. of regression Durbin-Watson stat
Equation: X1=C(5)+C(6)*Y+C(7)*X4+C(8)*X5 Y=C(1)+C(2)*X1 + C(3)*X2+C(4)*X3@X2 X3 X4 X5
X1=C(5)+C(6)*Y+C(7)*X4+C(8)*X5+C(9)*X6@X2 X3 X4 X5
Instruments: X2 X3 X4 X5 C
Observations: 19
|
R-squared |
0.228414 |
Mean dependent var |
56.87841 |
|
Adjusted R-squared |
0.074097 |
S.D. dependent var |
31.03656 |
|
S.E. of regression |
29.86457 |
Sum squared resid |
13378.39 |
|
Durbin-Watson stat |
0.841801 |
As we it seen from the table value of the multiple coefficient of determination R2 =0,92 shows that 92 % of total deviation of GDP is explained by the variation of general government revenue, oil prices and in relation of USD/IRR. Such a high value of the R2 is quite good it is close to 1 (maximumR2 = 1). However, if we look at the second equation of the model we can see that the value of R2 is only 0,22. This means that selected factors influence the given model non-significantly.2 DW test was shows that there exist autocorrelation between indicators.
In order to understand why this model showed poor results for the country of OPEC, that exports oil products amounted more than 80% from the total volume1 [1], it was decided to analyze the chosen indicators’ dynamic more detailed. It can be seen from the table given below that the dynamic of Iranian currency experienced significant falls. After analyzing different articles and news on this topic, it became clear that there exist important political issues that influence the exchange rate of Iran. The peak of sanctions against Iran has begun in 2002 because he has issued "nuclear program" for extraction of uranium in large numbers. Such policy of Iran wasn't pleasant to the USA and Europe as it was visible that Iran extracts uranium not in the peace purposes. Respectively, sanctions against Iran that amplified every year have been imposed. 3
Table 1. Iranian currency (IRR) exchange rate fluctuation during the year 2002
|
Year |
Exchange Rate of IRR |
X6 |
|
1997 |
1753,39 |
0 |
|
1998 |
1752,33 |
0 |
|
1999 |
1753,40 |
0 |
|
2000 |
1764,90 |
0 |
|
2001 |
1754,03 |
0 |
|
2002 |
6907,04 |
1 |
|
2003 |
8193,89 |
1 |
|
2004 |
8613,99 |
1 |
|
2005 |
8963,96 |
1 |
|
2006 |
9170,94 |
1 |
|
2007 |
9281,15 |
1 |
|
2008 |
9428,53 |
1 |
|
2009 |
9864,30 |
1 |
|
2010 |
10254,18 |
1 |
|
2011 |
10616,31 |
1 |
2 Трегуб И.В., Хацуков к.л. Проверка применимости модели для прогнозирования экономических показателей // Экономика и социум. 2014. № 4-4 (13). С. 1345-1349.
3 Expert Online Journal, Iranian Economy, June, 2014, Available at: (Accessed at 16.02.2017)
|
2012 |
12175,55 |
1 |
|
2013 |
18414,45 |
1 |
|
2014 |
25941,66 |
1 |
|
2015 |
29011,49 |
1 |
That is why the extra variable X6 was included in the model in order to smooth down this hard fluctuation of exchange rate. The following results was obtained:
System: UNTITLED
Estimation Method: Two-Stage Least Squares
Sample: 1997 2015
Included observations: 19
Total system (balanced) observations 38
|
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
|
C(1) |
-15.74411 |
26.92958 |
-0.584640 |
0.5633 |
|
C(2) |
2.685356 |
0.993287 |
2.703506 |
0.0114 |
|
C(3) |
2.057049 |
0.982381 |
2.093943 |
0.0451 |
|
C(4) |
0.004455 |
0.002039 |
2.184474 |
0.0372 |
|
C(5) |
13.53520 |
7.311163 |
1.851307 |
0.0743 |
|
C(6) |
-0.328602 |
0.199220 |
-1.649449 |
0.1098 |
|
C(7) |
1.332526 |
0.501873 |
2.655106 |
0.0127 |
|
C(8) |
0.895851 |
0.707177 |
1.266799 |
0.2153 |
|
C(9) |
-16.56023 |
16.33418 |
-1.013839 |
0.3190 |
|
Determinant residual covariance |
262012.6 |
Equation: Y=C(1)+C(2)*X1+ C(3)*X2+C(4)*X3
Instruments: X2 X3 X4 X5 X6 C
Observations: 19
|
R-squared |
0.926601 |
Mean dependent var |
296.3264 |
|
Adjusted R-squared |
0.911921 |
S.D. dependent var |
171.5238 |
|
S.E. of regression |
50.90513 |
Sum squared resid |
38869.98 |
|
Durbin-Watson stat |
0.882670 |
Equation: X1=C(5)+C(6)*Y+C(7)*X4+C(8)*X5+C(9)*X6
Instruments: X2 X3 X4 X5 X6 C
Observations: 19
|
R-squared |
0.858510 |
Mean dependent var |
56.87841 |
|
Adjusted R-squared |
0.818084 |
S.D. dependent var |
31.03656 |
|
S.E. of regression |
13.23760 |
Sum squared resid |
2453.277 |
|
Durbin-Watson stat |
1.306596 |
As we it seen from the table value of the multiple coefficient of determination in the second equation is equal to R2=0,85 compare to the value of 0,22 received in the first model. This means that selected factors influence the given model significantly, and the downturns in the exchange rate can be smoothed out in order to analyze dependence of Iranian Economy on oil production in ore objective way, i.e. without the effect of sanctions imposed on country4. DW test was shows that there exist not significant autocorrelation between indicators.
Conclusion
Nowadays, research on the “Dutch disease” problem become especially relevant due to interesting economic trends arising on the world market. Iran as a huge oil-exporter needs a lot of attention in terms of high volatility. For oilproducing country it is a real struggle to face the “Dutch disease” phenomena in conditions of world economic crises. Especially, if we take into the account the fact that external political climate for Iran cannot be named stable. It was mentioned previously, that despite the fact that the sanction was imposed, and Iranian currency experienced high volatility, this country still remains on of the leading position of oil-producing countries. That is exactly why more attention should be paid on economic policies regarding oil-production as well as export of oil.
After two models’ analysis, based on economic data for the period 19972015, we are able to make following conclusions: 2nd model used, could possibly be used to estimate influence of used factors on gross domestic product, how changes are determined by general government revenue, oil prices and net exports but without accounting on the exchange rate, due to instable political situation and sanctions imposed on Iran.
Список литературы Analysis of possible availability of the “Dutch disease” in economy of Iran
- The Official site of the World Bank, Iranian statistical data profile http://data.worldbank.org (Accessed at 14.02.2017).
- Трегуб И.В., Хацуков К.Л. Проверка применимости модели для прогнозирования экономических показателей//Экономика и социум. 2014. № 4-4 (13). С. 1345-1349.
- Трегуб А.В., Трегуб И.В. Методика прогнозирования показателей стохастических экономических систем//Вестник Московского государственного университета леса -Лесной вестник. -2008. -№2 (59). -С. 144-152.
- Oil and the Future of Iran: A Blessing or a Curse? Future of Iran Economy September, 2013 Available at: http://li.com/docs/default-source/future-of-iran/the-future-of-iran-(economy)-oil-and-the-future-of-iran-a-blessing-or-a-curse-pdf.pdf?sfvrsn=2 (Accessed at 16.02.2017).
- Expert Online Journal, Iranian Economy, June, 2014, Available at: http://expert.ru/2014/02/6/v-ozhidanii-peremen/(Accessed at 16.02.2017).
