ANALYSIS OF POSSIBLE AVAILABILITY OF THE DUTCH DISEASE IN ECONOMY OF IRAN

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1 УДК Zherebyatyeva N.D., master student of 1 st year IFF group 1-2m Scientific adviser: Tregub I.V. Ph.D. in Technics, Sc.D. in Economics, Professor Financial University under the Government of the RF Moscow, Russia Жеребятьева Н.Д., студент 1 курса магистратуры МФФ группа 1-2м Научный руководитель: Трегуб И.В., к.т.н., д.э.н., профессор Финансовый университет при Правительстве РФ Россия, Москва ANALYSIS OF POSSIBLE AVAILABILITY OF THE DUTCH DISEASE IN ECONOMY OF IRAN Abstract. 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

2 need to rearrange indicators in order to see clear picture and make conclusions concerning such phenomena as Dutch disease in Iran. Key words: Dutch disease, oil production, Iran, Iran economy, econometrics model, oil export. 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: Where: { Y t = C(1) + C(2) X1 t + C(3) X2 t + C(4) X3 t + ε t X1 t = C(5) + C(6) Y t + C(7) X4 t + C(8) X5 t + ε t Y t - GDP at market prices (current US$ billions); X1 t - General government revenue (current US$ billions); X2 t - Real oil prices (USD per barrel); X3 t - Official exchange rate (IRR per US$, period average); X4 t -Exports of goods and services (current US$ billions); X5 t -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: Included observations: 19 1 The Official site of the World Bank, Iranian statistical data profile (Accessed at )

3 Total system (balanced) observations 38 Coefficient Std. Error t-statistic Prob. C(1) C(2) C(3) C(4) C(5) C(6) C(7) C(8) Determinant residual covariance Equation: Y=C(1)+C(2)*X1+ C(3)*X2+C(4)*X3 Instruments: X2 X3 X4 X5 C Observations: 19 R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid 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 Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat As we it seen from the table value of the multiple coefficient of determination R 2 =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 R 2 is quite good it is close to 1 (maximumr 2 = 1). However, if we look at the second equation of the model we can see that the value of R 2 is only 0,22. This means that selected factors

4 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 X , , , , , , , , , , , , , , , Трегуб И.В., Хацуков к.л. Проверка применимости модели для прогнозирования экономических показателей // Экономика и социум (13). С Expert Online Journal, Iranian Economy, June, 2014, Available at: (Accessed at )

5 , , , ,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: Included observations: 19 Total system (balanced) observations 38 Coefficient Std. Error t-statistic Prob. C(1) C(2) C(3) C(4) C(5) C(6) C(7) C(8) C(9) Determinant residual covariance Equation: Y=C(1)+C(2)*X1+ C(3)*X2+C(4)*X3 Instruments: X2 X3 X4 X5 X6 C Observations: 19 R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat 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

6 R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat As we it seen from the table value of the multiple coefficient of determination in the second equation is equal to R 2 =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 country 4. 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 , we are able to make following conclusions: 2 nd model used, could 4 Expert Online Journal, Iranian Economy, June, 2014, Available at: (Accessed at )

7 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.

8 References 1. The Official site of the World Bank, Iranian statistical data profile (Accessed at ). 2. Трегуб И.В., Хацуков к.л. Проверка применимости модели для прогнозирования экономических показателей // Экономика и социум (13). С Трегуб А.В., Трегуб И.В. Методика прогнозирования показателей стохастических экономических систем //Вестник Московского государственного университета леса Лесной вестник (59). С Oil and the Future of Iran: A Blessing or a Curse? Future of Iran Economy September, 2013 Available at: (Accessed at ). 5. Expert Online Journal, Iranian Economy, June, 2014, Available at: (Accessed at ).