CC BY
2
УДК 519.862
Glukhova E.D.
1 course master student International Financial Faculty Finance University under the government of Russian Federation
Russia, Moscow Academic adviser: Tregub I. V.
Глухова Е.Д. студент магистратуры 1 курс, международный финансовый факультет Финансовый Университет при правительстве РФ
Россия, г. Москва Научный руководитель: Трегуб И.В.
старший преподаватель ГОЛЛАНДСКАЯ БОЛЕЗНЬ В АЛЖИРЕ Аннотация. Данная работа посвящена исследованию влияния Голландской болезни на экономики нефтедобывающих стран через анализ корреляции между ВВП выбранной страны и заданными параметрами. Исследованная модель показывает, как изменения в доходах бюджета, обменного курса валюты и экспорта, влияют на ВВП.
Ключевые слова. Алжир, ВВП, экономика, экспорт, Голландская болезнь, нефтяная промышленность, цены на нефть.
THE "DUTCH DISEASE" IN ALGERIA. Abstract. This work is dedicated to the "Dutch disease " and its influence on the oil-producing countries' economies through analysis of correlation between gross domestic product of the chosen country and selected parameters. Model shows, how changes in general government revenue, depreciation or appreciation, as well as exports (taking into account, that oil-producing country is mainly oil-exporter), affects GDP.
Key words: GDP, General Government Revenue, Econometrics, Exports, "Dutch disease", Economics, Oil prices, Oil-producing country Summary
This work is dedicated to the analysis of economic model in Algeria. Algeria is a country, strongly dependent on oil exports revenues. Following work includes substantiated problem, main economic indicators of Algeria for the period 19972014, oil prices for the same period of time and estimated model. Model has been estimated using 2SLS method, using EViews program. This work represents a practical example of econometric modeling using real data and based on real economic case. This model contains mathematical representation of the system according to the formulation of problem, methods of constructing the model, computer implementation process modeling and analysis of results. This research provides information about the interdependence of main economic indicators of Algeria. In conditions of high oil price volatility, volatility of demand it is
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interesting to analyze economic indicators of oil-producing country and estimate possible or existing interdependence between them.
Introduction
Algeria, officially the People's Democratic Republic of Algeria, is a sovereign state in North Africa on the Mediterranean coast. Hydrocarbons have long been the backbone of the economy, accounting for roughly 60% of budget revenues, 30% of GDP, and over 95% of export earnings. Algeria has the 10th-largest reserves of natural gas in the world and is the sixth-largest gas exporter. It ranks 16th in oil reserves. Hydrocarbon exports have enabled Algeria to maintain macroeconomic stability and amass large foreign currency reserves and a large budget stabilization fund available for tapping. In addition, Algeria's external debt is extremely low at about 2% of GDP. However, as many big oil-producing countries, Algeria has certain problems developing industries not related with oil industry because of heavy regulation and an emphasis on state-driven growth.1 Here come "Dutch disease" phenomena, explaining the relationship between resource production "boom" and significant decline in other spheres, especially in manufacturing.
Many scientists have been analyzed the influence of oil prices fluctuations on Gross domestic product of Algeria and Dutch disease phenomena. Tunisian scientists R. Jbir and S. Zouari-Ghorbel in their article Oil Price and Dutch Disease: The Case of Algeria, published in Energy Sources journal in 2011 proved the fact that Algeria was affected by Dutch disease through the oil price shock and its correlation with the exchange rate.2
In this article we examined the economic model, which describes, how GDP is affected by General government revenue, exports (taking into account, that in Algeria export mainly represented by Hydrocarbon sector i.e. oil, gas and refined products, and their relation with the exchange rate, in terms of Dutch disease.
In order to analyze model 4 exogenous (independent) variables were taken: real oil prices, relation of USD/DZD, total exports and total imports; and 2 endogenous (dependent) variables - GDP and General government revenue. Model has following specification:
Yt = C(1) + C(2) * X1t + C(3) * X2t + C(4) * X3t + et Xlt = C(5) + C(6) * Yt + C(7) * X4t + C(8) * X5t + st
Where Yt - GDP at market prices (constant 2010 bln US$), X1t -General government revenue bln US$, X2t - Real oil prices (USD per barrel), X3t - Official exchange rate (DZD per US$, period average), X4t-Exports of goods and services (constant 2010 bln US$), X5t-Imports of goods and services (constant 2010 bln US$). Data collected for the period from 1997 to 2014 from the open and reliable resources.
Estimation was made using Two-Stage Least Squares method and following results were obtained:
1 "Country Comparison: Area". CIA World Factbook. Last updated on January 12, 2017
2 Oil Price and Dutch Disease: The Case of Algeria R. Jbir & S. Zouari-Ghorbel Unité de recherche MO.DEV.I 99/UR/0624, Département des Sciences Economiques, Faculté de Sciences Economiques et de Gestion de Sfax , Sfax, Tunisia Published online: 06 Jul 2011.
Coefficient Std. Error t-Statistic Prob.
C( 1) 135.5945 42.88607 3.161736 0 .0038
C(2) 0.084056 0.029785 2.822046 0.0087
C(3) -3.859731 1.605750 -2.403693 0.0231
C(4) -0.724734 0.676566 -1.071195 0.2932
C(5) -7810.180 1556.172 -5.018841 0.0000
C(6) 232.1329 53.58001 4.332453 0.0002
C(7) -188.7766 61.41876 -3.073598 0.0047
C(8) -275.2532 92.10389 -2.988507 0.0058
Determinant residual covariance 16435207
Equation: Y=C(1)+C(2)*X1+ C(3)*X2+C(4)*X3 Instruments: X2 X3 X4 X5 C
Observations: 18
R-squared Adjusted R-squared S.E. of regression Durbin-Watson stat
0.884669 Mean dependent var
0.859955 S.D. dependentvar 10.01809 Sum squared resid 2.929614
139.8959 26.77019 1405.070
Equation: X1=C(5)+C(6)*Y+C(7)*X4+C(8)*X5 Instruments: X2 X3 X4 X5 C Observations: 18
R-squared Adjusted R-squared S.E. of regression Durbin-Watson stat As we it
0.934472 Mean dependent var 3277.372
0.920431 S.D. dependent var 1928.923
544.1107 Sum squared resid 4144790.
1.744285
we it seen from the graph value of the multiple coefficient of determination R2=0,93 shows that 93 % of total deviation of GDP is explained by the variation of general government revenue, oil prices and in relation of USD/DZD. Such a high value of the R2 is quite good it is close to 1 (maximumR2 = 1). This means that selected factors influence the given model significantly.3 DW test was passed successfully and this means that no autocorrelation detected, F-test was passed as well.
Conclusion
Nowadays, research on the "Dutch disease" problem become especially relevant due to interesting economic trends arising on the world market. Algeria as a huge oil-exporter needs a lot of attention in terms of high volatility. For oil-producing country it is a real struggle to face the "Dutch disease" phenomena in conditions of world economic crises. It was mentioned previously, that any market volatility could provoke economic misbalances.
After model' analysis, based on economic data for the period 1997-2014, we are able to make following conclusions: model used, could possibly be used to estimate influence of used factors on gross domestic product, how changes are
3 I.V.Tregub. Mathematical models of economic systems dynamics: Monography. M.: Finance Academy, 2009. 120 p.
determined by general government revenue, oil prices and net exports as well as exchange rate, in terms of "Dutch disease". Algerian economy relies heavily on hydrocarbon sector and depends on exports volume. Of course the way out of that situation is not easy to find at all.
List of references
1.Algeria: Selected Issues. February 2005 IMF Country Report No. 05/52
2.Country Comparison: Area". CIA World Factbook. Last updated on January 12, 2017
3.I.V.Tregub. Mathematical models of economic systems dynamics: Monography. M.: Finance Academy, 2009. 120 p.
4.Oil Price and Dutch Disease: The Case of Algeria R. Jbir & S. Zouari-Ghorbel Unité de recherche MO.DEV.I 99/UR/0624, Département des Sciences Economiques, Faculté de Sciences Economiqueset de Gestion de Sfax , Sfax, Tunisia Published online: 06 Jul 2011. 5.http://data.worldbank.org
УДК 336.221
Гончарова Н.А., кандидат экономических наук, доцент
доцент ВАК
ФГБОУ ВО «Кубанский Государственный Аграрный университет
имени И. Т. Трубилина» Россия, г. Краснодар Захожая Н.Е. студент
4 курс, факультет «Налоги и налогообложение» ФГБОУ ВО «Кубанский Государственный Аграрный университет
имени И. Т. Трубилина» Россия, г. Краснодар
ОФФШОРНЫЕ КОМПАНИИ КАК МЕТОД ОПТИМИЗАЦИИ НАЛОГООБЛОЖЕНИЯ Аннотация: В данной статье рассматриваются вопросы применения оффшорных компаний для оптимизации налогообложения. Рассмотрены основные схемы употребления оффшорных зон для снижения налоговой нагрузки.
Ключевые слова: оффшорные зоны, оффшор, налоговая оптимизация, налоговое планирование, схема.
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