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analyzed. Being trustworthy and adequate, the econometric model passed a number of tests. Calculations confirmed the hypothesis 2 and 7 and proved significance of total reserves and oil price for decision-making of foreign investors. Moreover, gross domestic models in the previous period and R&D expenditure variables were also included in the model showing negative correlation with the endogenous variable - FDI.
But at the same time, the model requires further study as significant role of the institutional factors were not taken into consideration. Firstly, well-developed institutions contribute to the growth of productivity of factors in the country-recipient. Secondly, operation of poor-developed institutions can lead to additional costs for the investors (for example, bribes in case of corruption). Thirdly, the FDI are particularly vulnerable to all the forms of uncertainty in the host country. Thus, the institutional factors can explain the dynamics of FDI flows as well as economic determinants, especially in developing economies, e.g. the Russian Federation.
The list of reference:
1. Average annual OPEC crude oil price from 1960 to 2017 (in U.S. dollars per barrel) // Statista URL: https://www.statista.com/ (дата обращения: 27.02.2017).
2. DataBank. World Development Indicators // The world bank URL: http://databank.worldbank.org/data/home.aspx (дата обращения: 27.02.2017).
3. Foreign direct investments in Russia sharply decrease // BBC URL: http://www.bbc.com/russian/news/2016/05/160527_direct_investments_russia (access date: 25.02.2017).
4. Suslov M.Yu.E., Tregub I.V. Ordinary least squares and currency exchange rate // International Scientific Review. 2015. № 2 (3). С. 33-36.
5. Tregub I.V. The capital market model on the example of Norway // в сборнике: forum for research in empirical international trade сан Рафаэль, 2015.
УДК 330.4
Orlov Ph.P. First-year master student International Finance Faculty Financial University under the Government of Russian Federation
Russia, Moscow 2017
THE USE OF ECONOMETRIC METHODS IN THE CONSTRUCTING OF MATHEMATICAL SYSTEMS FOR DETECTING «DUTCH DISEASE» IN ECONOMY. EVIDENCE FROM CANADA
Key words:
Dutch disease, Canada, GDP, regression, export, crude oil, natural gas, energy, oil prices, natural resources, industry, exchange rates, economics, econometrics.
Abstract
This work answers the question about existence of the Dutch disease in Canada. To answer this question the regression analysis was made with the help of a special software Eviews 9. The TSLS model, which was used in this work, shows us the situation where Canadian GDP depends on exchange rates, oil prices, export of crude oil and where exchange rates depend on GDP, oil prices, export of natural gas and other energy.
Introduction
The Dutch disease relates to the situation where a resource boom appearing in an economy leads to the strengthening of real exchange and to the weakening of manufacturing sector at the same time. The underlying mechanism, which takes place in the Dutch disease, works that the real exchange rate tends to become stronger with the increase of exports from the natural resource sector. However, such currency strengthening affects badly the economy's exports relating to the manufacturing sector. It may even lead to de-industrialization.24
Hypothesis and literature review
First of all, it is important to recall a situation from the past to explain the hypothesis of this work. In the period of 2002 - 2008, the significant rise in oil prices and commodity has led to a development of the Canadian commodity and energy sectors. It can be demonstrated by the substantial development of the oil sand in the province of Alberta, in its Northern part called Athabasca. The increase of the oil prices to a new high level has caused an expansion of oil extraction and its export, because the extraction from oil sand is really difficult and costly. This has led to a significant increase of nominal GDP per capita in Alberta, to important financial spillovers for some other provinces and improvement of public finance in the region. During the same term, the exchange relation of Canadian dollar/US dollar appreciated and the industrial production sector has contracted. Canada has also increased many concerns of economists and policy makers while the rise of commodity and energy prices gives obvious benefits for its economy as a whole.
These concerns were mainly referred to the possibility that the Dutch disease phenomenon could take place in the Canadian economy at that period of time. However, it does not mean that the situation has changed and it gives us additional reasons to check it. It is taken for granted nowadays by the most part of analysts that strengthening of the Canadian dollar versus the US dollar negatively affects the Canadian economy. Moreover, it is also strongly believed that the Canadian currency is very dependent on oil prices.25 If we return back again to the example above, sometime later the sudden decrease took place, because the oil and commodity prices together with the worsening situation relating to the financial crisis in 2008 have put an end to the resource boom in Canada. Going
24 Corden, W.M. - "Boom Sector and Dutch Disease Economics: Survey and Consolidation." 1984.
25 The Toronto conference in January 2008 - "Implications for Canada of a High-valued Canadian Dollar. Has the Canadian Economy Caught Dutch Disease?"_
further into the version of existence of the Dutch disease in Canada it is necessary to mention that there was a slight decrease in the Canadian manufacturing sector of economy at that period of time. It was shaken as well, because of the worsening of the economy of the United States the same year.
According to all mentioned before, it makes sense to make a hypothesis basing on two strands. They were already used some time ago by different authors.26 A first strand should test that GDP of Canada is dependent on the CAD/USD exchange rate, oil prices and export of crude oil. A second strand should test whether the CAD/USD exchange rate is dependent on GDP, oil prices, export of natural gas and other energy resources.
Analysis and results
During the recent analysis was used the Two-Stage Least Squares Regression model which is the most suitable here, because our hypothesis includes two strands which consist of dependent and independent variables and this model is used exactly in such cases. 2SLS analysis is the extended version of the OLS model.
The recent analysis has two dependent variables: GDP and CAD/USD exchange rate. It has four independent variables: oil prices, export of crude oil, export of natural gas and export of other energy resources. All data was taken from the Statistics Canada and Federal Reserve Bank of St. Louis. GDP is the model is the Real GDP Index for Canada, where 2010 is taken as 100. Oil prices are in US dollars and are WTI historical prices. All export variables are presented in analysis in millions of US dollars. All abovementioned data was taken quarterly for the period of 1996 - 2016 and is seasonally unadjusted.
According to these indicators, the following equation was composed: GDP = C(1) + C(2)CAD_USD + C(3)OIL_PRICE + C(4)CRUDE_OIL CAD_USD = C(5) + C(6)GDP + C(7)OIL_PRICE + C(8)NATURAL_GAS +
C(9)OTHER_ENERGY Instruments: OIL_PRICE, CRUDE_OIL, NATURAL_GAS, OTHER_ENERGY
Total amount of observations in each equation is 84 and 168 observations in total, which gives us a possibility of a widespread regression analysis to find evidence of existence of the Dutch disease in Canada. The result is below:
Coefficient Std. Error t-Statistic Prob.
C(1) 1.312888 0.249904 5.253578 0.0000
C(2) -0.888431 0.417007 -2.130496 0.0347
C(3) 0.003245 0.002216 1.464725 0.1450
C(4) 1.75E-05 4.19E-06 4.164732 0.0001
C(5) 0.880419 0.068161 12.91673 0.0000
26 Robert A. Amano, Simon van Norden - "Oil Prices and the Rise and Fall of the U.S. Real Exchange Rate" May 1996.
C(6) -0.343461 0.085197 -4.031388 0.0001
C(7) 0.004616 0.000409 11.27488 0.0000
C(8) -4.16E-06 2.12E-06 -1.960756 0.0517
C(9) 3.57E-05 1.94E-05 1.836706 0.0681
Determinant residual covariance 2.69E-06
First equation: GDP = C(1) + C(2)*CAD USD + C(3)*OIL PRICE + C(4)*CRUDE OIL
R-squared 0.626499 Mean dependent var 0.934925
Adjusted R-squared 0.612492 S.D. dependent var 0.129250
S.E. of regression 0.080459 Sum squared resid 0.517886
Second equation: CAD USD + C(9)*OTHER ENERGY = C(5) + C(6)*GDP + C(7)*OIL_PRICE + C(8)*NATURAL_GAS
R-squared 0.866707 Mean dependent var 0.814886
Adjusted R-squared 0.859958 S.D. dependent var 0.127649
S.E. of regression 0.047769 Sum squared resid 0.180269
According to the result determined by Eviews 9, it is necessary to mention several facts. Firstly, both R2 s demonstrate high values. The first R2 is 0,63 and it means that the total deviation of Canadian Gross Domestic Product can be explained by CAD/USD exchange rate, oil price and export of crude oil. The second R2 is even higher and equals to 0,87 and illustrates that CAD/USD exchange rate really depends on GDP, oil price, export of natural gas and export of other energy. Moreover, all the probabilities of mistakes are low and are about 0,1 while rounding them. It means that our model is significant. Statistical Error indicators of regression demonstrate low probability of statistical error that means that the regression results are very accurate.
Conclusion
According to the econometric model illustrated above, several economic conclusions should be made. The GDP index of Canada decreases by 0,89% if the exchange rate of Canadian dollar increases by 1 LCU to the US dollar. It means that the economy of Canada really suffers from the Canadian dollar strengthening. Another fact is that the Index of GDP slightly rises by 0,003% if oil price increases by 1 US dollar. Moreover, the Index of GDP increases by 1,75% if the export of crude oil rises by 1 million US dollars. It shows us that the Canadian GDP is influenced by oil prices and export of oil. Pretty the same situation refers to the second equation, where CAD/USD exchange rate decreases by 0,34% if the GDP index increases by 1%. CAD/USD exchange rate also rises by 0,0046% if oil price rises as well. It means that the Canadian dollar is slightly influenced by oil prices.
Another economic conclusion refers to the Canadian exports, where export of crude oil, natural gas, refined petroleum and other energy resources is one of
the minor parts in the export structure of Canada. It is just 3% out of total and it demonstrates us that the sector of natural resources does not influence the Canadian economy too much.
Finally, it is obvious that the Canadian economy is dependent on oil prices and the sector of natural resources (especially crude oil). However, such dependence is very slight and the mentioned sector is not the major one in Canada. According to these two conclusions, we can make a final one: there is no Dutch disease in Canada nowadays, but it can take place in this country if some special conditions appear.
References:
1. www.statcan.gc.ca
2. fred.stlouisfed.org
3. Corden, W.M. - "Boom Sector and Dutch Disease Economics: Survey and Consolidation." 1984.
4. The Toronto conference in January 2008 - "Implications for Canada of a High-valued Canadian Dollar. Has the Canadian Economy Caught Dutch Disease?"
5. Robert A. Amano, Simon van Norden - "Oil Prices and the Rise and Fall of the U.S. Real Exchange Rate" May 1996.
6. Трегуб И.В. Математические модели динамики экономических систем -монография, М.: 2009.
7. Suslov M., Tregub I. Modeling the currency exchange rate. Methods and principles // Economics. 2015. № 1. С. 67-70.
8. Suslov M.Yu.E., Tregub I.V. Ordinary least squares and currency exchange rate // International Scientific Review. 2015. № 2 (3). С. 33-36.
The influence of "Dutch Disease" on the Libya's economy. Prepared by: Anton Shumov
University: Finance University under the Government of the Russian Federation
Faculty: International Finance Faculty
Group: 1-2 master program
Academic adviser: Tregub Ilona Vladimirovna
Key words: GDP, General Government Revenue, Econometrics, Exports, "Dutch disease", Economics, Oil prices, Oil-producing country, Libya, Econometric model, use of Eviews, Study of real statistical data. Abstract
This work sheds light on the "Dutch disease" and its influence on the oil-producing economies through the analysis of correlation between gross domestic product of the chosen country and such key indicators as country's exchange rate, oil prices and government revenue. Model shows, how changes in general government revenue and oil market prices, depreciation or appreciation, as well as exports (taking into account, that oil-producing country is mainly oil-exporter), affects GDP. It supposed that county's exchange rate depends on the oil market
