CC BY
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List of sources:
1. Joao Sousa Andrade, Adelaide Duarte, The Fundamentals of the Portuguese Crisis // PANOECONOMICUS, 2, 2011. PP. 195-218.
2. Joao Sousa Andrade, Adelaide Duarte, The Dutch Disease in the Portuguese Economy // Estudos do GEMF, #5, 2013.
3. Zuzana Brincikova, The Dutch Disease: An Overview // European Scientific Journal, August 2016.
4. Трегуб И.В. Investment project risk analysis in the modern Russian economy // research in empirical international trade. - Slovenia: working papers. June. 2012.
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6. Трегуб И.В. Математические модели динамики экономических систем -монография, М.: 2009.
УДК 330.4
Tsarkova V.S. 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 NIGERIA Key words:
Nigeria, «Dutch disease», Gross domestic product, Total export of goods, consumer price index, exchange rate US dollar/ Nigerian naira, oil prices, foreign direct investment. Abstract
This article analyzes the development of the Dutch disease in Nigeria. For the analysis I used yearly data from 1995 to 2015. These results illustrate that a significant proportion of Nigeria's GDP is generated mainly due to the revenues from fuel exports , while other industries remain outside the attention of the state and stay underdeveloped. I used an econometric model, whereby the analysis confirmed the hypothesis of the presence of Dutch disease in Nigeria's economy.
Summary
At the present stage of economic development, many countries faced the problem associated with the movement of factors of production from less developing sectors of the economy in a rapidly developing industries. Typically, such movement includes the capital, as investments in the fast-growing sector
become immediately profitable. Furthermore, human resources in such sectors are better compensated as a result of increased demand. Reallocation of capital and labor can have a negative impact on those industries that have lost these resources, causing them to decline. As the cost of production factors exacerbated by the effect of the resources movement, those sectors competing for affected resources tend to lose their competitive edge. To sum up, Dutch disease affects the economy of a country in two ways: first by causing a resource movement effect from one sector of the economy to another, and second, by inducing a spending effect that appreciates the real exchange rate of the country's currency 30. Symptoms listed above make it possible to ascertain the presence of "Dutch Disease" in a particular country.
In Africa, there is a looming threat of Dutch disease due to the substantial natural resource wealth of many of its regions. Nigeria began extracting oil in the late 1950s and since then the oil industry has dominated the economy and given it much needed boosts. However, price shocks in oil and recessions have severely damaged its economy, leaving it at the mercy of the market.
Literature review
There is a growing literature dealing with different aspects of the Dutch Disease and resource curse. Since the focus of this article is on the existing of «Dutch Disease» in Nigeria and an examination of economic indicators which affect GDP more , this section reviews some empirical and theoretical studies on this topic which were used in analysis.
Theoretical study of Jason Gould and Katen N. Kapadia High explains the effects of increasing in oil production which leads to ignoring traditionally strong sectors. In the other study, Bayoumi and Mhleisen (2006) estimate the influence of changes in energy and non-energy commodity prices on real exchange rate. The work of Forsyth and Nicholas (2008) was also dedicated to examining whether economy of the country suffer from «Dutch disease». Their general result is that non-oil manufacturing was spared the perverse effects of oil price increases despite the appreciation of the nominal and real exchange rate.
On the basis of mentioned studies I composed system of equations, which helps to test economy of Nigeria for the symptoms of «Dutch disease».
Empirical evidence
To confirm the hypothesis of existing "Dutch disease" in economy of Nigeria I took yearly data from 1995 to 201531. The analysis in this article is based on the World Bank's official data. The following indicators were analyzed:
1. Gross domestic product (Billion US dollars);
2. Total export of goods (Billion US dollars) ;
3. Fuel export (Billion US dollars);
4. Consumer price index;
30 Jason Gould and Katen N. Kapadia. Dutch Disease in Africa: A Case Study of Nigeria and Chad: University of Michigan
31 World bank national accounts data http://data.worldbank.org/country/nigeria_
5. Exchange rate of Nigerian Nairn against US dollar
6. Oil prices
7. Foreign direct investment inflow. Using this indicators I composed following equation:
Y = C1 + C2X1 + C3x4 + C4x6 ; x4 = C5 + C6Y + C7x2 + C8x5 + C9x6 + C10x7 + C11x3.
Where Y - GDP, X1 - Total export of goods; X2 - Fuel export, X3 - Real interest rate , X4 - CPI, X5 - exchange relation US$/Nigerian Naira, X6 - oil prices, X7 - FDI .
According to model above, dependent variables are GDP expressed in billions US dollars and Consumer Price Index. Total export of goods, fuel export, real interest rate, exchange relation US$/Nigerian Naira, oil prices and foreign direct investment are considered as instrumental variables
With the help of Eviews, using Two- Stage Least Squares Method I obtain following results:
Coefficient Std Error t-Statistic Prob
c<1) -59 33020 25 75410 -2 303719 0 0281
C<2) 3 560144 1 550658 2 295893 0 0286
C<3) 2 954952 0460034 6 423332 0 0000
C(4) -2 776927 1 819182 -1 526470 0.1370
C(5) -8697240 9150549 -0 950461 0 3492
C(6> 0142776 0 035977 3.968519 0 0004
C(7) -0 267654 0083657 -3 199435 0 0032
C(8) 0290197 0089809 3 231284 0 0029
C(9) 0 322457 0125900 2 561203 0 0155
COO) 14 36297 5 741797 2501475 00179
C(11) 0015436 0084556 0182549 0 8563
Determinant residual covariance 2887913
Looking at model probability of mistakes of coefficient C(5) and C(11) is high and it exceeds allowable 15%. In this case I decided to exclude coefficient C(11) from the model to make it more significant. C(5) is constant that is why we don't take its value into account and don't exclude from the model.
Coefficient Std. Error t-Statistic Prob.
C(1) -58.03160 26.03623 -2.228879 0.0330
OC2) 3.640109 1.567715 2.321920 0.0268
C£3> 2.897192 0.467408 6.198419 0.0000
C<4) -2.304865 1.837495 -1.526461 0.1367
C(5) -9.223577 7.43509 + -1.240546 0.2238
C(6) 0.141646 0.031 673 4.472171 0.0001
cm -0.266441 0.080261 -3.319680 0.0023
OCB) 0.296166 0.070901 4.177164 0.0002
OC9) 0.319902 0.123813 2.583749 0.0145
0(10) 14.53747 5.162388 2.816036 0.0033
Determinant residual covariante 29780.66
Equation: Y= 0(1) -<-C(2rX1 *C(3)1X4 +■ C(4)*X6
instruments: X1 X2X5X6 X7 C
Observations: 21
R-squared Adjusted R-squared S.E. of regression D urbin-Watson stat
0.948815 Mean dependentvar "194.3020
0.939783 S.D. dependentvar 187.6431
46.04620 Sum squared resid 36044.29 1 061322
Equation: X4 = 0(5) + Cl(6)*Y + Of7J*X2-instruments: XI X2X5X6 X7 C Observations: 21
-C(8)*X5 -<-Ct9)*X6 * C(1 0)*X7
R-squared Adjusted R-squared S.E. of regression □ urbin-Watson stat
0.990391 Mean dependent var 69.61427
0.987189 S.D. dependent var 44.38420
5.023751 Sum squared resid 378.5712 2.378715
High value of coefficient of determination R2=0.94 shows that 94% of total deviation of GDP is explained by the variation of total export of goods, consumer price index and oil prices. This result proves all chosen indicators to be significant. The other coefficient of determination of second equation is also high32. It illustrates that fuel export, real interest rate, oil prices, FDI inflow significantly influence on CPI. According to the model above we can see that probability of mistakes of all coefficients is acceptable.
Then, to check whether autocorrelation is of the residuals of the model, we should pay attention on value of Durbin- Watson statistic. With the help of tables of Durbin- Watson statistic , we can find that for n = 21 and k = 5 values dL = 0,83 and dU = 1,96. As we see , DW1 = 1,06 is on the interval (0,83 : 1,96 ) in uncertainty zone and because of this we can't argue whether there is autocorrelation or not. The second value DW2 = 2, 38 is in uncertainty zone as well (4 - 1,96 = 2, 04), it is also impossible to conclude about the presence of autocorrelation.
Conclusion
Analyzing the econometric model we can see that total export of goods has a large influence on Gross domestic product. With an increase in exports to one billion US dollars, GDP increases by 3.6 billion dollars. In addition, exchange-traded oil prices also have a significant impact on GDP. With an increasing of oil prices on the US dollar, the GDP of Nigeria loses 2.8 billion US
32 I.V.Tregub. Mathematical models of economic systems dynamics: Monography. M.: Finance Academy, 2009. 120 p._
dollars. Keeping at view that oil exports exceed 70% of the total export of goods in the structure of exports of Nigeria, we can conclude that this is the dominant sector of the economy, while other industries remain outside the attention of the state and stay underdeveloped. This factor lets us say that economy of Nigeria suffer from «Dutch disease».
However, analyzing the second equation, we can see that an increase in FDI to one billion US dollars, the CPI increases by 14 units. In this case, the task of the government is to organize measures to attract investment in other sectors of the economy. Thus, the development of other sectors will reduce the dependence of the Nigerian economy on the world market price changes.
List or references:
1. Jason Gould and Katen N. Kapadia. Dutch Disease in Africa: A Case Study of Nigeria and Chad: University of Michigan
2. "The Dutch Disease," Nov. 26, 1977, The Economist, pp. 82-83
3. "Country Profile 2008: Nigeria," Economist Intelligence Unit 4-6
4. World bank national accounts data http://data.worldbank.org/country/ni geria
5. I.V.Tregub. Mathematical models of economic systems dynamics: Monography. M.: Finance Academy, 2009. 120 p.
УДК 330.101.22
Umarova A.N. Third-year student, Economics and finance faculty Obukhova L. Y. Scientific supervisor Senior teacher Foreign languages department Financial University under the Government of the Russian Federation Russia, Moscow ECONOMIC EFFICIENCY VS. SOCIAL JUSTICE Abstract: The article discusses two controversial concepts: of 'economic efficiency' and 'social justice'. The author considers the possible ways offinding a compromise between these two opposites.
Key words and phrases: economic efficiency, social justice, redistribution of incomes, diversification strategy, socially oriented economy.
In economics, there are apparent contradictions between such concepts as: 'economic efficiency' and 'social justice'. Today, the issue of implementation of the principles or an attempt to integrate the opposites, is especially relevant.
What is 'economic efficiency'? As a rule, it implies the effectiveness of production, which is determined by comparing costs and profits. The economic efficiency of the country is characterized by a number of factors:
