THE IMPACT EXERTED BY SIX VARIABLES ONTO THE GDP CALCULATION THROUGH THE VARIABLE X1 Текст научной статьи по специальности «Математика»

Одним из недостатков социального менеджмента в России является отсутствие обучения данной дисциплине в университетах, что создает слабую подготовку менеджеров в этой сфере. Помимо этого, отрицательное воздействие оказывает консерватизм социального мышления, низкий теоретический и аналитический потенциал развития и недостаточное применение на практике.

Также слабая подготовка менеджеров в этой сфере создает такую ситуацию, когда социальную политику приравнивают к экономике, а социальный менеджмент - к экономическому или финансовому менеджменту, что является не совсем верным.

Социальная политика есть цель социального менеджмента, лишь вместе они выступают процессом либерализации социальной сферы, совершенствования социальных систем, вопросами защиты и стабилизации качества жизни граждан.

Подводя итог, хотелось бы сделать вывод, что социальная политика представляет не только науку об институциональной экономике, но и науку об отношениях граждан с обществом, их взаимосвязях. Социальная политика непосредственно затрагивает повседневные интересы людей, создает те или иные, лучшие или худшие возможности для удовлетворения самых различных их нужд. Поэтому, если она в максимально возможной степени способствует удовлетворению таких нужд и созданию благоприятных условий жизни социума, то это является важным фактором обеспечения стабильности в обществе или в какой-то общественной системе, предотвращая социальную напряженность и конфликты.

Для социального менеджмента, который напрямую взаимосвязан и взаимозависим от социальной политики, большое влияние имеет поведение человека, который выступает объектом социальных отношений. Следовательно, данный менеджмент призван обеспечить современное общество стабильно функционирующим социальным «механизмом» управления социальной сферой жизни.

Список литературы

1. Акинфиева Н.В., Беликова Т.В. Социальный менеджмент. Учебно-методическое пособие. - Саратов: Издательский центр «Наука», 2009. - 92 с.

2. Анисимова С.А. Управление персоналом организации социального обслуживания. Учебное пособие. — М.: АПКиППРО, 2015. — 212 с.

3. Афонин, Ю. А. Социальный менеджмент: Учебник/Жабин А.П., Панкратов А.С.-М.:Изд-во МГУ, 2014.-320с.

4. Волгин Н.А. Корпоративная социальная политика, как ресурс развития России. //Социология власти. 2003. №3. С.115

5. Волгин Н.А. Усиление социальной направленности экономики России: Актуальные проблемы, вопросы теории и практики. М.: Рос. акад. гос. службы при Президенте РФ, 2012

6. Грик Н.А. Управление в социальной работе. Томск: ТУСУР, 2017. — 87 с.

7. Неверов А.В. Основы социального менеджмента. Учебное пособие для студентов гуманитарных специальностей. — М.: РУДН, 2017. — 96 с.

8. Толмачев А.В. Управление организацией (предприятием): учебное пособие // Толмачев А.В., Иванова И.Г. - Краснодар, 2016.

ВЛИЯНИЕ ШЕСТИ ПЕРЕМЕННЫХ НА РАСЧЕТ ВВП ЧЕРЕЗ ПЕРЕМЕННУЮ Х1

Пиль Э.А.

Академик РАЕ, профессор, д.т.н., Государственный университет

аэрокосмического приборостроения

THE IMPACT EXERTED BY SIX VARIABLES ONTO THE GDP CALCULATION THROUGH THE

VARIABLE X1

Pil E.A.

Academic of the RANH, professor, d.t.s., State University of Aerospace Instrumentation

Аннотация

В статье рассматривается вопрос расчета валового внутреннего продукта при шести различных переменных. На основе результатов расчета были построены двухмерные графики, которые дают наглядное представление, как изменяется ВВП от их значений.

Abstract

The present article deals with the issue of the gross domestic product calculation, in the event when six variables affect the GDP. Based on calculation results the 2D graphs were plotted, making it possible to visualize the GDP variations depending on specific variables.

Ключевые слова: валовой внутренний продукт, расчеты, таблицы, 2D.

Keywords: gross domestic product, calculation, tables, 2D figures.

The article as presented below shows how six variables' values affect the GDP calculations. For this purpose the variables' values may be whether constant, increasing or decreasing by a factor of 10. Hence, at issue

is Veu (GDP) - Veu (GDP) = f(X1, X2, X3, X4, X5, X6) variation. Herein Veu (GDP) denotes the volume of economic shell. In this particular case the Veu (GDP) values were calculated through the variable X1 [1, 2].

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

4 6

№ n/n

Fig. 1. Veu (GDP) =fiX1X2X3X4J5J6) X1 =0,24. .13X2=X3=X4=X5=1X5=0,1..1

8400 6300

g 4200

>

2100 0

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

4 6

№ n/n

10

Fig. 2. Veu (GDP) =fX1X2X3X4X5X6) X1=0,24..13X2=X3=X4=1X5=1..10X6=0,1.. 1

9

6

3

0

0

2

8

Thus, Figure 1 shows the Veu (GDP) curve when the variables' values were as follows Х1 = 0.24...13, Х2 = Х3 = Х4 = Х5 = 1, Х6 = 0.1...1. As can be seen from the figure in question, the plotted curve decreases from 8.34 to 4.27, that is by 1.95 times. Therefore, the given variables aren't recommended for use where a country recovers from an economic crisis. In the event the plotted Veu (GDP) curve grows, the variables used may then be applied to draw the country out of the economic crisis.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 3. Veu (GDP) =fX1 X2X3 X4X5 X6) X1=1,7..24,31X2=X3=1X4=X6=0,1..1X5=1..10

The scenario when the dependency Veu (GDP), plotted during the calculations, is a constant value makes it feasible to support the country's economy during the recession period without fluctuations. The following Figure 2 shows the Veu (GDP) curve, with the variables Х1 = 1.7...243, ^ = 1, Х3 = Х5 = 1...10, Х4 = Х6 = 0.1...1, which increases from 8.34 and up to 8338.93, that is by a factor of 1000.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig. 4. Veu (GDP) = fX1X2X3X4X5X6) X1=1,7..243X2=1X3=X5=1J0X4=X5=0,L1

The next two Figures 3 and 4 display two curves when the variables were Х1 = 1.7..24.31, Х2 = Х3 = 1, Х4 = Х6 = 0.1..1, Х5 = 1..10 and Х1 = 1.7..243, Х2 = 1, Х3 = Х5 = 1..10, Х4 = Х6 = 0.1..1 accordingly. As it can be seen, the plotted curves increase equally from

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

8400

6300

a CD

4200

2100

№ n/n

Fig. 5. Veu (GDP) =fX¡X2X3X4X5X5) X1=1,7..2,4X2=X3=X5=1..10X4=X5=0,1..1

8.34 to 8339.93, that is by a factor of 1000. However, it's worth noting here that the values of the variable X1 have their maximums: specifically, Х1max = 67.35 at point 8 (Fig. 3) and Х1max = 570.44 at point 9 (Fig. 4).

Q O

10

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

4,5

3,0

1,5

0,0

№ n/n

Fig. 6. Veu (GDP) =f(X1X2X3X4X5X5) X1=0,88..0,01,X2=1X3=1..10X4=0,1..1,X5=X5=1

10

0

0

2

4

6

8

0

2

4

6

8

The curve plotted in Figure 5 with the variables Х1 = 1.7...2.4, Х2 = Х3 = Х5 = 1...10, Х4 = Х6 = 0.1...1 is similar to the curves in Figures 3 and 4, and it also has its maximum for the variable Х1max = 8.7 at point

7. From the next Figure 6 it is obvious that the Veu (GDP) values remain invariable at the variables Х1 = 0.88...0.01, Х2 = 1, Х3 = 1...10, Х4 = 0.1...1, Х5 = Х6 = 1.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig.7. Veu (GDP) =fX1X2X3X4X5X5) X1=0,12..2,4X2=X3=X4=X5=1,X5=0,99. ..0,1

Similarly, Figure 7 shows that the plotted Veu curve, with X1 = 0.12...2.4, X2 = X3 = X4 = X 5=1, X6 = 0.99...0.1, increases marginally by a factor of 1.95,

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig. 9. Veu (GDP) = f(X1X2X3X4X5X6) X1=0,12..0,12X2=X3=X4=X5=X6=1..0,1

In the following two Figures 9 and 10, the reducing Veu (GDP) curves are shown at X1 = 0.12...0.12, X2 = X 3 = X4 = X5 = X6 = 1...0.1 and X1 = 0.12...0.12, X2 = X3 = X4 = X5 = 1...0.1, X6 = 1 respectively, having their minimums for Veu (GDP)mm = -1.11 at points 7. As it may be noticed, here at once we have negative Veu (GDP) values, which is due to the fact that the variable X5 becomes lesser than the variable X6, i.e. X5 < X6. Therefore in these instances the calculations may be used for point 1 only, when X5 > X6.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig.ll. Veu (GDP) =fX1X2X3X4X5X6) X1=0,12..0,45X2=X3=X4=X5=X6=1..0,1

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig. 13. Veu (GDP) =fX1X2X3X4X5X6) X1=0,12J71X2=X3=X5=1X4= 1.0,1X5= 110

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 8. Veu (GDP) =f(X1X2X3X4X5X5) X1=0,12..0,001X2=1X3=X4=1,X5=X5=1..0,1

that is from 4.27 to 8.34. In Figure 8, the Veu (GDP) curve decreases from 4.27 to 0.004, that is by a factor of 1000.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig. 10. Veu (GDP) =fX1 X2X3X4X5X5) X1=0,12..0,12X2=X3=X4=X5= 1..0,1X5=1

Figure 11 clearly shows that the Veu (GDP) curve decreases from 4.27 down to 0.004, that is by 1000 times, and has its maximum value for the variable X1 being equal to 0.45 at point 4 (X1max = 0.45). The curve plotted in Figure 12 drops from 8.34 down to its minimum of -0.6 at point 9, that is by 13.94 times, upon which value it raises from -0.6 up to -0.4, by a factor of 1.5. In the example given above the calculations may be utilized only between points 1 and 5, since in this particular case the values X5 > X6.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

Fig. 12. Veu (GDP) =fX1 X2X3X4X5X5) X1=0,24..0,05X2=X3=X4= 1X5= L0,1X5=0,1..1

Fig. 14. Veu (GDP) =f(X1 X2X3X4X5X5) X1=0,88..0,88X2=X3=X5=1X4= 0,1. .1X5= 1.0,1

Figure 13 points out that the Veu (GDP) curve, with the variables X1 = 0.12...171, X2 = X3 = X6 = 1, X4 = 1...0.1, X5 = 1...10, increases from 4.27 and up to 8339.93, that is by 1951.37 times. And the Veu (GDP) curve inFigure 14, plotted with X1 = 0.88...0.88, X2 = X3

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

8,4 ■

4,2

> 2,1

4 6

№ n/n

Fig. 15. Veu (GDP) =fX1X2X3X4X5X6) X1=0,12..0,002X2=1..10X3=X4=X5=X6=1

= X6 = 1, X4 = 0.1...1, X5 = 1...0.1, first drops from 4.27 down to its minimum of Veu (GDP) = -1.11 at point 7, and then raises up to -0.4. It is worth mentioning here that yet in the second line the variable values X5 < X6, and therefore these shall be disregarded.

Veu (GDP) = f(X1, X2, X3, X4, X5,

6,0

CD 3,5

-1,5

№ n/n

Fig. 16. Veu (GDP) =f(X1X2X3X4X5X6) X1=1,72..0,36X2=X3=1, X4=X6=0,1. .1, X5= 1.0,1

8,5

6,3

1,0

0

As seen from the Veu (GDP) dependency, plotted in Figure 15, it grows from 4.27 up to 8.34, that is by a factor of 1.94. This curve was plotted under the following values of the variables X1 = 0.12...0.002, X2 = 1...10, X3 = X4 = X5 = X6 = 1. The values Veu (GDP) here vary more vigorously between points 1 and 7. The next Figure 16 was plotted with the variables X1 = 1.72...0.36, X2 = X3 = 1, X4 = X6 = 0.1...1, X5 = 1...0.1

8,5

6,0

3,5

1,0

-1,5

Veu (GDP) = f(X1, X2, X3, X4, X5, :

10

№ n/n

Fig. 17. Veu (GDP) =fX1X2X3X4X5X6) X1 =1,72.. 0,21X2= 1, X3=X5= 1..0,1X4=X6=0,1..1

and it shows that it is similar to Figure 12. The curve plotted here also drops from 8 down to its minimum being -0.6 at point 9, that is by 13.94 times, upon which value it raises from -0.6 up to -0.4, by a factor of 1.5. In the example given above the calculations may be utilized only between points 1 and 5, since in this particular range the values X5 > X6.

8400

6300

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

CD 4200

> 2100

№ n/n

Fig. 18. Veu (GDP) =fX1X2X3X4X5X6) X1 =0,24.. 17,15X2= 1X3=X4=X5= 1.0,1X6=0,11

0

When Figure 17 was plotted, the following variables were used: X1 = 1.72...0.21, X2 = 1, X3 = X5 = 1...0.1, X4 = X6 = 0.1...1. The obtained curve Veu (GDP) is also similar to two curves plotted in Figures 12 and 16 and, hence, their conclusions are also applicable

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

4,5

3,0

1,5

0,0

№ n/n

Fig.19. Veu (GDP) = f(X1,X2,X3,X4,X5,X6) X1=0,88..0,01,X2= 1,X3=1..10, X4=0,1..1,X5=X6=1..0,1

to the former curve. Figure 18 depicts the Veu (GDP) curve which raises fiom 8.34 and up to 8338.93, that is by 1000 times, withthe variables beingXl = 0.24...17.15, X2 = 1, X3 = X4 = X5 = 1...0.1, X6 = 0.1...1. Inthis example the variable X1 has its maximum of 31.6 at point 8 (Xlmax = 31.6).

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

8,5

Q CD

6,0

3,5

1,0

-1,5

1 1

№ n/n

Fig. 20. Veu (GDP) = f(X1,X2,X3,X4,X5,X6) X1=0,24..1,65,X2= 1, X3= 1..10, X4= X5= 1.. 0,1, X6=0,1..1

The Veu (GDP) dependency, plotted in Figure 19, is decreasing from 4.27 down to 0.004, that is by 10 times, with the variables X1 = 0.88...0.01, X2 = 1, X3 = 1...10, X4 = 0.1...1, X5 = X6 = 1...0.1. In this example the variable X1 also has its maximum of 1.62 at point 3 (X1max = 1.62). The curve Veu (GDP) plotted in Figure 20

also drops from 8.34 down to its minimum being -0.6 at point 9, that is by a factor of 13.94, upon which value it raises from -0.6 up to -0.4, by a factor of 1.5. In this example the variable X1 has its maximum of 2.06 at point 4 (X1max = 2.06).

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

8,5

- 6,0 Q."

S. 3,5

=3" 0)

> 1,0

-1,5

Fig.21. Veu (GDP) =fX1X2X3X4X5X5) X1=0,24..0,20X2= 1X3=X4=X5=1..0,1X5=0,1.. 1

8400

6300

S 4200

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

46 № n/n

Fig. 22. Veu (GDP) =fX1X2X3X4X5X5) X1=0,24..0,20,X2=1X3=X4=X5=1..0,1X5=0,1..1

0

№ n/n

The Veu (GDP) curve presented in Figure 21, with variables being X1 = 0.24...0.20, X2 = 1, X3 = X4 = X5 = 1...0.1, X6 = 0.1...1, is identical to the curve in Figure 21. However in this instance the variable X1 has its maximum of 0.56 at point 2 (X1max = 0.56). The Veu (GDP) dependency in Figure 22 was obtained when the

Veu (GDP) = f(X1, X2, X3, X4, X5,

8400

6300

4200

2100

4 6

№ n/n

Fig. 23. Veu (GDP) =fX1X2X3X4X5X5) X1=0,12..0,17X2=X5=1..10X3=X4= 1..0,1X5=1

variables had the following values X1 = 0.24...0.20, X2 = 1, X3 = X4 = X5 = 1...0.1, X6 = 0.1...1. In this example the Veu (GDP) values increase from 4.27 to 8379.59, i.e. grew by 1960.88 times. With these variables the X1 value has its maximum of 573.12 at point 9 (X1max = 573.12).

Q

Ö

4,5

3,0

1,5

0,0

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

10

Fig. 24. Veu (GDP) =f(X1X2X3X4X5X5) X1=0,12..0,09, X2=X3=1..10X4=1..0,1X5=X5=1

0

0

2

4

6

8

As seen in Figure 23 the plotted Veu (GDP) dependency raises from 4.27 to 8338.93, that is by 1951.37 times, under the following variables being X1 = 0.12...0.17, X2 = X5 = 1...10, X3 = X4 = 1...0.1, X6 = 1. In this example the variable X1 has its maximum of 0.85 at point 4 (X1max = 0.85). Figure 24, which was plotted

Veu (GDP) = f(X1, X2, X3, X4, X5, X6) 4,5 . i.i.i.i..

» 3,0

Q.

Q g.

=3"

0) >

with the variables X1 = 0.12...0.09, X2 = X3 = 1...10, X4 = 1...0.1, X5 = X6 = 1, demonstrates that Veu (GDP) dependency remains invariable and equal to 4.27. In this instance the value of the variable X1 has its maximum of 0.2 at point 2 (X1max = 0.2).

Veu (GDP) = f(X1, X2, X3, X4, X5, X6) 8400 -| >

gy 6300 -------jf--

Q-" s

Q /

O 4200

> 2100

4 6

№ n/n

10

Fig. 25. Veu (GDP) =f(X1 X2X3X4X5X5) X1=0,88..1,25X2=X3=1..0,1,X4= 0,1..1,X5=X5=1

4 6

№ n/n

Fig. 26. Veu (GDP) =fX1X2X3X4X5X5) X1 =0,24.. 0,17, X2=X5= 1..10,X3=X4=1..0,1,X5=0,1..1

,5

0,0

0

0

2

8

The Veu (GDP) dependency, plotted in Figure 25 with variables X1 = 0.88...1.25, X2 = X3 = 1...0.1, X4 = 0.1...1, X5 = X6 = 1, is identical to that of Figure 24, except here the X1 variable's value has its maximum of 2.01 at point 9 (X1max = 2.01). From the following Figure 26 plotted with the variables X1 = 0.24...0.17, X2 = X5 = 1...10, X3 = X4 = 1...0.1, X6 = 0.1...1, it can be seen that the Veu (GDP) curve raises from 8.34 and up to 8338.93, that is by 1000 times. And the variable X1 has its maximum of 0.87 at point 4 (X1max = 0.87).

In Figure 27, the Veu (GDP) values increase from 4.27 up to 8338.93, that is by 1951.88 times, under the variables being X1 = 0.88...243, X2 = X6 = 1, X3 = X5 = 1...10, X4 = 0.1...1. In this example the variable X1 has also its maximum of 569.79 at point 9 (X1max = 569.79). Should the Veu (GDP) dependency with the variables X1 = 0.86...1.25, X2 = X3 = X5 = 1...10, X4 = 0.1...1, X6 = 1...0.1 be plotted, then the resulting curve in Figure 28 will go from 4.27 and up to 4273.38, that is by 1000 times. Then, the variable X1 will have its maximum of 4.46 at point 7 (X1max = 4.46).

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 27. Veu (GDP) =fX1X2X3X4X5X5) X1=0,88..243X2=X6=1X3=X5=1..10,X4= 0,1.1

Veu (GDP) = fX1, X2, X3, X4, X5, X6)

№ n/n

Fig. 29. Veu (GDP) =f(X1 X2X3X4X5X6) X1=171..1,25X2=X6=1X2= 1..10, X4= 0,1..1,X5=10..1

The next two Figures 29 and 30 display two Veu (GDP) dependencies which had been plotted with variables X1 = 171...1.25, X2 = X6 = 1, X3 = 1...10, X4 = 0.1...1, X5 = 10...1 and X1 = 171...1.25, X2 = 1, X3 = 1...10, X4 = X6 = 0.1...1, X5 = 10...1 accordingly. We can see that both Figures drop from 8338.93 down to

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig.31. Veu (GDP) =fX1X2X3X4X5X6) X1=172... 0,01X=X3=1..10,X4=X5=0,11X5=101

In the last two Figures 31 and 32, two Veu (GDP) dependencies are presented, with variables X1 = 172...0.01, X2 = X3 = 1...10, X4 = X6 = 0.1...1, X5 = 10.1 and X1 = 0.24...17.15, X2 = X3 = X5 = 1...10, X4 = 1...0.1, X6 = 0.1...1, accordingly. In Figure 31 the Veu (GDP) curve decreases from 8379.59 down to 4.27, that is by 1960.88 times. In Figure 32 the Veu (GDP) curve, conversely, increases from 8.34 to 8338.93, that is by 1000 times.

Below is the Combined Table 1, which incorporates calculations of 25 scenarios out of 83 considered by the author during the Veu (GDP) calculations. This

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 28. Veu (GDP) = f(X1X2X3X4X5X5) X1=0,85..1,25, X2=X3=X5=1..10,X4=0,1..1X5=1..0,1

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 30. Veu (GDP) =fX1X2X3X4X5X6) XI=1711,25X2= 1X3= 1..10, X4=X6=0,11 X5=101

4.27 by 1951.37 times (Fig. 29), and from 8379.59 down to 4.27, by 1960.88 times (Fig. 30). In this case the variables X1 have the following maximums on both curves: 308.61 at point 4 (X1max = 308.61) for Figure

29, and 317.33 at point 3 (X1max = 317.33) - for Figure

30.

Veu (GDP) = f(X1, X2, X3, X4, X5, X6)

№ n/n

Fig. 32. Veu (GDP) =fX1X2X3X4X5X5) X1=0,24..17,15,X2=X3=X5=1..10,X4=1..0,1X5=0,1..1

Table presents all values of Veu (GDP) parameters in descending order. Here, the Veub and Veuf values stand for initial and final values of the parameter Veu (GDP) which had been obtained during the calculations. The Veuf/Veub ratio characterizes the degree of increase (decrease) of the last parameter Veuf value in relation to the initial Veub value, occurred during calculation. This allows for selection of such values of the variables XI, X2, X3, X4, X5, X6 under which the Veu (GDP) growth takes place, even under the provision of the economic crisis, i.e. when the ratio Veuf/Veub > 1.

Table 1.

Scenarios of variation of the values of the variables X1 X2, X3, Х4, Х5, X6, as well as calculated data _Veub and Veuf, and their ratio Veub / Veuf_

№ X1 X2 X3 X4 X5 X6 Veub.Vf (GDPeb.GDPef, $) Veuf/Veub (GDPeu/GDPeub)

1. 0.12.. .24.43 1 1 1 1.10 1.0.1 427.8379.59 1960.88

2. 0.12... 172 1 1 1.0.1 1.10 1.0.1 427.8379.59 1960.88

3. 0.12.1723 1 1.10 0.1.1 1.10 1.0.1 427.8379.59 1960.88

4. 0.12.171 1 1 1.0.1 1.10 1 427.8338.93 1951.37

5. 0.12.17150 1.0.1 1.10 1.0.1 1.10 1 427.8338.93 1951.37

6. 0.88.243 1.0.1 1.0.1 0.1.1 1.10 1 427.8338.93 1951.37

7. 0.12.1715 1.0.1 1.0.1 1.0.1 1.10 1 427.8338.93 1951.37

8. 0.88.573 1 1.10 0.1.1 1.9 1.0.1 427.6107.54 142921

9. 0.88.569 1 1.10 0.1.1 1.10 1 427.6072.06 1420.90

10. 0.88.67.63 1 1 0.1.1 1.8 1.0.1 427.4287.60 1003.33

11. 024.24.31 1 1 1 1.10 0.1.1 8.34.8338.93 1000.00

12. 0.12 1.10 1 1 1.10 1.9.90 427.4273.38 1000.00

13. 0.12.125 1.10 1.10 1 1.10 1.9.90 427.4273.38 1000.00

14. 0.12.124 1 1.10 1 1.10 1.9.90 427.4273.38 1000.00

15. 0.88.124 1 1.10 0.1.1 1.10 1.9.90 427.4273.38 1000.00

16. 024.17.15 1.10 1.10 1.0.1 1.10 0.1.1 8.34.8338.93 1000.00

17. 0.12.31.51 1 1.0.1 1.0.1 1.8 1 427.4257.71 996.33

18. 0.12.0.001 1 1.0.1 1.0.1 1.0.1 1.0.1 427.4198.45 982.47

19. 0.88.0.01 1.10 1.0.1 0.1.1 1.10 1.9.90 427.4198.45 982.47

20. 1.72.570 1 1.10 0.1.1 1.9 0.1.1 8.34.6079.08 729.00

21. 0.88.8.65 1.10 1.10 0.1.1 1.7 1 427.2845.59 665.89

22. 0.88.8.65 1.10 1.10 0.1.1 1.7 1 427.2845.59 665.89

23. 1.72.67.35 1 1 0.1.1 1.8 0.1.1 8.34.4269.53 512.00

24. 024.31.60 1 1.0.1 1.0.1 1.8 0.1.1 427.4269.53 512.00

25. 024.31.60 1 1.0.1 1.0.1 1.8 0.1.1 8.34.4269.63 512.00

The last Table 2 is actually a modified Table 1, in which only the ratio Veuf/Veub > 1 was left, while the variable X2 =1. The variable X2 characterizes the thickness of the economic shell in question. In this way the final Table 2 had been obtained in which all the values of the variables XI, X2, X3, X4, X5, X6, were consolidated, with the help of which a country may be brought out of economic crisis. It shall immediately be mentioned here that when variables from Table 2 are

being selected attention should primarily be focused on those lines which have maximal number of items. In case a variable's value is equal to 1, this means that during the calculations it remained unchanged. In the example given this takes place at three variables' values which are highlighted bold. Therefore in this particular case it will be necessary to change three variables only, which is of course easier.

Table 2.

Scenarios of variation of the values of the variables X1 X2, X3, Х4, Х5, X6, as well as calculated data Veub and Veuf, and their ratio Veub / Veuf at Х2 = 1

№ X1 X2 X3 X4 X5 X6 VeUb.Veuf (GDPeUb.GDPeuf $) Veuf/Veub (GDPeuf/GDPeUb)

1. 0.12.24.43 1 1 1 1.10 1.0.1 427.8379.59 1960.88

2. 0.12.172 1 1 1.0.1 1.10 1.0.1 427.8379.59 1960.88

3. 0.12.1723 1 1.10 0.1.1 1.10 1.0.1 427.8379.59 1960.88

4. 0.12.171 1 1 1.0.1 1.10 1 427.8338.93 1951.37

5. 0.88.573 1 1.10 0.1.1 1.9 1.0.1 427.6107.54 142921

6. 0.88.569 1 1.10 0.1.1 1.10 1 427.6072.06 1420.90

7. 0.88.67.63 1 1 0.1.1 1.8 1.0.1 427.4287.60 1003.33

8. 024.24.31 1 1 1 1.10 0.1.1 8.34.8338.93 1000.00

9. 0.12.124 1 1.10 1 1.10 1.9.90 427.4273.38 1000.00

10. 0.88.124 1 1.10 0.1.1 1.10 1.9.90 427.4273.38 1000.00

11. 0.12.31.51 1 1.0.1 1.0.1 1.8 1 427.4257.71 996.33

12. 0.12.0.001 1 1.0.1 1.0.1 1.0.1 1.0.1 427.4198.45 982.47

13. 1.72.570 1 1.10 0.1.1 1.9 0.1.1 8.34.6079.08 729.00

14. 1.72.67.35 1 1 0.1.1 1.8 0.1.1 8.34.4269.53 512.00

15. 024.31.60 1 1.0.1 1.0.1 1.8 0.1.1 427.4269.53 512.00

16. 024.31.60 1 1.0.1 1.0.1 1.8 0.1.1 8.34.4269.63 512.00

References

1. Пиль Э.А. Расчет ВВП при изменении трех значений переменных. // Materials of the XIII International scientific and practical conference, «Modern scientific potential - 2017», 28 February - 07 March, 2017. Volume 2. Economic science. Sheffield. Science and education. LTD. UK - 104 p. - С. 99-101

2. Пиль Э.А. Построение графиков для экономической оболочки // Materialy XIII. Mieedzy Narodowej Naukowi-Praktycznej Konferencji. «Naukova Mysl Informacyjnej Powiki - 2017». 07-15 marca 2017 roku. Tom 2. Politologia, Prawo, Ekonomiczne nauki Zarzadzanie. Poland. Przemysl Nauka i stadia - 104 p. Str. 18-20