CC BY
17
6. Капитонова Н.В., Капитонова A.A. Теневая экономика в условиях пандемии C0VID-19 в России/ /Теневая экономика, - 2020. - Том 4. -№ 4. - С. 193-204.
7. МазурЛ.В., Батяев A.B. Налоговая нагрузка и теневая экономика // Территория науки. - 2018. -N»5. С98-105.
З.Массарова А.Р.Ликвидация бедности в развивающихся странах: эволюция концепций // Вестник РУДН. Серия: Экономика. - 2015.- №4. - С.51-63. 9. Северухин C.B.Теневая экономика в строительном секторе: анализ и меры противодействия //
Вестник Академии права и управления. - 2020. -№3 (60).-С57-61.
10. Теневая экономика поданным Росстат [Электронный ресурс]. -Режим доступа: https:// rosinfostat.ru/tenevaya-ekonornika/ (дата обращения: 12,01.2022).
11. Emerging from the shadows // The shadow economy to 2025. - URL https;//www.accaglobal. com/sg/en/professional-insights/global-econoinics/Emerging-from-the-shadows.htnnl (accessed: 23.01.2022).
ПОКАЗА ТЕЛЬ ОТНОСИТЕЛЬНОЙ ПРОДУКТИВНОСТИ В ГЛОБАЛЬНОЙ ЭКОНОМИКЕ Сейдаметова За рема Сейдалиевна, доктор педагогических наук, профессор Темненко Валерий Анатольевич, кандидат физико-математических наук, доцент
Крымский инженерно-педагогический университет имени Февзи Якубова, Симферополь, Республика Крым
Цель исследования - ввести новый экономический индекс "показатель относительной продуктивности страны в глобальной экономике су", характеризующий отклонение индекса экономической продуктивности (ЕР!) данной страны от некоторой идеальной продуктивности, определенной формой осевой линии роя глобальной экономики в трехмерном пространстве экономических индексов ЕР! BU, CPL Для определения величин показателя g используются форма осевой линии глобальной экономики 2019 года, установленная ранее авторами. В статье изучено распределение стран по показателю g и индексу социально-экономического равновесия стран a, а также исследована связь показателя g с индексом экономической продуктивности ЕР!. Научная новизна заключается во введении нового экономического индекса и вычислении его значений для с тран по эко/!омическим данным 2019 года. Распределение с тран по показа телю g позволяе т выявить в результате некоторый диапазон индекса д, свидетельствующий о сбалансированном состоянии экономики.
Ключевые слова: глобальная экономика; экономические индексы; ЕР!-группы.
D0I 10.24923/2222-243Х.2022-42.10
УДК 339.97:330.43 THE RELATIVE PRODUCTIVITY EXPONENT
ВАК РФ s.2.2/08.00.1 з /д/ GLOBAL ECONOMY
ß Seidametova Z.S., 2022 & Temnenko V.A., 2022
SEIDAMETOVA Zarema Seidalievna, DScof Pedagogical sciences, Professor
The purpose of the study is to introduce a new economic index, the "relative productivity exponent in the global economy g", which characterizes the deviation of the economic productivity index (EPi) of a given country from some ideal productivity determined by the shape of the axial line of the swarm of the global economy in the three-dimensional space of economic indices EPI, BU, CP!. To determine the values of the relative productivity exponent g, the shape of the axial tine of the global economy of2019, established earlier by the authors, is used. The article examines the distribution of countries according to the exponent g and the index of socio-economic equilibrium of countries ft, and also investigates the relationship between the exponent g and the index of economic productivity EPi. The scientific novelty of the research lies in the introduction of a neweconomic index g and the calculation of its values for countries based on economic data from 2019. The distribution of countries according to the value of g allows us to reveal, as a result, a certain range of the exponent g, indicating a balanced state of the economy.
Keywords: global economy; economic indices; EPi-groups.
TEMNENKO Valery AnatoHevich, PhD of Physics and Ma thernaticalsciences, Associate Professor
Crimean Engineering-Pedagogical University named after Eevzi Yakubov, Simferopol, Republic of Crimea
Introduction
The authors of the article [1 ] introduce the general idea of describing the global economy in multidimensional presentation spaces of economic indices. In particular, the convenience of using the three-dimensional space of economic indices EPI, BLI, CPI was noted. The EPI measures the economic productivity of a country. This index is determined by the following formula:
EPI -
GDP/PC ma;t(GDP/PC)
100%,
(1)
where GDP/PC is the GDP / Per Capita value of a given country in a given year, and max (GDP/PC) is the maximum GDP/Per Capita value reached in the same year by some country in the world.
The second index BLI that we use is defined as follows:
BR
BLI =--100%,
(2)
where BR is the budget revenue of the government of the country, and GDP is the Gross Domestic Product of the given country.
The third index in this 3D index space is the Corruption Perception Index, CPI. It is an expert assessment on a 100-point scale- It characterizes the level of corruption: the higher the CPI value, the lower the level of corruption.The method for determining this index is given in [2].
For our purposes, the mathematical difference between the continuity of EPI and BLI and the discrete nature of the CPI can be neglected. We can assume that all countries in the world are located as points in some continuous index box of size 100x100x100.
Basic part
General description of terminology and statistical data. In the article [3], the axial line of the swarm of the global economy was built in the three-dimensional space of the economic indices EPI, BLI, CPI. In articles [4] and [5], the distribution of budget deviations of countries from the axial line of the global economy was investigated and the idea of some measure for the country's budgetary equilibrium in the global economy was introduced. In this regards an attempt to construct some indicator characterizing the deviation of a country's economic productivity from the axial line of the global economy, seems relevant
The purpose of the study is the introduction of a new economic index g, characterizing the deviation of the EPI of a given country from the ideal level of EPI, determined by the shape of the axiai line of the swarm of the global economy. This purpose structured the following tasks: 1) mathematical definition of the neweconomical index g,
2) calculation the value of t?for all countries according to the statistics of the pre-covid 2019;
3) building a histogram of the distribution of the pnndex according to the data of 2019; 4) study of the statistical relationshipbetween the exponent pand the index of socio-economic development a previously introduced by the authors; 5) study
of the statistical relationship between the exponent g and EPI.
The theoretical basics of the research was publications [1]r [3], [4}, [5]r [6], [7].
The practical significance of this study is to create the basics for identifying the boundaries of balanced economies for countries with different economic productivity EPI,
Usually in the annual statistics of the WB, IMF and Transparency international there are about 170 countries for which all three mentioned economic indices are known. Among these countries, the champion in terms of GDP/PC for a number of years (2016-2019) was Luxembourg, We used the GDP/PC for this country to calculate the index EPI for allcountries of the world. In fact, Luxembourg is significantly inferior in size to the GDP/PC of Monaco and Liechtenstein, But for these two countries there is no information on the CPI and BLI indices.
Our earlier detailed analysis of the global economy based on 2016-2018 years data (see, for example, [6], [7]), allowed us to propose the idea of distributing the entire scale of economic productivity of the countries of the world into threezones:"hot","warm"and "cold".The hot zone is characterized by high EPI values (and, as a rule, high CPI and BLI values). The lowest level of EP! required to classify a country as belonging to "hot" zone is recorded by us according to the EPI of Japan (33.68% in 2018,35.09% in 2019). The hot zone includes 24 countries. The list of these countries did not change in 2016-2019.The "cold" zone corresponds to the low values of the EPI index. Typically, cold zone countries have significantly lower CPI values than hot zone countries, which means higher levels of corruption in the cold zone. The "cold" zone includes about one hundred and twenty countries. This number may vary slightly from year to year: some underdeveloped countries may appear and disappear in world statistics (for example, Somalia, Venezuela, etc.}. The upper EPI I i mit for co Id zone cou ntries can cu rrently be fixed at the EPI of Romania (10.55% in 2018,11.26% in 2019). The "warm" zone corresponds to the interval along the EPI axis, limited both from the bottom and from the top (12-13% is the lower limit; 29-30% is the upper limit). Now there are 28 countries in the "warm" zone. In recent years, only one country - Argentina - has left the list of "warm" economies and sank into the "cold" zone.
In the article [8] a detailed description of the global economy of 2019was presented. This article describes in detail the methodfor identifying EPI-groups of the global economy. The EPI-group is a
CU ftj o
OJ
h-
Q-<
X
cm
-vT
s
59
tC
tC
o
X o
X
o
tC CO
60
group of countries with similar EPI scores. The method for identifying EPI-groups is based on the analysis of the distribution of the EPI distance between neighboring countries along the axis of the EPI index. To distinguish EPI-groups, a histogram of the distribution of countries according to the EPI index is also used. In total, we have identified seven EPI-groups:
- the EPi-group Hot, coinciding with the "hot" zone of the global economy;
- two EPI-groups in the zone of "warm" economies - the EPI-group UpperWarm (20<EPI<30) and the EPI-group LowWarm (12<EPI < 17). Each of these EPI-grou ps in 2018-2019 contained 14 countries;
- in the zone of "cold" economies 4 EPI-groups can be distinguished - the EPI-group UpperCold (39 countries in 2019, 4.67<EPI<11.26), the EPI-group MiddleCold (28 countries in 2019,2.21 <EPI <4.32), the EPI-group LowCold (27 countries in 2019, 0,93<EPI<2.00), the EPI-group LDC (the Least Development Countries), 22 countries in 2019,0.23<EPl<0.78).
The most significant thing that was empirically established by us in the cited works is the impossibility of the existence of an arbitrary combination of three economic indices EPI, BLI, CPI for any country in the world. Consequently, there are some undiscovered laws of the global economy, which in the form of certain inequalities allow some combinations of three economic indices and prohibit other combinations. These undiscovered laws govern the placement of one hundred and seventy countries of the world in the economic index box, forming a swarm of the world economy in this three-dimensional box.The core of this "swarm" occupies a very small part of the volume of the three-dimensional box.
The article [9] introduces the idea of the median points of EPI-groups in the three-dimensional index space EPI, BLI, CPI. In the article [3], based on the data on the median points of the EPI-groups, the axial line of the "swarm" oftheglobaleconomy was constructed. This three-dimensional curve sets a certain fun da mental trend in the functioning of the global economy, a certain form of the dominant relationship between the EPI, BLI, CPI indices. This axial line is specified using two equations, To write these equations, it is convenient to introduce one-letter designations for the three economic indices we use:
CPI^- s:;EPl jT; BLI -» z.
0)
z - Z(x) = a + -p\ 1 + Erf
(4)
where
Erf(tO
P
= vs/
e T oCt {error function).
The parameters a, p, and a 4-parameter function (4) were found in [3] by the method of least squares.
In the papers [4] and [5] we analyzed the distribution of countries' budget deviations d from the axial line of the global economy. The value dt is used as a standardized measure of the deviation of the budget of the country number i from the axial line:
dt =ñAz¿
(5)
where hzt - z, -Z0Oi and ^'s i'ie half-width
of the difference of BLI between the asymptotics of large CPI (x - «) and small CPI [k 0).
Countries with IdJ < 1 are classified by us as countries in budget equilibrium. Countries with di > 1 are countries with surplus budgets. Countries with d, < -1 are classified by us as countries with weak budgets.
According to paper [3], the projection of the axial line of the swarm of the global economy onto the plane of economic indices {CPI, EPI} has the following form:
y = H» 10"5.
(6)
In this one-letter notation, the projection of the axial line onto the (CPI, BLI) plane has the form:
In this expression, the rapidly growing function X* describes the fundamental trend of the global economy: rapid growth in the characteristic economic productivity of EPI-groups with an increase in the characteristic CPI index for the EPI-group. This fundamental trend was first identified by us in [6]. The function A(x) included in the axial line equation (6) is a little changing function of the CPI index: ffy (i.e., EPI) for different countries can differ by almost three orders of magnitude, then the factor A(x) changes no morethanthreetimes.Thex'function describes a powerful fundamental trend in the global economy, and the multiplier^ (x) describes the fine-tuning of this trend. This factor is of the order of unity. The form of the function A(x) is given in [3].
A relative productivity exponent.The purpose of this article is to study the distribution of countries by deviations of their economic productivity v from the axial line of the swarm of the global economy Y(x). To describe these deviations, we will introduce a "relative productivity exponent" g as follows:
(7)
where v, is the EPI index of some country numbered i, and Y(x.) is the y - coordinate of the axial line of the swarm of the global economy at x^xj where x is the CP I index of the same country. Earlier in [10j, [11] we introduced the parameter of the country's socio-economic equilibrium a_ as follows:
iL =
xf
(S)
(9)
(10)
equilibrium a and the relative productivity exponent g according to 2019 data. This figure represents the projection of the swarm of the global economy onto the plane of economic parameters Jg, a} This figure represents 165 countries-points of the swarm of the global economy in 2019. There are 168 points in total in this swarm in 2019. We do not show in fig. 1 three "monster" countries with a significantly disturbing socio-economic balance.The economic indices of these countries with abnormally high values of a and gare shown in table 1.
The common feature of these three countries is the extremely high level of corruption (CPI20).
In [11] it is noted that Libya and Iraq, in whose territories military clashes have been taking place for many years, strictly speaking, should not be present at all in world economic statistics. The specificity of Equatorial Guinea is also briefly noted in [11].
This parameter characterizes the correspondence between the state of society (it is measured by the x variable, i.e., CPI) and the productivity of the country's economy, measured by the V variable (i.e., EPI). In [10] and [11], the distribution of the countnes of the world by this parameter a was investigated.
Comparing formulas (6), (7) and (8), we can write the valuer in the following form:
* •
1 ■
• + •
• •
■ 4 * 1 1»
___J
■
The statistical relationship between economic parameters g and &■ Using the economic parameters g and & that we introduced, we try to quantify the relationship between the state of society in a given country (it is characterized using the variable x, i.e.,CPI) andthe productivity of the economy of a given country (it is characterized using the variable y, i.e., EPI), The definition of g (9) includes the "fine-tuning function'Mfx), which characterizes the local behavior of the axial line of the swarm of the global economy. The definition of the socio-economic equilibrium parameter a (8) does not include the function A(x}. If the function Afx} wereconstant, then from (9) there would follow a rigid functional connection between d andg:
Fig. 1. Projection ofthe2019swarm of the global economy onto the plane of parameters g, a, where g is a relative productivity indicator, <i isa parameter of the socio-economic equilibrium
Table 1. Economic indices of countries with significantly disturbed socio-economic equilibrium
(2019, &>"\Q,g>3)
Country & a EPI BLI CPI
Equatorial Guinea Libya 43,27 4.831 7.09 17.91 16
25,52 4.303 6.70 104 18
Iraq 12,98 3.62 5.19 36.49 20
But since A(x) is not a constant value, the functional relationship (10) is "blurred" by statistical deviations.
We show in fig. 1 the statistical relationship between the parameter of socio-economic
cu ftj o
OJ
h-Q_
< X
cm
-vT
i
61
Distribution of countries by the relative productivity exponent. Fig. 2 shows a histogram of the distribution of countries in 2019 by the relative productivity exponent This histogram is constructed as follows. The entire range of possible £ values from gmjn =-3.017 (Rwanda) to gmex =4.831 (Equatorial Guinea) is divided into 60 equal intervals Ag - 0.1308 wide. The height of the column in Fig. 2 shows the number of countries with ag value within a given half-open interval A3. The left side belongs to the interval, the right does not belong to it, exceptfor the last
interval. This figure clearly shows the "central array" of the histogram, which can be called "countries with a balanced economy". This array (-1.2 < g < 0.9} contains 114 countries.
This histogram also shows a compact array of countries with increased g values (1.1 < g < 2.35, 28 countries). We will speak of these countries as having a "PIus-type-imbalance in terms of relative productivity exponent".
This histogram also shows a compact array of countries with low g values (-2.1 <, g £ -1.3, 19 countries).
Fig. 2. A histogram of the distribution of countries by the relative productivity indicator
As isolated points in the histogram in fig. 2, there are two ultra-low productivity countries. These are Rwanda (#=-3.017, a =0.04) and Burkina Fa so (£=-2.402,3=0.11).
• ■ •
•
*
ft'. • t
fit* • * \m • • * •
y * i * in
*
Fig. Projection of the 2019 swarm of the global economy onto the plane of econom ic pa ra meters {EPI, 0
This histogram contains 5 countries with abnormally high values g (g>2.6) as isolated points. In addition to the three "monster" countries shown in Table 1, this group of five
countries also includes Congo, Rep. also called Congo-Brazzaville ¡£=2.745, £=5.38) and Russian Federation (#=2,645, d=6.57). Congo, Rep., like Equatorial Guinea, is a large oil producer with a highly uneven distribution of income within the country (Gini Index is equal to 48.9,2011 estimate [12]}. In addition, the country has been burdened in the past with the Marxist-Leninist model of governance (1969-1992).
The economy of the Russian Federation is also heavily dependent on oil and gas production.The distribution of income in the Russian Federation is also very uneven. Gini's index is 41.1 (2019) [13].
The histogram in fig. 2 includes all countries in the world with well-known economic indices. This histogram, accumulating all information about the global economy, gives too wide range for a "productivity-balanced economy". Fig. 3 shows the projection of the swarm of the global economy onto the plane of economic indices {EPI, g}. This figure shows that with decreasing EPI, the spread of countries in terms of g increases. It seems that for each EPI-group it is possible to set a certain limit value glim>0 such that all countries of this EPI-group with \g\-<gUm can be considered as countries with a balanced economy. You can see in fig. 3 that the lowest Rvalue can be set in the EPI-group Hot (EPI>35%), With a decrease in the characteristic EPI value, the ghm value for EPI-groups increases (the spread of £ values increase).
Conclusions
A new economic index - the relative productivity exponent # - has been introduced. It characterizes the deviation of a country's economic productivity from some ideal productivity.This ideal productivity is determined by the shape of the axial line of the swarm of the global economy in the three-dimensional space of the economic indices EPI, BLI, CPI, The distribution of countries is investigated by the relative productivity exponent. A histogram of the distribution of countries in 2019 by relative productivity exponent was built. On this histogram, the central massif is highlighted, which owns countries with a "balanced economy" (more than a hundred countries). The statistical relationship between EPI indices and relative productivity exponent has been studied.
iiiliiiliSil
iipiiisi
— ® **a ***
References:
1. Сейдаметова З.С. Глобальная экономика в презентационных пространствах экономических индексов / З.С. Сейдаметова, 6.А.Темненко//Ученые записки Крымского инженерно-педагогичес-когоуниверситета,- 2020. - № 3(69). - С 156-161.
2. Explanation of how individual country scores of the Corruption Perceptions index are calculated [e-resource],-URL; bitly/3q7eYYe
3. Seidametova Z.S. The axial line of the global economy "swarm" in the space of economic indices EF'I, BU, CPI / Z. S. Seidametova, V, A. Temnenko // KANT, № 3 (40), 2021. - С 77-84,
4. Seidametova Z.S. A budget deviations parameter and nuclei of an equilibrium for the EPI-groups in global economy, i, "Hot" and "Warm" economies / Z.S.Seidametova, V, A.Temnenко//Ученые записки Крымского инженерно-педагогического университета, MM (74), 2021. - С. 167-175.
5. Seidametova Z.S. A budget deviations parameter and nuclei of an equilibrium for the EPI-groups in global economy. il. "Cold" economies / Z.S. Seidametova, // Ученые записки Крымского инженерно-педагогического университета, MM (74), 2021. - С. 175-182.
6. Сейдаметова З.С. Распределение стран с "тёплой" экономикой в пространстве экономических индексов EPI, ВЦ CPI / З.С. Сейдаметова //Ученые записки Крымского инженерно-педагогического университета. - 2020. - № 1 (67). - С. 174-183.
7. Сейдаметова З.С. Мировая экономика 2018 года е трехмерном пространстве экономических ин дексов: стабильность ядра "горячих" экономик /
З.С. Сейдаметова // Национальные экономические системы в контексте формирования глобального экономического пространства: сб. науч.тр. / под общ. ред. д.э.н., профессора З.О. Адамановой. - Вып. б. - Симферополь: АРИАЛ, 2020,- С 608-613.
8. Seidametova Z.S. Global economy in the space of economic i ndtces EP(,BU,CPlin2019/Z.S. Seidametova // Ученые записки Крымского инженерно-педагогического университета. - 2020. - № 4 (70). - С. 192-199.
9. Seidametova Z.S. EPI-groups of the 2019 global economy in the s pace of economic i ndices, I. "Hot" a hd "warm" economies / Z. S. Seida metova, V.A.Tem nen ko // Ученые записки Крымского инженерно-педагогического университета. - 2021. - МО 2 (72). - С. 179-188.
10. Seidametova Z.S. Parameter of the socioeconomic equilibrium of a country in the global economy "swarm". I. Hot and warm economies / Z. S. Seidametova, V, A. Temnenko // Ученые записки Крымского инженерно-педагогического университета, - 2021. - М» 3 (73). - С 120-128.
11. Seidametova Z.S, Parameter of the socio-economic equilibrium of a country in the global economy "swarm". II. Cold economies / Z.S. Seidametova // Ученые записки Крымского инженерно-педагогичес-когоуниверситета. - 2021. - № 3 (73). - С. 128-134.
12. Congo, Republic of the [e-resource].- URL: bit.ly/ 3qZGXZ5
13. Коэффициент Джин ни в России [e-resource], -U R L; htt ps;// г их ре rt, гц/Сгат и сти ка; К оэф ф и ци е нт_-Джин и_в_России
CU
ftj О OJ
h-
0-
<
X
сч
-vT
i
63
OBLIGA T/ONS OF A UTONOMOUS INSTITUTIONS: THEORETICA LAND A CCOUNTING ASPECTS
Turishcheva Tatyana Borisovna, PhD of Economics, Associate Professor, Russian Economic University. С. V. Plekhanov; Associate Professor of the Department of Audit and Corporate Reporting, Financial University under the Government of the Russian Federation, Moscow
To date, in modern economic conditions one of the most difficult and controversial accounting issues can be considered accounting obligations, institutions that are maintained at the expense of budgetary funds, which is largely due to the aggravation of non-payment problems, in the deepening of the payment crisis contributes its share and the lack of regulation of the budget system, which concerns the untimely payment of public obligations, which are carried out by autonomous institutions. In this context, the purpose of the article is to consider from theoretical and accounting points of view the obligations of autonomous institutions. As a result of the Study different classification attributes and substantive aspects of the obligations of autonomous institutions are highlighted. Ai so, special attention is paid to the issues of accounting and recognition of obligations, some features of which, are considered on specific examples, namely: the accounting of obligations arising in the process of operations for the supply of goods, works, services and rent.
Keywords: autonomous institution; accounting; obligations; content; valuation; recognition; accounts; settlements; delivery; tent.
DOI 10.24923/2222 243X.2022 42.11
ОБЯЗА ТЕЛЬСТВА АВТОНОМНЫХ УЧРЕЖДЕНИЙ: уд к 657.6
ТЕОРЕТИЧЕСКИЕ И УЧЕТНЫЕ АСПЕКТЫ ВАК РФ 5.2.4/08.00.10
На сегодняшний день в современных условиях хозяйствования одним из наи- ф Турищева Т.Е., 2022 более сложных и спорных вопросов учета можно считать учет обязательств учреждений, которые содержатся за счет средств бюджета, что в значительной степени связано с обострением проблем неплатежей, в углубление платежного кризиса вносит свою долю и неурегулированность бюджетной системы, что касается несвоевременной оплаты государственных обязательств, которые
