Research of Reasons for Human Development Index Growth by GMDH
The goal of this paper is modeling of influence of macroeconomic factors on the growth of national income as a component of human development index. Indicators influencing national income growth were analyzed. Models that give possibility to analyze what macroeconomic indicators are the most influen...
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irk-123456789-836642015-06-22T03:02:15Z Research of Reasons for Human Development Index Growth by GMDH Tutova, O. Savchenko, E. Наукові статті The goal of this paper is modeling of influence of macroeconomic factors on the growth of national income as a component of human development index. Indicators influencing national income growth were analyzed. Models that give possibility to analyze what macroeconomic indicators are the most influential for the national income growth were developed. Also these models enable to assess how national income will change with changing given indicator. Метою даної роботи є моделювання впливу макроекономічних факторів на зростання національного доходу як компонент індексу розвитку людського потенціалу. Були проаналізовані показники, що впливають на зростання національного доходу. Розроблено моделі, які дають можливість проаналізувати те, що макроекономічні показники є найбільш впливовим для зростання національного доходу. Крім того, ці моделі дозволяють оцінити, наскільки національний дохід буде мінятися при зміні даного показника Целью данной работы является моделирование влияния макроэкономических факторов на рост национального дохода в качестве компонента индекса развития человеческого потенциала. Были проанализированы показатели, влияющие на рост национального дохода. Разработаны модели, которые дают возможность проанализировать то, что макроэкономические показатели являются наиболее влиятельным для роста национального дохода. Кроме того, эти модели позволяют оценить, насколько национальный доход будет меняться при изменении данного показателя. 2013 Article Research of Reasons for Human Development Index Growth by GMDH / O. Tutova, E. Savchenko // Індуктивне моделювання складних систем: Зб. наук. пр. — К.: МННЦ ІТС НАН та МОН України, 2013. — Вип. 5. — С. 120-129. — Бібліогр.: 7 назв. — англ. XXXX-0044 http://dspace.nbuv.gov.ua/handle/123456789/83664 681.513; 004.942 en Індуктивне моделювання складних систем Міжнародний науково-навчальний центр інформаційних технологій і систем НАН та МОН України |
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Наукові статті Наукові статті Tutova, O. Savchenko, E. Research of Reasons for Human Development Index Growth by GMDH Індуктивне моделювання складних систем |
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The goal of this paper is modeling of influence of macroeconomic factors on the growth of national income as a component of human development index. Indicators influencing national income growth were analyzed. Models that give possibility to analyze what macroeconomic indicators are the most influential for the national income growth were developed. Also these models enable to assess how national income will change with changing given indicator. |
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Tutova, O. |
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Research of Reasons for Human Development Index Growth by GMDH |
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Research of Reasons for Human Development Index Growth by GMDH |
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Research of Reasons for Human Development Index Growth by GMDH |
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Research of Reasons for Human Development Index Growth by GMDH |
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Research of Reasons for Human Development Index Growth by GMDH |
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research of reasons for human development index growth by gmdh |
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Міжнародний науково-навчальний центр інформаційних технологій і систем НАН та МОН України |
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Research of Reasons for Human Development Index Growth by GMDH / O. Tutova, E. Savchenko // Індуктивне моделювання складних систем: Зб. наук. пр. — К.: МННЦ ІТС НАН та МОН України, 2013. — Вип. 5. — С. 120-129. — Бібліогр.: 7 назв. — англ. |
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Індуктивне моделювання складних систем |
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2025-07-06T10:28:52Z |
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Research of Reasons for Human Development Index
УДК 681.513; 004.942
RESEARCH OF REASONS FOR HUMAN
DEVELOPMENT INDEX GROWTH BY GMDH
Tutova O., Savchenko E.
International Research and Educational Center of Information Technologies and Systems of
NAS of Ukraine, pr. Academika Glushkova, 40, Kyiv, 03680, Ukraine
savchenko@irtc.org.ua, sir_ludovick@yahoo.com
Метою даної роботи є моделювання впливу макроекономічних факторів на зростання
національного доходу як компонент індексу розвитку людського потенціалу. Були
проаналізовані показники, що впливають на зростання національного доходу. Розроблено
моделі, які дають можливість проаналізувати те, що макроекономічні показники є найбільш
впливовим для зростання національного доходу. Крім того, ці моделі дозволяють оцінити,
наскільки національний дохід буде мінятися при зміні даного показника
Ключові слова: комбінаторний алгоритм МГУА, індекс людського розвитку,
макроекономічні показники
The goal of this paper is modeling of influence of macroeconomic factors on the growth of national
income as a component of human development index. Indicators influencing national income
growth were analyzed. Models that give possibility to analyze what macroeconomic indicators are
the most influential for the national income growth were developed. Also these models enable to
assess how national income will change with changing given indicator.
Keywords: combinatorial GMDH algorithm, human development index, macroeconomic data
Целью данной работы является моделирование влияния макроэкономических факторов на
рост национального дохода в качестве компонента индекса развития человеческого
потенциала. Были проанализированы показатели, влияющие на рост национального дохода.
Разработаны модели, которые дают возможность проанализировать то, что
макроэкономические показатели являются наиболее влиятельным для роста национального
дохода. Кроме того, эти модели позволяют оценить, насколько национальный доход будет
меняться при изменении данного показателя.
Ключевые слова: анализ, комбинаторный алгоритм МГУА, индекс развития человеческого,
макроэкономические показатели
1. Introduction
Twenty years ago, the Human Development Index (HDI) was proposed as an
alternative to conventional assessments of development based on measures of per
capita income. It complements income with health and education indicators. HDI
classifications are relative – based on quartiles of HDI distribution across countries
and denoted very high, high, medium and low HDI. Because there are 187 countries,
the four groups do not have the same number of countries: the very high, high and
medium HDI groups have 47 countries each, and the low HDI group has 46 countries
[1-4].
The first Human Development Report introduced a new way of measuring
development by combining indicators of life expectancy, educational attainment and
Індуктивне моделювання складних систем, випуск 5, 2013 120
mailto:savchenko@irtc.org.ua
_____________________ Tutova O., Savchenko E.
income into the composite HDI. The breakthrough for the HDI was the creation of a
single statistic which was to serve as a frame of reference for both social and
economic development. The HDI sets a minimum and a maximum for each
dimension, called goalposts, and then shows where each country stands in relation to
these goalposts, expressed as a value between 0 and 1.
The education component of the HDI is now measured by mean of years of
schooling for adults aged 25 years and expected years of schooling for children of
school entering age. Mean years of schooling is estimated based on educational
attainment data from censuses and surveys available in the UNESCO Institute for
Statistics database. Expected years of schooling estimates are based on enrolment by
age at all levels of education and population of official school age for each level of
education. Expected years of schooling are capped at 18 years. The indicators are
normalized using a minimum value of zero and maximum values are set to the actual
observed maximum value of mean years of schooling from the countries in the time
series, 1980–2012, that is 13.3 years estimated for the United States in 2010.
Expected years of schooling are maximized by its cap at 18 years. The education
index is the geometric mean of two indices.
The life expectancy at birth component of the HDI is calculated using a
minimum value of 20 years and maximum value of 83.57 years. This is the observed
maximum value of the indicators from the countries in the time series, 1980–2012.
Thus, the longevity component for a country where life expectancy birth is 55 years
would be 0.551.
For the wealth component, the goalpost for minimum income is $100 (PPP) and
the maximum is $87,478 (PPP), estimated for Qatar in 2012.
Purchasing power parity (PPP) is an economic theory and a technique used to
determine the relative value of currencies, estimating the amount of adjustment
needed on the exchange rate between countries in order for the exchange to be
equivalent to (or on par with) each currency's purchasing power. It asks how much
money would be needed to purchase the same goods and services in two countries,
and uses that to calculate an implicit foreign exchange rate. Using that PPP rate, an
amount of money thus has the same purchasing power in different countries.
The decent standard of living component is measured by Gross National Income
(GNI) per capita (PPP$) instead of Gross Domestic Product (GDP) per capita (PPP$)
The HDI uses the logarithm of income, to reflect the diminishing importance of
income with increasing GNI. The scores for the three HDI dimension indices are then
aggregated into a composite index using geometric mean.
The HDI facilitates instructive comparisons of the experiences within and
between different countries.
2. Description of Macroeconomic Data
10 countries with different levels of human development from different regions
were chosen in order to explore the reasons for their remarkable progress in rating of
HDI. Hong Kong, Special Administrative Region of China, and Singapore have very
Індуктивне моделювання складних систем, випуск 5, 2013 121
Research of Reasons for Human Development Index
high level of human development. Belarus, Saudi Arabia, Bolivarian Republic of
Venezuela, Islamic Republic of Iran, and Ecuador have high level of human
development. Ghana and United Republic of Tanzania have respectively medium and
low level of human development. HDI for these countries in 2005-2012 is presented
in the Table 1.
Table 1
Human development index (HDI) value
Country 2005 2006 2007 2008 2009 2010 2011 2012
Hong Kong, 0,857 0,865 0,877 0,892 0,894 0,9 0,904 0,906
Singapore 0,852 0,863 0,872 0,887 0,877 0,892 0,894 0,895
Chile 0,789 0,791 0,8 0,807 0,808 0,813 0,817 0,819
Belarus 0,73 0,743 0,756 0,768 0,78 0,785 0,789 0,793
Venezuela 0,694 0,703 0,712 0,738 0,741 0,744 0,746 0,748
Iran 0,685 0,704 0,706 0,717 0,723 0,74 0,742 0,742
Ecuador 0,682 0,686 0,688 0,715 0,716 0,719 0,722 0,724
Ghana 0,491 0,493 0,506 0,52 0,534 0,54 0,553 0,558
Tanzania 0,395 0,401 0,408 0,414 0,458 0,466 0,47 0,476
Source: Human Development Index (HDI) value: HDRO calculations based on
data from UNDESA (2011), Barro and Lee (2011), UNESCO Institute for Statistics
(2012), World Bank (2012) and IMF (2012).
Singapore data from 2006 till 2008 were omitted in the Table 1. Combinatorial
algorithm GMDH was used for modelling to restore those values [5, 6]. They are
shown in italics in the Table 1. Models of dependency of restored variable on all
others were developed for this purpose. Therefore, we should build dependency of
the following type:
20122011201020092008200720052006 ,,,,,, HDIHDIHDIHDIHDIHDIHDIHDI = .
This model is obtained for 2007:
201220052007 575,04818,00538,0 HDIHDIHDI ++−= ,
parameters of model: 000109,0=AR ; 00307,0=BS .
Similarly three omitted values for Singapore and other gaps of different
parameters were restored.
All these countries differ in many ways but they all can be considered
developmental states. The recent literature on developmental states has grown out of
the experiences of the East Asian “miracle” economies: Japan before the Second
World War and Hong Kong, China (SAR), the Republic of Korea, Singapore and
Taiwan Province of China in the second half of the 20th century. Common traits
include promoting economic development by explicitly favoring certain sectors;
commanding competent bureaucracies; placing robust, competent public institutions
at the centre of development strategies; clearly articulating social and economic
goals; and deriving political legitimacy from their record in development.
Індуктивне моделювання складних систем, випуск 5, 2013 122
_____________________ Tutova O., Savchenko E.
That some East Asian developmental states were not democracies has
prompted many to think that the developmental state model is also autocratic. But
evidence of the relationship between authoritarianism and development is mixed.
Democratic countries such as Japan and the United States have functioned as
developmental states. Since the 1950s, the Scandinavian countries have also acted as
a type of developmental state, where political legitimacy is derived from the welfare
state and full employment rather than from rapid growth. The Swedish state
developed strategic sectors through public private partnerships (iron and steel,
railways, telegraphs and telephone, and hydroelectric power). It also provided
targeted protection to support the emergence of heavy industries, promoting research
and development. Its welfare policy was closely integrated with strategies to promote
structural change towards high-productivity sectors [1].
Stated above 10 countries have experienced significant growth of GNI for
2005-2012.
GNI per capita income in PPP terms is an aggregate income of an economy
generated by its production and its ownership of factors of production, less the
incomes paid for the use of factors of production owned by the rest of the world,
converted to international dollars using purchasing power parity (PPP) rates, divided
by midyear population. It is presented in the Table 2.
Table 2
Gross National Income (GNI) per capita
Country 2005 2006 2007 2008 2009 2010 2011 2012
Hong Kong, 35,720 38,643 41,057 42,591 40,393 42,591 45,160 45,598
Singapore 42,330 46,112 48,344 49,075 47,502 51,259 52,439 52,613
Chile 11,600 11,678 12,294 13,097 12,942 13,551 14,407 14,987
Belarus 8,540 9,407 10,187 11,311 11,329 12,245 12,770 13,385
Saudi Arabia 20,780 20,896 20,580 20,964 20,552 20,858 21,812 22,616
Venezuela 9,770 10,656 11,599 11,891 11,210 10,848 11,068 11,475
Iran 9,060 9,503 10,177 10,316 10,390 10,834 10,936 10,695
Ecuador 6,190 6,423 6,458 6,936 6,863 7,073 7,288 7,471
Ghana 1,190 1,075 1,130 1,225 1,394 1,451 1,596 1,684
Tanzania 1,050 1,095 1,149 1,197 1,230 1,288 1,324 1,383
Source: GNI per capita in PPP terms (constant 2005 international $): HDRO
calculations based on data from World Bank (2012), IMF (2012) and UNSD (2012).
Since GNI is important component of HDI, it is valuable to determine what
factors influence income and to measure their impact. Four influential factors were
chosen. The Organization for Economic Co-operation and Development defines the
employment rate as the employment-to-population ratio (shown in the Table 3).
Table 3
Employment to population ratio
Country 2005 2006 2007 2008 2009 2010 2011
Hong Kong, 60,8 61,4 61,9 62 61,1 60,9 61,2
Singapore 66,3 67,7 68,7 69,3 68,5 69 69,2
Індуктивне моделювання складних систем, випуск 5, 2013 123
Research of Reasons for Human Development Index
Chile 58,3 59 59,8 60,6 59,6 62,3 62,9
Belarus 55,6 55,2 54,8 54,4 53,8 54,2 54,4
Saudi Arabia 61,2 60,4 60,8 60,6 60 59,9 59,7
Venezuela 66,8 67,7 68,4 68,9 68,4 68 68,1
Iran 49 48,3 47,9 45,7 46 46,2 46,1
Ecuador 72,2 73,1 72,4 70,8 70,7 71,2 71,5
Ghana 82,1 81,2 81,3 81,4 81,4 81,5 81,3
Tanzania 84,3 84,5 84,4 84,4 84,4 84,4 84,2
Source: Employment to population ratio, population 25+: ILO (2012). ["Key
Indicators on the Labour Market: 7th edition". Geneva:
ILO.].http://www.ilo.org/empelm/what/lang--en/WCMS_114240. Accessed March
2012.
This is a statistical ratio that measures percentage of the population ages 25
years or older that is employed. This includes people that have stopped looking for
work. The International Labor Organization states that a person is considered
employed if they have worked at least 1 hour in "gainful" employment in the most
recent week.
Employed persons are all those who, do any work at all as paid employees, work
in their own business or profession or on their own farm, or work 15 hours or more as
unpaid workers in a family-operated enterprise; and all those who do not work but
had jobs or businesses from which they were temporarily absent due to illness, bad
weather, vacation, childcare problems, labor dispute, maternity or paternity leave, or
other family or personal obligations – whether or not they were paid by their
employers for the time off and whether or not they were seeking other jobs.
Unemployed persons are all those who, have no employment during the
reference week; are available for work, except for temporary illness; and have made
specific efforts, such as contacting employers, to find employment sometime during
the past 4-week period.
Included in the group ‘Not in the labor force’ are all persons in the civilian non-
institutional population who are neither employed nor unemployed. Information is
collected on their desire for and availability to take a job at the time of the interview,
job search activity in the prior year, and reason for not looking for work in past 4-
week period.
Multiple jobholders are employed persons who, have two or more jobs as a
wage and salary worker, are self-employed and also held a wage and salary job, or
work as an unpaid family worker and also hold a wage and salary job.
Foreign direct investment presented in the Table 4 is a sum of equity capital,
reinvestment of earnings, other long-term capital and short-term capital, expressed as
a percentage of GDP. It is a direct investment into production or business in a country
by a company in another country, either by buying a company in the target country or
by expanding operations of an existing business in that country. Foreign direct
investment is in contrast to portfolio investment which is a passive investment in the
securities of another country such as stocks and bonds.
Індуктивне моделювання складних систем, випуск 5, 2013 124
_____________________ Tutova O., Savchenko E.
Table 4
Foreign direct investment, net inflows (% of GDP), (%)
Country 2005 2006 2007 2008 2009 2010
Hong Kong, 18,9 23,7 26,3 27,7 25 31,7
Singapore 12,5 21,1 22 5,1 8,7 18,1
Chile 5,7 4,7 7,2 8,4 7,5 7
Belarus 1 1 4 3,6 3,8 2,5
Saudi Arabia 3,8 5,1 6,3 8,3 9,7 4,8
Venezuela 1,9 -0,3 0,7 0,4 -0,8 0,3
Iran 1,6 0,7 0,6 0,5 0,9 1,6
Ecuador 1,3 0,7 0,4 1,9 0,6 0,3
Ghana 1,4 3,1 5,6 9,5 5,5 7,9
Tanzania 6,6 2,8 3,5 1,9 1,9 1,9
Source: Foreign direct investment, net inflows (% of GDP): World Bank
(2012a). "World Development Indicators 2012." Washington, D.C.: World Bank.
http://data.worldbank.org. Accessed April, 2012.
Foreign direct investment has many forms, broadly, foreign direct investment
includes mergers and acquisitions, building new facilities, reinvesting profits earned
from overseas operations and company loans. In a narrow sense, foreign direct
investment refers just to building new facilities.
Total dependency ratio shown in the Table 5 is ratio of the sum of the
population ages 0–14 and ages 65 and older to the population ages 15–64. Countries
that have a high dependency ratio have more people who are not of working age, and
fewer who are working and paying taxes. The higher the number, the more people
that need to be looked after.
Table 5
Total dependency ratio
Country 2005 2006 2007 2008 2009 2010 2011 2012
Hong Kong, 35,9 35,1 34,2 33,4 32,6 32 32,1 32,3
Singapore 39 38,2 37,5 36,8 36,3 35,9 35,6 35,4
Chile 49,2 48,4 47,6 46,8 46,2 45,7 45,4 45,2
Belarus 43 42,3 41,5 40,8 40,3 40 40,2 40,5
Saudi Arabia 57,6 55,1 53,3 52 50,9 49,9 49,5 49
Venezuela 56,9 56,2 55,5 54,9 54,4 54 53,6 53,3
Iran 45,2 43,3 41,8 40,7 39,8 39,2 38,9 38,7
Ecuador 60,9 60,2 59,5 58,9 58,3 57,7 57 56,3
Ghana 76,1 75,7 75,2 74,6 74,1 73,6 73,3 73
Tanzania 90,6 90,9 91,1 91,3 91,5 91,8 92,2 92,6
Source: Total dependency ratio: UNDESA (2011). 2010 Revision of World
Population Prospects.
Total reserves minus gold shown in the Table 6 is a sum of special drawing
rights, reserves of International Monetary Fund (IMF) members held by the IMF and
Індуктивне моделювання складних систем, випуск 5, 2013 125
Research of Reasons for Human Development Index
holdings of foreign exchange under the control of monetary authorities, excluding
gold holdings, expressed as a percentage of GDP.
Table 6
Total reserves minus gold
Country 2005 2006 2007 2008 2009 2010 2011
Hong Kong, 69,9 70,1 73,7 84,7 122,2 119,7 117,1
Singapore 93,9 97,8 96,6 104,3 106,6 105,8 99,1
Chile 13,8 12,5 9,7 12,8 14,6 12,9 16,9
Belarus 3,8 2,9 8,7 4,4 9,8 6,2 10,9
Saudi Arabia 49,1 63,4 79,4 92,9 108,8 98,7 93,7
Venezuela 16,4 16 10,5 10,5 6,6 3,3 3,1
Iran 3,2 5,2 7,6 8,4 12,2 20,1 16,3
Ecuador 4,6 3,6 6,2 6,9 5,5 2,5 2,5
Ghana 16,4 10,3 8,1 6,2 13 14,8 14
Tanzania 14,5 15,8 17,2 13,8 16,2 17 15,7
Source: Total reserves minus gold: World Bank (2012a). "World Development
Indicators 2012." Washington, D.C.: World Bank. http://data.worldbank.org.
Accessed April, 2012.
3. GNI Growth Modeling
The most influential factors for HDI were chosen for research of their impact
on GNI growth for all 10 countries. Values of pair correlation between HDI and all
other parameters were calculated for that purpose. Those parameters for which the
value of pair correlation was more than 0.9 were selected. Since GNI shows the level
of prosperity, it was chosen as an output variable:
y - gross national income per capita.
Four most influential factors were selected:
1x - employment to population ratio;
2x - foreign direct investment, net inflows (% of GDP), (%);
3x - total dependency ratio;
4x - total reserves minus gold.
Two options of models – regression model by least square method and model
by combinatorial algorithm GMDH – were developed. Models for Belarus, Iran, and
Tanzania are presented below.
This model is obtained with least square method:
4321 066,0777,1174,0181,1292,19 xxxxy −−++= .
This model is obtained with combinatorial algorithm GMDH by regularity
criterion with after-determination by bias error criterion [7]:
31 109,2643,1926,7 xxy −+= .
Parameters of model: ;014,0=AR .310,0=BS
Індуктивне моделювання складних систем, випуск 5, 2013 126
_____________________ Tutova O., Savchenko E.
Results of modeling by least square method (LSM) and combinatorial
algorithm GMDH (Combi) for Belarus are presented in the Table 7.
Table 7
Influence of those four factors on GNI for Belarus
Belarus 1x 2x 3x 4x y )(mod LSMy )(mod Combiy
2005 55,6 1 43 3,8 8,54 8,4891 8,5348
2006 55,2 1 42,3 2,9 9,407 9,3202 9,3545
2007 54,8 4 41,5 8,7 10,187 10,4077 10,3852
2008 54,4 3,6 40,8 4,4 11,311 11,3948 11,2050
2009 53,8 3,8 40,3 9,8 11,329 11,25083 11,27435
2010 54,2 2,5 40 6,2 12,245 12,2687 12,5643
2011 54,4 7,2 40,2 10,9 12,77 12,6576 12,4708
1x and turned out to be the most influential factors for Belarusian GNI.
Furthermore, increase of employment to population ratio to the level of 2005 will
increase GNI by approximately 11 %. And increase of total dependency ratio to the
level of 2005 will have the same effect.
3x
Similarly models for Iran are obtained. This model is obtained with least
square method:
4321 039,0212,0205,0048,0428,16 xxxxy +−−+= .
This model is obtained with combinatorial algorithm GMDH by regularity
criterion:
431 0026,035,0111,0434,19 xxxy −−+= .
Parameters of model: ;0166,0=AR .428,0=BS
Results of modeling by least square method (LSM) and combinatorial
algorithm GMDH (Combi) for Iran are presented in the Table 8.
Table 8
Influence of those four factors on GNI for Iran
Iran 1x 2x 3x 4x y )(mod LSMy )(mod Combiy
2005 49 1,6 45,2 3,2 9,06 9,0159 9,02899
2006 48,3 0,7 43,3 5,2 9,503 9,6480 9,61183
2007 47,9 0,6 41,8 7,6 10,177 10,0618 10,0868
2008 45,7 0,5 40,7 8,4 10,316 10,2412 10,2259
2009 46 0,9 39,8 12,2 10,39 10,5147 10,5648
2010 46,2 1,6 39,2 20,1 10,834 10,821 10,777
2011 46,1 0,7 38,9 16,3 10,936 10,9134 10,8807
For Iran increase of employment to population ratio to the level of 2005 will
lead to increase of the GNI by 1% and increase of total reserves to the level of 2010
will have the same influence.
Індуктивне моделювання складних систем, випуск 5, 2013 127
Research of Reasons for Human Development Index
This model is obtained with least square method for Tanzania:
4321 0004,0212,0008,02,0736,35 xxxxy −+++−= .
This model is obtained with combinatorial algorithm GMDH by regularity
criterion:
43 0008,018,03,15 xxy ++−= .
Parameters of model: 005,0=AR ; 464,0=BS .
As fertility levels decline, the dependency ratio falls initially because the
proportion of children decreases while the proportion of the population of working
age increases. The period when the dependency ratio declines is known as the
“window of opportunity” when a “demographic dividend” may be reaped because
society has a growing number of potential producers relative to the number of
consumers. However, as fertility levels continue to decline, dependency ratios
eventually increase because of the proportion of working age starts declining and the
proportion of older persons continues to increase. As populations grow older,
increases in old-age dependency ratios are indicators of the added pressures that
social security and public health systems have to withstand. Tanzania and Ghana may
face this challenge in future.
Results of modeling by least square method (LSM) and combinatorial
algorithm GMDH (Combi) for Tanzania are presented in the Table 9.
Table 9
Influence of those four factors on GNI for Tanzania
Tanzania 1x 2x 3x 4x y )(mod LSMy )(mod Combiy
2005 84,3 6,6 90,6 14,5 1,05 1,0484 1,0554
2006 84,5 2,8 90,9 15,8 1,095 1,1176 1,1106
2007 84,4 3,5 91,1 17,2 1,149 1,1411 1,1478
2008 84,4 1,9 91,3 13,8 1,197 1,1868 1,1811
2009 84,4 1,9 91,5 16,2 1,23 1,2203 1,2192
2010 84,4 1,9 91,8 17 1,288 1,2827 1,274
2011 84,2 1,9 92,2 15,7 1,324 1,3361 1,345
Conclusions
Ten countries with different levels of human development from different
regions were chosen in order to explore the reasons for their remarkable progress in
the rating of HDI during 2005-2012. HDI growth means growth of the per capita
income along with improvement in the field of education and health care. Since the
gross national per capita income characterizes decent standard of living, it was
chosen as the main component of HDI for research.
For that purpose macroeconomic data influencing the gross national per capita
income were analyzed. Values of pair correlation between HDI and all other
parameters were calculated for that. Impact of such indicators as employment to
Індуктивне моделювання складних систем, випуск 5, 2013 128
_____________________ Tutova O., Savchenko E.
population ratio, total dependency ratio, amount of foreign direct investment, and
amount of total reserves minus gold on the gross national per capita income was
explored by the example of Belarus, Iran, and Tanzania. Two types of economical
and mathematical models were developed for that. Regression model was built by
least square method, and the other model was built by combinatorial algorithm
GMDH by regularity criterion with after-determination by bias error criterion.
Both models display that employment to population ratio and total dependency
ratio are turned to be the most influential indicators for growth of the gross national
income in Belarus. Thus, increase of employment to population ratio to the level of
2005 will increase the GNI by approximately 11 %. And increase of total dependency
ratio to the level of 2005 will have the same effect. For Iran increase of employment
to population ratio to the level of 2005 will lead to increase of the GNI by 1% and
increase of total reserves to the level of 2010 will increase the GNI by 1% as well.
Total dependency ratio has the most significant impact on the GNI of Tanzania.
References
1. Human Development Report 2013 / [Електронний ресурс] -
http://hdr.undp.org/en/reports/global/hdr2013
2. Тутова О.В. Концептуальні основи формування людського капіталу //
Економіко-математичне моделювання соціально-економічних систем. Збірник
наукових праць. Вип. 17 – Київ: Міжнародний науково-навчальний центр
інформаційних технологій та систем НАН України і МОН України, 2012. – 379
с. – С. 119-129.
3. Savchenko Ie., Tutova O. Analysis of Human Development Level by
Inductive Algorithms // Proceedings of International Workshop of Inductive
Modelling. Kyiv, 8-14 May. – 2012. – P. 28 – 33.
4. Savchenko Ie., Tutova O. Use of GMDH for Investigation of Impact of
Non-income Components on HDI. – Індуктивне моделювання складних систем,
випуск 4, 2012. – с.28-37.
5. Ivakhnenko A. G., Stepashko V.S.: Pomekhoustoichivost modelirovania
(Noise-immunity of modeling). Kiev: Naukova Dumka, 1985. – 216 p. (in Russian).
6. Ивахненко А.Г., Савченко Е.А., Ивахненко Г.А., Гергей Т.
Применение алгоритмов МГУА для восстановления пропущенных данных и
прогноза уровня глюкозы в крови при надомном мониторинге диабета //
Проблемы управления и информатики. – № 3. – 2002. – C. 123-133.
7. Савченко Е.А., Степашко В.С. Аналитическое и численное
исследование селективных свойств критерия несмещенности ошибок в задачах
индуктивного моделирования // Проблемы управления и информатики. – №2. –
2012. – С. 39-50.
Індуктивне моделювання складних систем, випуск 5, 2013 129
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