CC BY
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Ye. Popova, Post-Graduate Student, Transport and Telecommunication Institute, Latvia, Riga,
Social model type as a determinant of human capital
This paper discusses the factors that are defining for the of human capital level. The study is based on time series. The regression function are represented for the main factors of human capital. In the future, these regressions used to predict the human development index. Some dependencies provide the possibility of scientific prediction; the time period makes it possible to verify. The functions typology is performed on the basis of regression types and determination coefficients. Some factors considered for groups of countries that use the same social model. The paper discusses the Continental and Scandinavian social model.
Keywords: human capital, factors, regression, functional dependencies, forecast.
Introduction
Measuring the human capital is the difficult complex and ambiguous process. In the early 90s the group of experts of UNO Development Programme the new concept of human potential development was worked out [4]. The cornerstone of this concept is not capability of productive labour (i. e. economic value of person), but development of human as a personality via increase of options due to the growth of life expectancy, education and income. The human development is considered as a purpose and criterion of social progress, but not as a facility of economic growth. The advantage of the concept is distinguishing the fundamental criteria of social development (long life, education, income), suitable for quantitative comparison. The demographic characteristics (life expectancy, infant mortality rate) and economic indicators (GDP, CIP) were used as generalising features for a long time.
Nevertheless, the development of the world has demonstrated that the economic growth is not always followed by positive social consequences, seen in creation of favourable conditions for increase of population education level, accessibility of healthcare services, develop-
ment of sport, decrease of unemployment risk, etc [15]. That is why the system of indicators of population living standards comprises demographic and socio-economic indices nowadays. They reflect the important sides of human development. The method of calculation of these indices is improving according to international classifications, and results in the Index of the Human Capital Development (HDI), which is measured all over the world. On the basis of the above written, the human capital is a certain integral value calculated on the fundamental of numerous indicators. Undoubtedly, these components will be determining for the human capital measurement [2, 8, 9, 10]. Several researches demonstrate that the same factors are determining for social model as well [11, 12, 13, 14].
Social Model and the Human Capital Development
The society functioning within the state can be described with a special social model, showing the way how this process happens. Any social model has certain elements which can be mentioned in a flexible order: taxation, social insurance, public services, regulations [5].
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Nowadays the European social models are classified in the following way:
• Scandinavian Model (or Nordic Model, or Social-Democratic Model, or Institutional Model), distributing the social benefits among all citizens of the country;
• Anglo-Saxon Model (or Liberal Model, or Beveridge Model) distributes the social benefits among people who need this social support. There are rigid limitations for the benefits accessibility;
• Continental European Model (or Bismarck Model, or Conservative Model) states that the social support can be given to the people who have been presented on the Labour Market and who have some social funds;
• Mediterranean Model (or Subsidiary Model, or Catholic Model) assumes significant social support from the state and simultaneously dependence on person representation on the labour market [16].
For determining the exact ways of influence of the social systems on the human capital, the European countries have been grouped in accordance with the type of the social models adopted in the certain society. The Scandinavian model is represented by such countries as Denmark, Iceland, Finland, Sweden, and Norway. Germany, France, Austria, Estonia, Lithuania, Poland and Latvia present the Continental model. The Liberal model is implemented only in two countries — the United Kingdom and Ireland, and Catholic model functions in three countries — Spain, Italy and Portugal. Since this investigation is oriented on the indicators responsible for the human capital formation, development and reproduction, the research under consideration operates with these indicators only [3].
The particular task of the paper is to determine the exact social model, adoption of which facilitates comprehensively the human capital development. Further investigation deals with the countries, presenting this model and compares them with the countries, representing the Baltic region. For achieving this goal the complex HDI index (Human Development Index), computed on the basis of several indicators, has been em-
ployed. Then the average value of indicator was computed for every model. The results of these calculations are presented in tables 1, 2, 3, 4.
According to this indicator Scandinavian Model is the Model mostly facilitating the Human Capital development. Undoubtedly, this criterion is not sufficient enough basis for choosing this Model as a reference model for comparison of the regions. Nevertheless, all other indices (see Table 5), determining the level of development of different components of human capital, also demonstrate the advantage of Scandinavian Model. According to the Life Expectancy indicator the first place is taken by the Catholic Model; this fact is conditioned and explained rather by climate parameters and specific genetic peculiarities of the population of this region than by the level of medicine, education and living standards development. The table shows indicators average for the corresponding model.
Next stage has comprised construction of the correlations for all countries, chosen for representing their models. For all countries within the models the factors with high degree of correlation (from 0.8 till 1) have been found out; then the factors with weak correlations (from 0.3 till 0.79) and showing practically no correlation (from 0 till 0.29) have been discovered.
There has been used the Pearson's equation for the correlation coefficient of random variables X and Y calculation, which has the following form:
£ Ux- x)(y- y) =
(n - 1)sxsy
£ Ux- x )(y>- y)
~V£ - x )2 £ n=i(y - y )2'
where: x — a sample mean of X, y — a sample mean of Y, sx — a sample standard deviation of X, sy — a sample standard deviation of Y.
The correlations are revealed on the basis of Eurostat data [3] and Latvian Statistical Bureau [6].
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Table 1 § о
Scandinavian Model о
о.
Norway Sweden Iceland Finland Denmark Average
HDI: 0.971 0.963 0.969 0.959 0.955 0.963
Table 2
Continental Model
France Austria Germany Czech Republic Hungary Poland Estonia Lithuania Latvia average
HDI: 0.961 0.955 0.947 0.903 0.879 0.88 0.883 0.87 0.866 0.911
Table 3
Anglo-Saxon Model
Ireland UK Average
HDI: 0.965 0.947 0.956
Table 4
Catholic Model
Spain Italy Portugal Average
HDI: 0.955 0.951 0.909 0.938
Table 5
Values of indices of human capital
Index Model GEM Dem. Ind. LE QL Ed.Ind. IEF
1 2 3 4 5 6 7
Scandinavian Model 0.899 9.4 79.7 7.767 0.987 73.9
Continental Model 0.707 7.67 76.1 6.522 0.963 69.2
Liberal Model 0.75 8.48 79.2 7.625 0.971 76.6
Catholic Model 0.776 8.00 79.8 7.615 0.956 64.8
where: 1 — Human Development index (model),
2 — Gender empowerment measure,
3 — Index of Democratic development,
4 — Life expectancy index,
5 — Index of quality of life,
6 — Education index,
7 — Index of economic freedom.
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After determining the factors with practically linear dependence, the Student's criterion has been applied to them. It has allowed determining the factors with more stable basis. Since there has been comparison of factors expressed in different numbers, and numbers differ by several digits it has been necessary to reduce them to the unified system. It has been decided to use the numbers from 0 to 1. The indices have been left unchanged (GDP index, Life expectancy index, Index of level of education) The level of taxes, demonstrating the redistribution of GDP via taxation system, has been presented as a share of the GDP of the country.
The level of expenditures, shown in millions of Euros, has demanded significant transformations. On this purpose there have been chosen the countries with the highest Human Development Index in the models. It has been done due to the fact that the research considers the human capital development but not economic development level within the country. Consequently, Holland (the Netherlands) is supposed to be 1 for the Continental model (HDI=0.890, the highest position in Continental model and the 7th in the world rating) and Norway is supposed to be 1 for Scandinavian model (HDI=0.938, the 1st position in Scandinavian model and in the world rating) since the expenditures of these countries have been taken as 1, the corresponding expenditures of other _ countries have been converted in this scale.
The data converted into values from 0 to 2 1 have been implemented for calculating Stu-| dent's criterion. After calculating the values, is there have been sorted out the criteria, dem® onstrating the higher stability. The required t-| distribution has been obtained with employ-is ment of Statistics packet on the basis of Euro's^ stat data [3]. "ft
« Next step is investigation of the time series J data, allowing forecasting the resource of the § human capital development. There has been § established a regression equation for every bail sic factor of the human capital development. § These regression functions can also be em-<S ployed for forecasting the indices having great
influence on determining and describing the development of the human capital.
There has been done typologisation of regression functions on the basis of regression dependencies and coefficients of determination. Almost all of obtained regressions belong to the polynomial type of the second power or to the exponential type.
The factors have been considered from the point of view of social models. There have been investigated the countries employing Continental Model and Scandinavian Model. Since the countries grouping has been easily implemented also on the basis of the regression equations, it is possible to conclude that this stage of investigation also supports the idea that the approach towards the determination of the factors influencing the human capital in the dependence with the social model is correct.
There have been employed the statistic data from year 1993 to the year 2007 for conducting this experiment. Unfortunately, the data for years 1996 and 2006 have not been considered, since there are gaps in data for many countries for these years in Eurostat. The data on all countries, considered within the models (Scandinavian Model and Continental model) have been implemented. First of all there have been investigated the factors manifesting the high level of correlation with HDI (Human Development Index), and then the factors with insignificant correlation. The procedure of analysis has comprised all the possible regression dependencies of every factor trend; nevertheless, the coefficient of determination has been specified as a criterion for selecting the regression type. The obtained regression types are shown in Tables 6-8.
HDI Forecast
The above presented types of regression dependencies can be employed for forecasting the indices in future. Since the goal of this paper is analysis of the HDI factors, the forecast of this index is presented in this work.
The certain difficulties appeared in the process of working out this forecast. The Reports
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Table 6 §
SCANDINAVIAN MODEL — REGRESSION TYPES &
HDI LE GDP/cap ED/cap TAX/lab
R2 Type R2 Type R2 Type R2 Type R2 Type
NORW 0.8705 polyn 0.9736 polyn 0.9522 polyn 0.9413 polyn 0.5465 Polyn
SWED 0.8735 polyn 0.952 polyn 0.9804 polyn 0.9855 polyn 0.918 Polyn
ICEL 0.8443 polyn 0.9319 polyn 0.9722 polyn 0.9836 polyn 0.3306 Polyn
FINL 0.7529 polyn 0.9892 polyn 0.9883 polyn 0.9797 polyn 0.8425 Polyn
DENM 0.8236 polyn 0.9883 polyn 0.9916 polyn 0.9869 polyn 0.8597 polyn
SCAN 0.9383 polyn 0.9929 polyn 0.9886 polyn 0.9947 polyn 0.89 polyn
Table 6 (continuation)
SCANDINAVIAN MODEL — REGRESSION TYPES
POV/exp SOC/exp EMPL R&D/exp
R2 Type R2 Type R2 Type R2 Type
NORW 0.9612 polyn 0.9896 polyn 0.6307 polyn 0.9045 polyn
SWED 0.7866 polyn 0.9792 polyn 0.4122 polyn 0.975 polyn
ICELA 0.8484 polyn 0.9085 polyn 0.3699 polyn 0.9608 polyn
FINLA 0.8994 polyn 0.9922 polyn 0.7214 polyn 0.9859 polyn
DENM 0.3783 polyn 0.9924 polyn 0.7559 polyn 0.9793 polyn
SCAN 0.9023 polyn 0.9915 polyn 0.4719 polyn 0.9875 polyn
Table J
CONTINENTAL MODEL (group I) — REGRESSION TYPES
HDI LE GDP/cap ED/cap R&D/exp
R2 Type R2 Type R2 Type R2 Type R2 Type
NETHE 0.828 polyn 0.969 polyn 0.9863 expon 0.9924 Polyn 0.973 polyn
GERM 0.7659 polyn 0.982 polyn 0.976 expon 0.9651 Polyn 0.9647 polyn
AUSTR 0.7394 polyn 0.9874 polyn 0.9905 expon 0.9834 Polyn 0.9959 polyn
CZECH_ 0.7169 polyn 0.9746 polyn 0.9869 expon 0.9933 Polyn 0.9573 polyno
FRANC 0.7443 polyn 0.822 polyn 0.958 expon 0.9671 Polyn 0.9529 polyn
POLAN 0.743 polyn 0.9642 polyn 0.9735 expone 0.9939 Polyn 0.9122 polyn
CONT_I 0.7573 polyn 0.985 polyn 0.9903 expon 0.993 Polyn 0.9561 polyn
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Table / (continuation)
CONTINENTAL MODEL (group I) — REGRESSION TYPES
SOC/exp TAX/lab POV/exp EMPL
R2 Type R2 Type R2 Type R2 Type
NETHER 0.9705 exponen 0.494 polynom 0.6271 polynom 0.7064 polynom
GERMAN 0.9317 exponen 0.9638 polynom 0.7913 polynom 0.6995 polynom
AUSTRIA 0.9795 exponen 0.7991 polynom 0.2625 polynom 0.5002 polynom
CZECH_R 0.9829 exponen 0.9057 polynom 0.8 polynom 0.6777 polynom
FRANCE 0.9858 exponen 0.2965 polynom 0.9784 polynom 0.9762 polynom
POLAND 0.9827 exponen 0.9647 polynom 0.6189 polynom 0.9251 polynom
CONT_I 0.7371 exponen 0.9188 polynom 0.871 polynom 0.2386 polynom
Table В
CONTINENTAL MODEL (group II) — REGRESSION TYPES
HDI GDP/cap ED/cap R&D/exp
R2 Type R2 Type R2 Type R2 Type
ESTONIA 0.9514 polynom 0.975 polynom 0.9373 polyn 0.9565 polynom
LITHUAN 0.7077 polynom 0.9906 polynom 0.9764 polyn 0.9903 polynom
LATVIA 0.6779 polynom 0.9802 polynom 0.9996 polyn 0.9443 polynom
HUNGARY 0.6418 polynom 0.9773 polynom 0.9606 polyn 0.9661 polynom
CONT_II 0.933 polynom 0.998 polynom 0.979 polyn 0.9864 polynom
Table В (continuation)
CONTINENTAL MODEL (group II) — REGRESSION TYPES
SOC/exp EMPL TAX/lab POV/exp
R2 Type R2 Type R2 Type R2 Type
ESTONIA 0.9774 polynom 0.9284 polynom 0.906 polyn 0.9205 polynom
LITHUAN 0.9001 polynom 0.8526 polynom 0.7785 polyn 0.5216 polynom
LATVIA 0.9488 polynom 0.9416 polynom 0.9115 polyn 0.8657 polynom
HUNGARY 0.9889 polynom 0.9051 polynom 0.1804 polyn 0.4068 polynom
CONT_II 0.9776 polynom 0.9448 polynom 0.8837 polyn 0.7677 polynom
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on this index were always published with time lag of 2 years. So, in 2009 there was published the Report on HDI for year 2007, however, in year 2010 there was published not the Report for 2008, but the Report for year 2010, with simultaneous change of method of calculation of this index. Consequently, the indices for 2008 and 2009 were not published, and starting from 2010 this index is a brand new index. The old method assumed that HDI consists of 3 equal ranking components [16]:
• income, determined by GDP at PPS in US $;
• education, determined by adult literacy indicator (with weight of 2/3) and gross enrolment index (with weight of 1/3);
• length of life, determined by Life expectancy.
• For every of these indices the fixed minimal and maximum values have been determined:
• life expectancy — 25 and 85 years;
• adult literacy — 0% and 100%;
• gross enrolment — 0% and 100%;
• real GDP per capita at PPS in US$ — 100 and 40 thousand.
The indices are calculated according to:
Index = xi xmin
2.1 Mean Years of Schooling Index
W (Y ) =
lOg Xmax - lOg Ут
The final index is calculated as arithmetical mean of three indices.
According to new method the calculation is complicated by new components [16]. The following indices are used:
1. Life expectancy index LEI = ■ LE 20
83.4 - 20
2. Education index EI =
yjMYSI ■ EYSI
MYSI =
MYS 13.2
2.2 Expected Years of Schooling Index EYS
EYSI =
20.6
3. Income Index (II)
II =
In(GNIpc) - ln(100)
Income index is calculated differently in accordance with the diminishing marginal utility principle:
log y - log ym,n
0.951
ln(107.721) - ln(100)
Finally, the HDI is a geometric mean of the previous three normalized indices:
HDI = 3LEI ■ EI ■ II
The content of indices has also changed: LE: life expectancy at birth; MYS: Mean years of schooling (Years that a 25-year-old person or older has spent in schools); EYS: Expected years of schooling (Years that a 5-year-old child will spend with his education in his whole life); GNIpc: Gross national income at PPS per capita.
As a result of changed method, it is impossible to apply directly the received regression dependencies. Nevertheless, there should exist certain dependence between the indices calculated according to different methods. For determining this ratio the HDI for year 2010 was calculated according to the previous method. Index was calculated for every country considered in the paper and presenting the social model. On the basis of produced calculations there has been determined the ratio between the indices, calculated according to the old method (calculated values) and new method (presented in UNO Report). As a result the ratio of indices is determined as 1.14.
Next stage comprises the comparison of forecasted calculated values of HDI with coefficient 1.14 and values, presented in UNO Reports for years 2010 and 2011 [4].
The following results have been obtained: in group of countries with relatively high economic development implementing the Continental model the forecasted index differs with real by 2.14% in 2010 and by 2.2% in 2011.
In the group of countries with relatively low economic development, implementing the Con-
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tinental model, the difference in 2010 is 2.39% and in 2011 is 3.74%. The sharp difference exists due to HDI in Hungary, the real indicator is significantly lower than the calculated one.
The group of Scandinavian countries presents the following difference in indices: 2.24% in 2010 and 3.24% in 2011. In 2011 HDI in Norway is significantly higher than the calculated one.
Conclusion
The process of working over the presented paper involved the investigation of innovative economy, of knowledge economy. The different approaches towards innovations put forward the importance of human capital, it should be considered at new level of investigation, since human capital is responsible for the economic growth within the country and it should be ready to meet the new requirements to it in the frameworks of innovative economy.
In this connection the sources of human capital formation and the issues of measuring the human capital have been considered.
Comparison of factors, simultaneously significant for human capital and for social model adopted within the country has demonstrated that the social model is the factor influencing the human capital in the country and responsible for its formation, reproduction and development.
_ The research reveals the types of models.
Since the primary interest for authors presents 2 the Baltic region, the countries of which employ | the Continental social model, the papers con-is cerns mostly the influence of this model on the ® human capital development. The Scandinavian | model has been implemented as a comparison H basis. The paper also concerns the criteria for js choosing this model specifically as an object « of comparison.
J The special interest is presented by the in-§ vestigation of HDI (Human Development Index) § correlations with other factors important for the 1 human capital development, as well as factors § interdependence. Since the correlation depends dencies of factors are clearly observed within
the frameworks of the chosen models, it gives opportunity to conclude that the existing correlation dependencies reflect the level of the human capital development.
Further the considered correlation dependencies have been checked for sustainabili-ty with employment of Student's criterion. The Student's Criterion supported the correctness of methods applied to the human capital development and revealed the community of factors within the frameworks of the social models.
At last, there have been revealed the regression dependencies of the factors. The further possible investigation assumed to be taken in the nearest future will concern the employment of obtained regressions for forecasting the human capital development. Aggregating the regressions in the frameworks of the considered social models manifests their conformity. Accordingly, the fact of correctly chosen criterion for human capital factors grouping has been supported.
The obtained regression dependencies allow forecasting HDI, but the procedure is complicated by the fact of changing the method of calculating HDI in 2010, while the regressions have been obtained basing on the data of 2007. Nevertheless, the research has provided the coefficient allowing forecasting on the basis of regression equations even after changing the method of indicator calculation.
References
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5. Holostova Y. Social Policy and Social Work. Textbook. M., 2009. — 216 pp.
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7. Joseph E. Stiglitz A Global Recovery for a Global Recession The Nation, July 13, 2009.
8. Joseph Schumpeter, 1982. The Theory of Economic Development: An inquiry into profits, capi-
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tal, credit, interest and the business cycle), 1911, 13. 244 pp., Transaction Publishers.
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p. 439-368. 15.
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Shultz T. Human Capital in the International En- o cyclopedia of the Social Sciences. N. Y., 1968, £ vol. 6. ¿
Shultz T. Investment in Human Capital. N. Y., L., 1971, p. 26-28.
Social Security Programs throughout the World 1991, SSA Publication № 61-006/ Sept. Programs of 146 countries on social protection. Social State: Glossary-Reference / Ed. N. Gritsenko and others. M.: ATiCO, 2002. Strelchonok V., Popova Y. (2012) II. System Analysis of the Human Capital Development Factors, Nordic-Baltic-8.
Zinovkina M., Andreev S., Gareev R. Solution of Creative Managerial Tasks in Innovation Management. Innovative technical systems. M.: MSU, 2004. p. 7.
Е. Попова, аспирант Института транспорта и телекоммуникаций, Латвия, Рига, [email protected]
Социальная модель как детерминант человеческого капитала
Данная работа рассматривает факторы, которые являются определяющими для уровня развития человеческого капитала. Исследование базируется на временных рядах. Для основных факторов человеческого капитала представлены регрессионные функции. В дальнейшем эти регрессии использованы для прогноза индекса развития человеческого потенциала. Возможность научного прогнозирования обеспечена полученными зависимостями; временной промежуток делает возможной верификацию. Типологизация функций произведена на основе типов регрессионных зависимостей и коэффициентов детерминации. Факторы рассматривались для групп стран, использующих одинаковую социальную модель. В работе рассмотрены Континентальная и Скандинавская социальные модели.
Ключевые слова: человеческий капитал, факторы, регрессия, функциональные зависимости, прогноз.
