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Capitalization of Education: Cross-Cohort Analysis

русская версия

Опубликовано на портале: 31-12-2010
Мир России. 2006.  Т. 15. № 1. С. 76-100. 
The introduction of a new set of reforms at the beginning of 1990s has triggered a dramatic change in socioeconomic behavior for all social strata. The hard recession, associated with the transformation, together with the ill-conceived social policy were the general reason for an emerging number of specific problems related to human capital. The shift in personal income distribution among the population was the logical result of partial depreciation of some obsolete behavior patterns and skills, and the spreading acknowledgment of those, demanded in a new market economy. In this sense the observed human capital depreciation is associated with the fact, that its core components, such as education and professional status, obtained before the transformation period, could no longer guarantee individuals their former level of welfare. Furthermore Russia was about to face extreme unemployment and the loss of wages, which were sooner to become a serious threat for the most social groups. Far from every group though could equally challenge the changing socioeconomic reality. It is quite reasonable to suggest, that at the beginning of the transformation period the preferences and behavior patterns of the more flexible young would more likely match the new market conditions. They have a lot more chances to take an advantage of the arising opportunities, rather than the older ones. A younger generation would generally accept the reality as it is, and their choice of professional future would bear no additional costs, associated with the depreciation of obsolete skills, requalification and the painful process of adaptation to the changing environment, which would otherwise burden more senior citizens. In other words, for the given research we suggest that for the population, which happened to come into this world in the early 1970s and later, it was easier to accustom to a new system of social and economic relations. However the origin of the welfare differentiation was more commonly explained through other factors rather than through the difference in educational status and age-specific adaptation potentials. The ‘new old’ strategies of achieving a higher level of socioeconomic status often included the use of the existing social bonds and connections, access to nomenclature, etc., and the domination of those strategies must have significantly affected the educational stimuli. But it is possibly another delusion, because in the earlier 1990s Russia witnessed the boosting number of emerging universities, institutions and colleges, most with a commercial status, which was a direct response to the growth of the education market. Therefore it is clear, that the problem of education as a welfare differentiating factor deserves a better understanding today. A cross-cohort analysis, performed on a modern representative sample data, allows us to conduct a deeper research of the inner dynamics of the process, which is related to the shift in material incentives of the human capital accumulation. Thus it is possible to measure the adaptation consequence for different age groups and their welfare growth potentials, determined by the amount and quality of possessed professional skills and education. Eventually the objective of the current research is to test two of the following general hypotheses: 1) professional experience and education have smaller effect on older cohort’s welfare and relatively greater effect on younger cohort’s welfare (because of the difference in adaptation costs during the transformation period of 1990s), 2) formal education in modern Russia is not the only key factor of the human capital, individual welfare will also be produced through possession of modern skills. Addressing the theory of human capital [Schultz 1971, Becker 1993, Mincer 1958] proved very helpful in assessment of the existing capitalization potential of education. The wide-spread practice of Mincer’s econometric model of wages (particularly in Russia) determined its application in the current research and the corresponding calculation of education investment returns (in this work equally regarded as its capitalization opportunities). J. Mincer discovered the standard wages logarithm function with the following independent values: individual investment in education, professional track record, and job-specific experience. He interpreted their assessed factors as the human investment returns, and that gives us a powerful instrument for the estimation of their efficiency. However in order to receive a better idea about the nature of relation between education and welfare of certain social groups, the analysis was enhanced with additional variables, responsible for property values of individuals and regarded apart from the regression model (viz. through correlation analysis). Mincer’s equation was also enhanced with some ‘dummy’ variables, necessary to test the second hypothesis: the possession of second education and modern skills, represented by the knowledge of at least one foreign language and good computer skills (the general idea of such inclusion was extracted from Handel 1999). The secondary research data is based on the results of the survey of 2414 economically active Russians, conducted in November-December 2002 under the guidance of O. Shkaratan. The primary survey mission was to collect the data, necessary for the research of significant aspects of the post-Soviet transformation in Russia and the dynamics of the emerging social and economic processes. The feedback form included 99 questions, which particularly characterize every respondent and were logically structured into several blocks, making it possible to reveal the dynamics of his cross-generational and professional mobility, level of qualification and education, his living standards and the quality of life. The functional advantage of this data can be proved by successful survey results, achieved in the previous decades, and the experience of its organizers. The original selection from the survey was reduced to 1845 respondents, who satisfy the criteria of our research object. The new selection was thereafter split into 4 cohorts with a 10-year interval. The first cohort with respondents aged between 25 and 34 years old represents the Russians, most of whom graduated in 1992-2001. This cohort is distinguished by the fact, that its respondents have completed their education during and after the transformation period. The last and the ‘oldest’ cohort is a retiree group with people aged between 55 and 64 years old, who had to adapt to the beggarly social security and to find additional sources of income. Thus were obtained several conceptual objects for comparative cross-cohort analysis. It must be mentioned, that the gender-caused distribution of factors was left beyond the current research framework, and that could have slightly affected their estimation. Though it did not interfere with the primary research objective, it became clear, that it must be closely considered in further research. In conclusion the following findings were unveiled: 1. Despite the highest percentage of university graduates and possession of modern skills (foreign languages and computer knowledge), the ‘younger’ cohort (25-34 years old) did not reflect a considerably higher correlation between educational level and the level of welfare with the only exception of last cohort (55-64 years old). Thus was discarded the first hypothesis, stating that the education is more welfare differentiating among the young population, who bear no adaptation and requalification costs. 2. Some measurable relation between the wages and educational level is observed in the ‘older’ cohort (55-64 years old), but it was absolutely insignificant in considering their property and possessions. But the fact, that the average income level of this group is extremely low, justifies an exhausted capitalization of education.. 3. Welfare distribution according to educational level proved most reasonable for the middle categories of respondents (35-54 years old). 4. Econometric estimation of modern skills capitalization was also a successful experiment (with the only exception of the last cohort), which brings some empirical proof for the second hypothesis. But the growing returns of these factors for the older cohorts additionally discards our first assumption. 5. At the opposite extremes of the final selection (the ‘younger’ and the ‘older’ cohort) a significant sinking of incomes for the respondents with basic vocational and vocational-technical education (PTU graduates) was observed. Since nearly 10 years after the launch of radical transformation the national system of education and labor market can still be regarded as ineffective. Instead of an adequate response to the structural change it is continuing to lose its utility for the agents and economy as a whole. Foremost, based on the findings it was quite reasonable to put forward the following suggestion, that there exists a number of unobserved factors which determine the welfare of the young. While their influence is dominating, it threats the motivation of the future generation and its human capital accumulation strategies. In the next place, the depressing welfare of vocational school graduates poses another serious problem and demonstrates the total lack of an adequate policy, which must be determined in order to eliminate a number of obsolete industries and to execute the corresponding reorientation of the existing schools to the current market demands. In connection with the recent intentions of a future admission of Russia in Bologna process, the outlined problems deserve a further profound research. The adaptation of the international educational practices must therefore be brought into to the full compliance with the transformation-specific socioeconomic reality of the country. Otherwise it might become just another negative experience and cause a serious failure in future.
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