Abstract
Patterns of intergenerational educational mobility are studied in twelve post-communist countries of Central Europe and the former Soviet Union (FSU). No clear trend in educational inheritance emerges over the recent 50 years, covering both the period of socialism and transition to a market economy. If any, we find the decrease in intergenerational persistence up until the generation of the 1950s. In subsequent years no further decline is observed. On the contrary in a number of states the correlation between parents’ and children’s schooling got stronger, further increasing over the period of transition.
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Notes
- 1.
Educational mobility is understood as a change in educational status across generations. It is considered to be high if the highest level of education achieved by a child does not closely relate to that of his/her parents. Educational persistence, by contrast, characterizes a situation where the educational choices of children are affected by those of their parents.
- 2.
These comprise Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, Slovenia, Romania, Russia and Ukraine.
- 3.
Breen and Goldthorpe (1997) modeled this behavior within the framework of formal rational action theory, despite the fact that the parents' decision is often taken irrespective of the abilities that the offspring shows.
- 4.
The coefficients obtained by regressing the education of children against that of their parents were at the level of 0.4–0.6 for Bulgaria, the Czech Republic, Hungary, Poland, and Slovakia. Only for Russia were they found to be lower, 0.28 for men and 0.33 for women.
- 5.
For this study we only use the information about the education of parents and their children, no other regressors enter the specification. Note that our main focus is not on the causal relation, but rather on association between the two main entries.
- 6.
The relation between the two measures is as follows: \( r_{s}^{c} = \beta_{s}^{c} (\sigma_{0}^{c} /\sigma_{1}^{c} ), \) where the indexes c and s stand for cohort and schooling, \( \sigma_{0}^{c} \) and \( \sigma_{1}^{c} \) are standard deviations of schooling in two successive generation.
- 7.
This was probably the motivation behind the coding for education, and it may have given rise to an upward bias for older generations.
- 8.
The correlation between the education of parents and that of their children in Bulgaria almost doubled from 1995 to 2000. Moreover, educational attainments declined in absolute terms for children from families with lower levels of parents' education. Hertz et al. (2009) claim that this was an economically-driven structural change caused by the contraction of public spending on education and the decline in its quality, the increase in out-of-pocket costs, the fall in the number of schools, and the rise in unemployment among those with secondary education.
- 9.
Some overlapping between the two groups is possible within the limits of the confidence intervals, although it is not consistent throughout the years considered.
- 10.
Recall that the most important transformations caused by the economic transition in Eastern Europe took place in the late 1980s to early 1990s (Roland 2000).
- 11.
After World War II and until 1984, which covers the first five years of the war in Afghanistan, college students were exempted from military service. Because of the lack of soldiers, this privilege was abolished in 1984 for all the universities but the very best [http://www.allpravo.ru/library/doc6934p0/instrum6935/print6943.html]. The status quo was restored in 1989, the year in which the war in Afghanistan ended.
- 12.
Note, here we refer to the year when a person acquired the highest level of education, while previous tables and graphs referred to the year of birth. We assume that the distance between these two moments is of the range of 17–20 years.
- 13.
Note that in the extreme case where everybody holds the highest degree, mobility would go down to zero. While this is not realistic, it makes the point about the effect of an overall increase in education levels and the kind of contraction in the gap between the education of children and their parents evidenced in Table 4.3.
- 14.
An educated labour force is a luxury that not every country can afford in large numbers. In an open economy, people can always migrate in search of higher returns to their education. Unless a country pursues well-designed education and migration policies, increasing human capital may turn into a loss. In former planned economies migration was limited, as well known, and the full effect of higher education was felt within the country.
- 15.
IIM will be higher in a given generation if there are lower returns to human capital for children or if children's human capital is less sensitive to parental earnings (see e.g. Solon 2004; Blanden et al. 2005). To show that, assume that earnings are a function of human capital in a given generataion (W t = ϕφ t H t +u t ). It is also plausible to assume that children’s human capital accumulation relates to parental income (H t = φ t W t-1+v t ). Thus we can obtain the following intergenerational mobility function: Wt = ϕ t φ t W t-1+ω t, where ω t = ϕ t v t +u t .Then the intergenerational income mobility expressed by the join parameter t t will be higher if there are lower returns to human capital for children (captured by ϕ t ), or if children’s human capital is less sensitive to parental earnings (lower φ t ).
- 16.
Note: We use returns to education as reported in Table 4.6. They were deliberately selected for the mid 1990s and are expected to affect the education choices of the youngest cohorts. Mobility in turn is measured as an average of the correlation coefficients between the education of children born in the 1970s and the education of their parents.
- 17.
For a set of countries considered, returns to education explain about one third of the variation in educational persistence.
- 18.
Because of the few countries considered, the revealed positive relationship between PRE and IEM may not be particularly indicative. This effect was actually found to be weak in a recent study by Chevalier et al. (2009).
- 19.
Education is one of the main determinants of earnings, yet it explains only about one third of the variation in earnings (Bowles et al. 2001).
- 20.
Studying, studying and studying, Lenin's famous slogan was a form of life guide instilled in the minds of people from early childhood. Education was perceived primarily as a means to achieve a comprehensively developed personality (Pastuovic 1993).
- 21.
This explains a shift in interest to specialties not particularly in demand under central planning, with finance, economics and law leading the list.
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Acknowledgements
I am grateful to Sam Bowles and Tom Hertz firstly for getting me involved into this field of research and then providing guidance. Special thanks go to Francesca Bettio for careful supervision of this work which made part of the Doctoral thesis. I also wish to thank the participants of the IX GDN conference, the XXV AIEL conference and the BEROC seminar for useful comments, in particular, Tom Coupe, Randall Filer, Francesco Pastore and Maksim Yemelyanau, and the two anonymous referees for suggestions that allowed improving the chapter. All possible imperfections remain my own responsibility.
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Veraschagina, A. (2012). Education and Socioeconomic Mobility in Post-Communist Countries. In: Parodi, G., Sciulli, D. (eds) Social Exclusion. AIEL Series in Labour Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2772-9_4
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