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Transition Report 2013 Stuck in transition?

CH4 180sq

Facts at a glance

AROUND
37%
The proportion of the population aged 25 and over in the transition region that had completed at least secondary education in 1990 (compared with 35% in advanced economies).

ALMOST 75% of migrants from countries in the transition region emigrated to other countries in the region.

Cover 180sqV2

 

IN 14 transition countries, having an inadequately educated workforce was among the top three (out of 14) business environment obstacles.

10 The number of universities in the transition region among the top 500 universities in the 2013 Shanghai ARWU league table.


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Human capital

Returns to tertiary education in transition region

People with tertiary schooling typically earn higher incomes than those who start work after completing secondary schooling, with the difference between the two representing returns to tertiary education. More precisely, returns to tertiary education are the increase in lifetime income, relative to the income associated with secondary schooling, which an individual can expect as a result of obtaining a tertiary degree. This is a critical factor both in an individual’s decision to pursue higher education and, consequently, in the development of a country’s human capital stock.

Returns depend on the supply of, and demand for, tertiary-educated workers.1 It is not a problem when returns are comparatively low because of an abundant supply of highly educated graduates. However, when returns are low because of weak demand, this raises concerns. One reason for such a scenario could be the poor quality of tertiary education. Another could be that highly educated people are not being matched with the appropriate jobs and cannot use their skills effectively. A third reason could be that even though well-trained graduates are being matched with the right jobs, they are being under-paid. The last two interpretations imply that while a good education system is necessary to build an effective stock of human capital, this is not sufficient for growth if that stock is not used effectively or if there are inadequate incentives for an individual to invest in tertiary education.

Regression analysis can be used to identify the share of returns to tertiary education that is not explained by either the supply of and demand for tertiary graduates or the quality of the education system. This is illustrated in the first two columns of Table 4.2. Returns are estimated as average country-level differences in terms of the subjective income ladder between employed heads of households who have a university degree and those with just a secondary school diploma. The data used are taken from the Life in Transition Survey (LiTS) conducted by the EBRD and the World Bank in 2006 and 2010.2 On the supply side, returns depend on the proportion of people with a university degree and brain drain, measured as a high-skilled net emigration stock rate.3 Demand for tertiary graduates, on the other hand, is influenced by the quality of universities in the given country (measured by the number of S&E students originating from each country who later obtain a doctorate in the United States), as well as the average quality of secondary schooling (measured by the number of undergraduate students in the United States per million people of working age and by international assessment tests for secondary schools). In addition, the regressions use either the share of high-technology exports or GDP per capita as proxies for the degree to which the economic structure is likely to require (and value) tertiary education graduates.4

Table 4.2

Income ladder returns to tertiary education in terms of human capital supply and demand and the institutional environment

Dependent variable: income ladder return to tertiary education
  (1) (2) (3) (4) (5) (6) (7)
Determinants of supply       
Percentage of people with tertiary education  -0.024** -0.013 -0.015 -0.017 -0.025** -0.006 -0.014
-0.011 -0.011 -0.01 -0.011 -0.011 -0.011 -0.013
Brain drain  0.487 -0.031 0.18 0.268 0.206 0.436 0.008
-0.599 -0.572 -0.485 -0.562 -0.616 -0.599 -0.626
Determinants of demand       
Recipients of US S&E doctorates  0.023 0.014 0.014 0.018 0.02 0.023 0.009
-0.022 -0.018 -0.02 -0.022 -0.022 -0.017 -0.021
Undergraduates in the United States -0.001** -0.001** -0.001*** -0.001*** -0.001** -0.001*** -0.001
0 0 0 0 0 0 -0.001
Secondary school test scores 0 -0.003 -0.003** -0.003* -0.001 -0.002 -0.003*
-0.001 -0.002 -0.001 -0.001 -0.001 -0.002 -0.001
High-technology exports 0.015** 0.009 0.004 0.009 0.01 0.014* 0.003
-0.007 -0.007 -0.006 -0.007 -0.008 -0.008 -0.01
GDP per capita   0.039          
  -0.024          
Institutional environment       
Effectiveness of government     0.186**        
    -0.072        
Rule of law       0.127**      
      -0.057      
Impartial courts         0.090*    
        -0.052    
Contract viability           0.175***  
          -0.049  
Reforms             0.185*
            -0.1
Transition country indicator -0.075 0.463 0.143 0.107 0.108 0.11  
-0.138 -0.391 -0.152 -0.16 -0.154 -0.161  
Intercept 0.912 1.434** 1.329** 1.382** 0.815 0.05 0.826
-0.813 -0.57 -0.505 -0.659 -0.728 -1.217 -0.58
Observations 29 29 29 29 29 25 24
R-squared 0.405 0.556 0.587 0.495 0.463 0.648 0.452
Adjusted R-squared 0.207 0.379 0.422 0.294 0.248 0.472 0.212
F 3.383 3.51 4.652 3.983 4.67 5.642 2.079

Source: Barro and Lee (2013), US National Science Foundation, Institute of International Education, Altinok et al. (2013), World Bank (World Development Indicators and Worldwide Governance Indicators), Fraser Institute (Economic Freedom of the World index), International Country Risk Guide and EBRD.
Note: Robust standard errors in parentheses. ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively. Transition country indicator is a variable equal to 1 if the country is a transition country and 0 otherwise.

Note on variable definitions in Table 4.2 (sources in brackets): “Percentage of people with tertiary education” refers to share of population aged 25 and over who had completed tertiary schooling in 2005 (based on Barro and Lee, 2013, and own calculations); “recipients of US S&E doctorates” refers to average number of recipients in the United States in 2007-11 per million people of working age (National Science Foundation); “undergraduates in the United States” refers to average number of undergraduate students in United States in 2007-11 per million people of working age (Institute of International Education); “secondary school test scores” refers to average score in tests in 1995-2010 (Altinok et al (2013)); “GDP per capita” refers to 2006 GDP per capita at purchasing power parity in thousands of constant 2005 international dollars (World Development Indicators); “high-technology exports” refers to high-technology exports as a percentage of manufactured exports in 2006 (World Development Indicators); “effectiveness of government” refers to an effectiveness indicator for 2006 (Worldwide Governance Indicators); “rule of law” refers to a rule of law indicator for 2006 (Worldwide Governance Indicators); “impartial courts” refers to the variable measuring efficiency, transparency and neutrality of the legal framework with respect to dispute settlements and challenging government actions and or regulations in 2006 (Economic Freedom of the World); “contract viability” refers to the viability of contracts in 2006 (International Country Risk Guide); and “transition progress” refers to the average EBRD transition indicator score in 2006 (EBRD).

Chart 4.7 shows income ladder returns to tertiary education by country, adjusted for basic supply and demand forces, using the residuals from the first regression in Table 4.2.5 Assuming that raw returns and supply and demand factors are measured correctly, these adjusted returns reflect differences in the extent to which human capital is used and remunerated across countries. The chart shows a high degree of heterogeneity across countries. For instance, in Lithuania and the Czech Republic university graduates are, on average, almost 1.4 income ladder steps above secondary school graduates, while the difference in the perceived ladder position in Moldova is only 0.2 of a ladder step. The adjusted returns ranking in the chart is likely to be imprecise owing to measurement errors, the relatively small sample, the subjective nature of the relative income measure used in the analysis and the fact that the self-reported position on the income ladder may not reflect informal payments or gifts. Therefore, while a country’s broad position in the ranking – that is, whether it is near the top, at the bottom or in the middle – should be informative, the exact order need not be.

Chart 4.7

Source: Authors’ calculations using the EBRD/World Bank Life in Transition Survey (2006 and 2010).

The remaining columns of Table 4.2 explore the correlation between returns to education and variables describing the quality of the institutional environment, while controlling for supply and demand. For example, Sweden’s level of government effectiveness is associated with returns about one income ladder step above the levels seen in the Kyrgyz Republic and Moldova (column 3). Similarly, the rule of law in Germany and Sweden is associated with returns that are about two-thirds of an income ladder step higher than those seen in Albania, Azerbaijan, Kazakhstan, the Kyrgyz Republic, Russia and Ukraine (column 4).

For the same sets of countries, the difference between the minimum and maximum levels of court impartiality is estimated to be associated with a difference in returns of about half an income ladder step (column 5). Levels of contract viability in EU countries (excluding Bulgaria, Poland and Romania) are associated with returns about half a ladder step above those seen in Armenia, Moldova and Russia (column 6). Lastly, the level of transition progress in Estonia – as measured by the EBRD transition indicator – is associated with returns about three-quarters of an income ladder step above those seen in Azerbaijan.

There are several reasons why the institutional environment could (directly or indirectly) affect the level of returns to education.

  • Institutions affect implicit decisions by highly educated people to engage in rent-seeking or socially productive activities.6 Improvements in government effectiveness reduce the returns to rent-seeking, which is consistent with the regression results. The country-specific legal setting is also crucial, with a stronger rule of law, more impartial courts and a greater level of contract viability all reducing the cost of productive activities (for example, entrepreneurship). Greater progress with transition to a market economy also increases the potential upsides of entrepreneurship, while reducing the relative attractiveness of rent-seeking.
  • Market development, government effectiveness and country-specific legal characteristics also affect the allocation of highly educated people across the economy and within particular firms, in terms of both their positions and their actual effectiveness. Better institutions lead to more efficient matching of talented people with demanding jobs, leading to more efficient use of such people and, ultimately, greater productivity.
  • By reducing various risks that affect people and firms, a better institutional environment – particularly the legal aspects – directly or indirectly encourages the highly educated to further improve their knowledge and skills, which in turn enhances the quality of human capital stock, even after the completion of formal schooling.

To sum up, a better institutional environment increases the productivity of highly educated people and – by fostering higher returns to schooling – encourages more talented people to complete tertiary education. This, in turn, creates momentum for human capital accumulation and, consequently, for growth.

 

  1. See Montenegro and Patrinos (2013). [back]
  2. The data and the estimation method are described in more detail in Box 4.1. [back]
  3. Brain drain will reduce the number of tertiary-educated workers competing for jobs and therefore
    increase returns to tertiary education. At the same time, brain drain could have a downward impact on the returns to education if the human capital of workers who emigrate is higher than that of workers who stay in the country. The regression results suggest that the first channel generally prevails, although the net effect is not statistically different from zero. [back]
  4. See Goldin and Katz (2010). [back]
  5. Chart 4.7 shows the country-specific residuals from the regression (contained in column 1 of Table 4.2). [back]
  6. See Natkhov and Polishchuk (2013). [back]

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