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Transition Report 2013 Stuck in transition?

CH5 180sq

Facts at a glance

OVER 35% of variation in wealth in some transition countries is explained by circumstances at birth.

GENDER GAPS are greatest in the areas of employment, firm ownership and management across most countries observed.

Cover 180sqV2

 

PLACE OF BIRTH is the main driver of inequality with regard to wealth.

PARENTAL EDUCATION is the main driver of inequality of opportunity with regard to tertiary education.

RIGID LABOUR MARKET STRUCTURES and weak education systems restrict opportunities for young people.


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Economic inclusion

Youth gaps

The assessment of youth inclusion gaps used indicators of labour market flexibility (since labour market rigidity particularly harms new entrants),1 youth unemployment and idleness rates, as well as measures of education and financial inclusion.

The quality and length of education are considered separate dimensions: while quality is essential, there is also evidence that extending the length of secondary education affects careers and lifetime earnings.2 Financial inclusion focuses on the use of bank accounts and debit cards (rather than access to credit), reflecting research that suggests that the early use of financial products and the early establishment of savings habits increase the quality of financial decision-making in later life.3 Table 5.3 lists the indicators and data sources used.

Table 5.3

Youth inclusion gaps – dimensions and indicators

Dimension Indicators Sources
Labour market structure Hiring and firing flexibility Global Competitiveness Index, World Economic Forum 2012-13  
Redundancy costs
Wage-setting flexibility
Productive opportunities for young people Difference between unemployment rate at age 15-24 and age 25-65 ILO, World Bank, 2010 or latest
Percentage of youths who are "not in education, employment or training" (NEET) Eurostat 2012, Silatech 2009
Quantity Average years of education of 25 to 29-year-olds Barro-Lee (2010), Human Development Index 2012 
of education Percentage of 15 to 24-year-olds with no schooling
Quality of education Test performance relative to highest possible score Programme for International Student Assessment (PISA) 2009 or Trends in International Mathematics and Science Study (TIMSS) 2011  
Schools' accountability (achievement data tracked over time)
Teacher/instruction material shortages
Employers' perception of quality of education system World Economic Forum 2012-13
Households' perception of quality of education system LiTS 2010
Universities in top 500 (cumulatively over 10 years) Academic Ranking of World Universities (ARWU) 2003-12
Financial inclusion Percentage of youths (15 to 24-year-olds) with bank accounts compared to adults Global Findex 2011 
Percentage of youths (15 to 24-year-olds) with debit cards compared to adults

As in the case of the gender gaps, some of the underlying data consist of indices compiled by other institutions (such as the World Economic Forum’s indicators of labour market flexibility and the quality of education as perceived by employers), as well as comparative information on the reference group, which in this case consists of adults aged 25 and over. The latter is used to rate financial inclusion, as well as youth unemployment. Unlike gender gaps, however, youth and adult rates are compared in terms of absolute differences (expressed in percentage points), rather than as ratios or percentage differences.4Furthermore, the benchmark for calibrating a “negligible” gap is not zero (that is to say, parity between youth and adults), but a positive difference that is sufficiently low to be viewed as “normal” even in a very inclusive economic structure. For youth unemployment this is set at 6 percentage points, based on the low end of globally observed differences between youth and adult unemployment rates between 1991 and 2012, while a difference of 10 percentage points or less is still considered a “small” gap.5

In several cases – including the percentage of youths who are not in education, employment or training (NEET) and all data series related to the quality and quantity of education – gaps were assessed without a direct comparison with the adult reference group. There are no series that would correspond to the NEET category among adults, and the quality and quantity of education are no longer relevant for most adult workers.6 Hence, gaps for these data series are calibrated on the basis of international best practices (see Annex 5.2).

Table 5.4 shows interesting variation, both across dimensions (columns) and countries (rows). The quantity of education in most countries in the transition region compares well with international standards (11 years of schooling being the OECD average). SEMED countries, particularly Morocco, are an exception.

However, opportunities for young people – reflecting youth unemployment relative to adult unemployment, as well as the NEET category – are unsatisfactory in most countries, including most Western comparators. There are exceptions, though: the Baltic states, Germany, Slovenia and, thanks to a surprisingly low NEET rating, Ukraine. With the exception of Hungary and Slovenia, available data also suggest that quality gaps in education remain “medium” or “large” in the transition region and in SEMED countries.

Table 5.4

Inclusion gaps for youth

Country Labour market structure Opportunities for youth Quantity of education Quality of education Financial inclusion
Central Europe and the Baltic states     
Croatia Medium Large Small Medium Medium
Estonia Medium Small Negligible Medium Negligible
Hungary Large Medium Negligible Small Large
Latvia Small Small Small Medium Large
Lithuania Medium Small Small Medium Small
Poland Medium Medium Small Medium Large
Slovak Republic Medium Medium Small Large Large
Slovenia Medium Small Small Small Negligible
South-eastern Europe     
Albania Medium Large Small Large Negligible
Bosnia and Herzegovina Small Medium Medium not available Small
Bulgaria Small Medium Small Medium Small
FYR Macedonia not available Medium not available Large Medium
Kosovo not available not available not available not available not available
Montenegro Medium Large Small Large Large
Romania Small Medium Small Medium not available
Serbia Small Large Large Medium Large
     
Turkey Medium Medium Large Medium Large
     
Eastern Europe and the Caucasus     
Armenia Medium Large Small Medium Negligible
Azerbaijan Medium Large Negligible Large Medium
Belarus not available not available Negligible not available Large
Georgia Negligible Large Negligible Medium Negligible
Moldova Medium Medium Small Large Negligible
Ukraine Medium Small Small Large Negligible
     
Russia Medium Medium Negligible Medium Medium
     
Central Asia     
Kazakhstan Small Medium Small Large not available
Kyrgyz Republic Medium Medium Medium Large Small
Mongolia Small Medium Medium not available Negligible
Tajikistan Medium Large Small not available Negligible
Turkmenistan not available not available Small not available Negligible
Uzbekistan not available not available Small not available Small
Southern and eastern Mediterranean     
Egypt Medium Large Large not available Negligible
Jordan Negligible Large Large Medium Large
Morocco Medium Large Large Large Medium
Tunisia not available Large Large Large Small
Comparator countries     
France Medium Large Negligible Small Medium
Germany Medium Negligible Small Small Negligible
Italy Small Large Negligible Medium Large
Sweden Large Medium Small Small Negligible
United Kingdom Small Medium Small Small Negligible

Source: See Table 5.3.
Note: See Annex 5.2 for methodology.

The chart also shows that there is a degree of correlation between the level of rigidity in labour market structures, the quality of education and the availability of opportunities for young people. Most countries that experience “medium” or “large” gaps in the first two categories also have at least a “medium” gap in the third.

The best-performing country in the transition region appears to be Slovenia, with mainly “small” or “negligible” gaps. However, eight countries – Albania, Azerbaijan, Montenegro, Serbia and the four SEMED countries – have “large” gaps in opportunities for young people and one or both educational dimensions.

Between these extremes, common patterns across countries can be observed within the CEB and, to a lesser extent, EEC regions. In the latter region the typical pattern involves “medium” gaps for labour market structure, “medium” or “large” gaps for opportunities for young people and the quality of education, and “small” or “negligible” gaps for the quantity of education. CEB countries do better on quality of education and opportunities for the young.

 

  1. See Lindbeck and Snower (1989) and, for SEMED countries, World Bank (2013). [back]
  2. See Meghir and Palme (2005). [back]
  3. See Reinsch (2012). [back]
  4. This reflects the judgement that, at low rates of overall unemployment, a given ratio between youth and adult unemployment indicates a smaller inclusion problem than when overall unemployment is high. For example, a 10 per cent youth unemployment rate might be acceptable if adult unemployment is just 5 per cent, but a 30 per cent youth unemployment rate with adult unemployment at 15 per cent is far less acceptable. [back]
  5. Youth unemployment rates are almost always higher than unemployment rates for older cohorts (see International Labour Organization, 2012), partly for undesirable reasons such as insufficient numbers of entry-level jobs and labour market rigidities, but also for efficient reasons such as job-switching among the young. Young people are also more likely to be idle (see O'Higgins, 2003 and World Bank, 2012b). [back]
  6. While current education indicators could be compared with past indicators that would have been relevant for the current adult population, this would amount to comparing opportunities afforded to the young at two points in time, rather than comparing the opportunities of those who are currently young with those who are currently adults. [back]

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