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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.

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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

Rating the inclusiveness of economic systems and institutions

In the previous section, equality of opportunity was inferred by comparing individual outcomes, in terms of wealth and education, with characteristics of those individuals that should ideally be unrelated to such outcomes, but in fact are not. While this can represent an objective, data-based gauge of the “inclusiveness” of economic, political and social systems, it suffers from two drawbacks.

  • Because all the data were based on a survey of the adult population, some of the conditions that created the observed inequality of opportunity may be 10, 20 or even 30 years old. Economic and political systems may have changed in the meantime – for example, by providing better and more widespread primary and secondary education opportunities, or by treating young entrants to the labour market differently. It may take another generation for these improvements to be reflected in data about economic outcomes.
  • The results of the analysis presented in the previous section give few hints as to what policy-makers can do to make societies more inclusive. For example, the fact that inequality is high in Western Balkan countries and this relates to parental education points to the importance of the education system in evening out opportunity, but provides no further clues. Similarly, the finding that in most of EEC, Central Asia and some SEE countries a rural birthplace puts individuals at a critical disadvantage suggests a need to examine the quality of institutions, access to services, infrastructure and education in rural areas, but offers no further help in identifying what is amiss.

This section attempts to rate the existing (or recent) institutional environment in transition countries in terms of its propensity to create or impede equality of opportunity. This is done from the perspective of three “target groups”, namely women, residents of regions that are lagging behind economically and young people (15 to 24-year-olds).1 While the last group obviously does not reflect a circumstance at birth, it is used here as shorthand for a combination of circumstances and outcomes at a particular stage in life – namely, a non-privileged social background and access to education and initial job opportunities – that is of particular importance for society. Research has shown that young people who do not have sufficient access to education or work experience have substantially lower lifetime earnings and career opportunities.2

For each target group, the objective is to define “inclusion gaps” analogous to the EBRD’s sector-level assessments, which describe transition gaps for each sector and country of operations (see the section of this report entitled “Progress in transition: structural reform”). This involves the following four steps.

  • First, we need to identify dimensions of the economic system that are essential for reducing the inequality of opportunity suffered by members of particular groups. These generally include access to education, labour markets, finance and public services – which are important for any individual, almost regardless of circumstances. The aspect within each of these dimensions that is the most relevant will depend on the target group.
  • Second, we need to collect data on each of the dimensions. The extent of the available data is sometimes the limiting factor, particularly when trying to establish inclusion gaps across regions within countries
  • Third, a benchmark needs to be set that defines what an inclusive structure should look like, and there needs to be a rule on how to rate distance from the benchmark. In the case of gender gaps, the benchmark is economic parity between men and women. In other cases – for example, when comparing the opportunities of young entrants to the labour market with those of experienced workers – the benchmark can be defined by best practices in advanced economies. The distance from the benchmark is expressed on the 10-point scale – from 1 (indicating the largest possible gap) through 2-, 2, 2+, 3-, 3, 3+, 4- and 4 to 4+ (indicating a negligible gap) – used for the EBRD’s transition indicators
  • Lastly, we need to average ratings based on individual data series to arrive at an inclusion gap for each dimension, target group and country (a gender gap for access to finance in Romania, for instance). When data series with overlapping content are used, a “principal components” approach is employed that in effect weights each series according to how much new information it contributes. In most cases simple averages are used, occasionally giving a series that is deemed to be more important a higher weighting.

Note that under this approach, inclusion gaps measure differences in opportunities – across regions, between women and men, or between 15 to 24-year-olds and older workers – rather than opportunity levels. If both men and women, or all regions within a country, do poorly, there is no inclusion gap, even though there may be large gaps in terms of transition or development. For example, a small gap in access to finance does not necessarily mean that women have easy access, only that they do not have significantly greater difficulties than men.

The remainder of this section summarises the dimensions and data used to calculate the inclusion gaps and presents the main results for each target group. Methodological details on the third and fourth steps above – particularly the question of how gaps were defined for each data series – are available in Annex 5.2.

 

  1. This analysis could be extended to include other groups defined by ethnicity, disability or sexual orientation. [back]
  2. See Gregg and Tominey (2005). Macmillan (2012) calculates that a year of youth unemployment reduces earnings 10 years on by an average of about six per cent and means that, on average, individuals spend an extra month unemployed every year up to their mid-30s. [back]

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