by Dirk Van Damme
Head of the Innovation and Measuring Progress division, Directorate for Education and Skills
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The rise of income inequality in OECD countries, especially from 1985 onwards, is now a well-documented fact, and a reason for much concern among policy-makers and economists. The Gini coefficient of income inequality in 16 OECD countries with available data has risen from .286 in 1985 to .316 in 2010. The concept of ‘inclusive growth’ suggests that without finding an adequate and effective policy response to increasing inequality future sustainable economic growth might also be jeopardised. However, the causes and underlying mechanisms behind the increase in inequality are less clear. A new paper based on data from the Survey of Adult Skills (PIAAC) hints to the role skills play in the puzzle behind income inequality.
At first sight, this seems a bit enigmatic. In recent decades huge investments have been made to improve the education and training of citizens in OECD countries. Consequently, the skills level of younger generations is higher than for older ones: on the PIAAC numeracy scale the mean score in the participating countries has increased from 259.9 among the 55-65 year-olds to 279.4 among the 25-34 year-olds. More workers with higher skills means more productivity and more income, at least that’s the conventional argument. Despite persistent challenges with regard to equitable access to education and equity in learning outcomes, the benefits of educational expansion have gradually been spread more evenly over the population (the education Gini has improved from .22 to .15 in OECD countries). But apparently that hasn’t helped improve income inequality. The missing link is most likely the role played by the unequal distribution of skills among workers.
The proportion of adults at each end of the skills scale is one approach to measure the unequal distribution of skills. As the chart above illustrates, there is a pretty strong correlation of .59 between the share of low-skilled adults and the Gini coefficient. Spain, Italy, Ireland and Poland are, together with the United States, the countries with the highest numbers of low-skilled adults. At the other end of the scale we see a similar relationship: the share of high-skilled adults has a -.54 correlation with the Gini coefficient. As a result, the mean country score is quite strongly related to this measure of income inequality (-.63). Countries with high numbers of poorly skilled adults and low numbers of high-skilled tend to be countries with a high income inequality
Comparing the width of the distribution tells a similar, albeit slightly different story. How large is the skills gap between the highest and lowest quartiles in the skills distribution? The score point difference between the 75th and 25th percentiles ranges from 57 for the Czech Republic to 76 for the United States. But the interesting fact is that the width of the distribution is also related, although to a lesser extent (.40), to income inequality. The four countries which we identified as relatively low-skilled – Spain, Italy, Ireland and Poland – are situated in the middle of the pack, with a distribution width close to the average. The Nordic countries have similar gaps between the highest and lowest skilled 25%, but they have much lower levels of income inequality. A wide distribution of skills is seemingly not harmful in itself. It is noteworthy also that a wide distribution is positively related to national income, as measured by GDP per capita with a .59 correlation.
So, two slightly different patterns emerge: on the one hand, countries such as Spain, Italy, Ireland and Poland have comparatively low mean scores, and many low-skilled and few high-skilled adults; whereas Anglo-Saxon countries, such as the United States, the United Kingdom, Canada and Australia, on the other hand, have a more average mean score, but many low- and many high-skilled adults, resulting in a large discrepancy between both ends of the distribution. In both groups of countries the skills distribution is related to high social inequality.
A completely different pattern can be seen in the Nordic countries, the Flemish Community in Belgium and the Netherlands: these countries combine low social inequality with a skills distribution profile characterised by an average width, a comparatively high mean, few low-skilled and many high-skilled adults.
At the end of the day what stands out is that a large share of low-skilled adults is associated with a high income inequality. It is not a large skills gap between the low- and high-skilled which seems to be related to high social inequality, but the size of the low-skilled population. The smartest skills strategy a country can develop to improve social inequality is to upgrade the skills of low-skilled adults.
Links:
How closely is the distribution of skills related to countries’ overall level of social inequality and economic prosperity? OECD paper by Dirk Van Damme on New Approaches to Economic Challenges
Survey of Adult Skills (PIAAC)
OECD Skills Outlook 2013: First Results from the Survey of Adult Skills
Chart source: © OECD
