The OECD recently published the international comparison of the gap in employment rates between university graduates and workers with secondary education or less (link). There is no single exception to the fact that the employment rate is the highest in the group of individuals with college and university degree. Nonetheless, the comparison of the variation in employment rate in the cross section of OECD countries is very interesting.

Among the OECD countries (link), Iceland enjoys the highest employment rate (94.7 percent) of those with college or university degree followed by Switzerland (93.9 percent), Norway (92 percent) and Denmark (91.4 percent). The lowest employment rate for university graduates in 2008 was in Turkey (81.4 percent), Italy (86.5 percent), Israel (86.6 percent) and Greece (87.2 percent). In contrast, the employment rate for those below the secondary education is the lowest in Slovakia (39 percent), Hungary (47.5 percent), Poland (55 percent) and Czech Republic (57.4 percent).

The persistence of high unemployment rate for those below the secondary education degree is a broad outline of the findings from the course of labor economics. The human capital, defined as the stock of years of education per capita, is highly positively correlated with career earnings. The evolution of human capital across the countries has been a subject of debate on economic growth. The empirical study by Robert Barro and Jong-Wha Lee (link) has shown that, for instance, upper secondary school attendence by males has a significant long-term impact on the economic growth. The level of education, sustained by the years of schooling, is not a sole determinant of economic growth in the international perspective. Although, the economic growth is strongly positively correlated with the average years of schooling, the relationship is less powerful considering different parameters of the educational attainment. In the Barro-Lee dataset (link), there is a significant variation between the share of female population that enrolled in a tertiary education and the share of female that completed the tertiary degree. The difference is significant not only in the cross section but also in the country-based time series.

By far the highest tertiary degree completion rate for females has been present in Australia, Canada, Ireland, New Zealand and the United States. Among other countries, the completion rate of Iceland and the Netherlands has been significantly higher compared to the countries of the Continental and Mediterranean Europe. The rate of return to an additional year of schooling significantly differed across countries and across the level of education. For instance, Barro and Lee estimated that the rate of return is the highest at the tertiary level (17.9 percent per annum) compared to the secondary level (10 percent) while the rate of return from an additional year of schooling at the primary level is statistically insignificant from zero. The picture shows the regional variation in the average rate of return from an additional year of schooling.

The creation of human capital is essential to higher economic growth. Ultimately, the investment in human capital is the essential means of higher standard of living in poor countries. An interesting theoretical question is what could account for a divergence across the countries? Considering the relevant economic theory as well as scholarly contributions to the theory and empirics of economic growth, there are several factors that explain the significance of divergence in the rate of return from an additional year of education.

First, the impact of behavioral patterns on education and labor market decisions explains a pretty large part of the difference between the effect of education and labor market structure on the rate of return from schooling. Although the field of behavioral economics (link) is still a largely evolving discipline within the economics, the existing empirical studies of the effects of institutional variables on education outcome try to capture these effects by different proxies such as the estimates of political freedom, the rule of law and civil liberties. The changes in the return to education may be related to these factors since the relative worth of education in regions such as Sub-Saharan Africa and Latin America may incur high opportunity cost given the payoff from predatory behavior or working in the informal sector of the economy.

Second, general and firm-specific human capital investment, the increase in college premium and the enormous increase in female labor force participation help explain high rate of return from an additional year of schooling in advanced countries and East Asia. In particular, East Asian tigers were able to sustain high economic growth rates partly because of well-trained and educated labor force able to use the modern technologies. The resulting outcome of the Asian economic miracles has been a steady growth in output per worker and a gradual convergence of wage rates in South Korea and Japan to the level of U.S. According to Kevin Murphy and Finis Welch (link), the premium of getting a college education in the U.S in 1980s was 67 percent. The growth in college and university attendence rates is largely explained by the robust increase in tertiary education premium.

And third, greater labor force participation of women has also led to higher rates of college and university attendence. In spite the persistent male-female pay gap, women have experienced a tremendous increase in lifetime earnings as a consequence of higher rates of college and university attendence. The persistence of the male-female pay gap can be explained by the rewards to education rather than by inherent gender bias. The U.S. Census published the relevant data (link) on the distribution of female earnings. In 2003, the female earnings of high school graduates in the 25-34 age thresold represented 78 percent of average male earnings. The earnings of the same female age thresold with bachelor’s degree represented 89 percent of male earnings and 71 percent for those female with master’s degree. What accounts for the gender earnings gap across the levels of age and education is the asymmetric self-selection that led to dispersed gender distribution of relative earnings. Men usually self-select into the areas of work requiring a significant amount of risk-taking and rather uncertain payoffs while the female labor market pattern is inclined towards less risk-taking and greater certainty regarding the stability of lifetime earnings.

The data by the U.S. Bureau of Labor Statistics (link) published in 2003, showed that female-to-male earnings ratio in high-paying jobs is the lowest in the field of chief executives where female earnings represented 80 percent of average male earnings in the same field of occupation. On average, the female-to-male earnings ratio declined in low-paying occupations such as cashiers (93 percent), cooks (91 percent), food preparation (93 percent) and hand packaging (101 percent). Contrary to the popular perception, female earnings in the field of computer systems management and legal industry represented 91 percent of average male earnings while the highest ratio in high-paying occupations was recorded in pharmaceutical industry (92 percent).

Indeed, there is a persistent and historically lowest male-female earnings gap. But, as the labor economic theory of human capital predicts, the gender pay difference reflects different cognitive abilities and preferences of occupational selection considering the degree of risk-taking and payoff uncertainty. Even the international test scores (link) confirmed that advantage of female cognitive abilities comprehends in verbal reasoning and reading skills (link) while the cognitive abilities of male are more inclined towards the use of computer technology (link) and mathematics (link).

Even in a cross-country perspective, the gender wage differential persists. The gap, defined as the female-male ratio, ranges from 0.9 in France to 0.7 in Canada. The gender wage differential is a cross section of major economies is shown in the table below.

Source: F.D Blau & L.M Kahn, Gender Differences in Pay, 2000

The set of different institutional characteristics of labor market in different countries could easily complement the productivity growth rates as to explain the evolution of wage differential across countries. Even though wage rates are primarily determined by the productivity growth, the existence of collective bargaining schemes and rigid labor market mechanism determining wage rate and total compensation can add significantly to the enforcement of particular labor market policies affecting gender bias in wage determination. In the United States and other advanced countries, the main cause of the wider gender earnings gap is a significant gap between college education premium and high school premium. In addition, reductions in personal income tax rates furthermore increase the rewards to college education relative to the education levels of high school or less – which, by the empirical evidence, seems to be the main determinant of earnings gap in the labor market of advanced countries.