The OECD regularly recommends to countries to reform their education and training systems. Economists often refer to this as improving ‘human capital’. Yet, at the macroeconomic level, quantifying the effects of human capital on growth and productivity has often proven frustratingly elusive, both in the academic literature and in OECD work.
What is human capital?
Human capital can be broadly defined as the stock of knowledge, skills and other personal characteristics embodied in people that helps them to be productive. Pursuing formal education (early childhood, formal school system, adult training programmes) but also informal and on-the-job learning and work experience all represent investment in human capital.
How do we measure human capital?
There is no comparable and consistent measure across countries reflecting all these elements available. Economists thus rely on inferior substitutes, such as years spent in the schooling system, rates of enrolment in education and literacy.
A new OECD measure of human capital builds on two components: years of schooling and rates of return to schooling. Its novelty comes from its assumptions on marginal rates of return to education. Previous studies used the same rates of return for all countries and these didn’t change in time. We apply different rates of return for countries (to be precise, for five groups of countries) and they change over time (over three time periods), in order to better reflect the recent micro-economic evidence.
The underlying data for mean years of schooling come from the Wittgenstein centre for demography and global human capital and rates of returns to additional years of education reflect recent estimates of wage premia compiled by the World Bank.
Why does it matter?
Economists assume that countries with more educated population should have higher productivity. At the microeconomic level, those with more education and experience tend to earn higher salaries. It is more difficult to identify a robust positive relationship between economic outcomes and human capital at the macroeconomic level, where such link has been missing so far.
Our analysis fills this gap. The new measure shows that more human capital leads to more productivity. These results survive a battery of robustness checks. For more details see Botev, Égert, Smidova and Turner (2019).
Numerous studies examined educational policies at the student, school and country level (for literature overview see Smidova, 2019) and main OECD country experiences are summarised by the OECD’s Directorate for Education and Skills in Education GPS).
As the new human capital measure is built on years of schooling and rates of return to education, policies influencing education matter. The empirical analysis shows that the following educational policies tend to boost human capital at the country level (Égert, Botev and Turner, 2019):
Furthermore, the analysis shows that certain educational policies are ‘good value for money’, because they have a double dividend of boosting human capital as well as reducing spending pressures. These are: increasing attendance in pre-primary education, greater university autonomy and lower barriers to funding to students in tertiary education. Increasing school autonomy at primary and secondary level enhances educational outcomes, but does not reduce spending pressures. And, higher student-to-teacher ratio, higher age of first tracking and a reduction in the extent of tracking also boost human capital, but at a higher cost.
Illustrative impact on a median country: Reform that moves the policy to the average of the top 3 OECD performers.
The full impact takes decades to show, but positive impact is visible already in medium term (5 years). The size of impact depends on each country’s scope for reform, i.e. where does it stand in terms of the policy today. To see potential reform impact in your country, go to the dataviz below.
Find out more – select a country and policy area below.
Download the data at oe.cd/spider