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.

The Economics Department developed a new measure of human capital built using PISA and PIAAC surveys, and mean years of schooling.

The new measure is a cohort-weighted average of past PISA scores (representing the quality of education) of the working age population and the corresponding mean years of schooling (representing the quantity of education). In contrast to the existing literature, the relative weights of each component are not imposed or calibrated but directly estimated. The study finds that the elasticity of the stock of human capital with respect to the quality of education is three to four times larger than for the quantity of education.

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 new measure has a strong link with productivity with the potential for productivity gains being much greater from improvements in the quality than quantity component of human capital. The magnitude of these potential gains in multi-factor productivity is comparable to a similarly standardised improvement in product market regulation, but the effects materialise with much longer lags.

For more details see: “A new macroeconomic measure of human capital exploiting PISA and PIAAC: Linking education policies to productivity” by Égert, de La Maisonneuve and Turner (2022) 

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):

• First, more children attending pre-primary education improve human capital, especially in countries with above-average share of disadvantaged children. This result based on macroeconomic data is in line with the microeconomic literature.
• Another finding is that teaching resources matter. Fewer students per teacher boost human capital, which can be thought of as a crude measure of the teaching quality. We also found some evidence showing that higher share of qualified teachers is good for human capital.
• Third, streaming children at a later age into different education tracks such as vocational and grammar schools based on their ability or achievement has a positive impact.
• Schools having more autonomy and leeway on how to manage their resources is good for human capital. This positive effect is greater in countries with external central exams that captures external accountability imposed on schools.
• Finally, countries, in which universities have more autonomy in how they can allocate their resources, have higher human capital and the ease of access to individual financing of university education helps to raise a country’s human capital. It should be noted, however, that these results are less robust.

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.

 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. 

Non-technical reading

• A new aggregate measure of human capital: Linking education policies to productivity through PISA and PIAAC scores | CEPR

Papers providing technical details

• Égert, B., C.de La Maisonneuve and D. Turner (2022), “A new macroeconomic measure of human capital exploiting PISA and PIAAC: Linking education policies to productivity”

• de La Maisonneuve, B. Égert and D. Turner (2022), “Quantifying the macroeconomic impact of COVID-19-related school closures through the human capital channel”
• World Bank’s Human Capital Project
• Wittgenstein Centre for demography and global human capital
• OECD PISA Database
• PIAAC Database