News and Research 236

Measuring Human Capital using Global Learning Data | Analyses of a global database published in Nature reveal that in many developing countries progress in learning remains limited despite increasing enrolment in primary and secondary education, and uncover links between human capital and economic development. Although enrolment in schools has risen globally between 2000 and 2017, progress in learning (as measured by standardized tests) has been limited. The findings are based on the analysis of a new dataset which incorporates data from 164 countries representing 98% of the world’s population. Human capital — the value of people’s experience and skills to an organization or country — is an important component of economic development. This has normally been measured using metrics of schooling as a proxy, in which being in school translates into learning, which then translates to human capital. Much of the effort to measure learning has focused on high-income countries, and there has been an absence of comparable measures of learning from developing economies. The Harmonized Learning Outcomes (HLO) database enables comparisons of learning progress across the world. The database includes the results from seven different types of tests, which each cover between 10 and 72 countries, and have been combined and made comparable. Scores were disaggregated by schooling level (primary or secondary), subject (maths, science and reading) and gender. The HLO data is a key ingredient in the World Bank Human Capital Index, combining learning and schooling through the Learning-Adjusted Years of Schooling education component of the index. The HLO closely relates to a series of additional efforts to produce global learning data such as UNESCO’s effort to construct a globally comparable proficiency scale and the Rosetta Stone project. The HLO complements the related Learning Poverty indicator focused on reading in primary school. The slow/limited learning we find builds on multiple ‘soundings of the alarm’ highlighting the urgent need for proven solutions to boost learning. From 2000 to 2017, there was an increase in schooling for pupils (average number of years spent in school) and enrolment rates, but limited progress in learning. For example, in the Middle East and North Africa, enrolment rates for primary education increased from 95% to 99% between 2000 and 2010. However, learning levels remained around a score of 380 from 2000 to 2015 (high performance was considered to be a score of 625 and low performance a score of 300). The Nature paper builds on seminal work highlighting the gap between schooling and learning by Eric Hanushek, Ludger Woessmann, Lant Pritchett, the 2018 WDR, and others. Although modelling suggests that the world is on track to achieve universal primary enrolment by 2030, this will mean little if learning continues to stagnate.

Angrist, N., Djankov, S., Goldberg, P.K. and Patrinos, H.A., Measuring Human Capital using Global Learning DataNature (2021) | Human capital—that is, resources associated with the knowledge and skills of individuals—is a critical component of economic development. Learning metrics that are comparable for countries globally are necessary to understand and track the formation of human capital. The increasing use of international achievement tests is an important step in this direction. However, such tests are administered primarily in developed countries, limiting our ability to analyze learning patterns in developing countries that may have the most to gain from the formation of human capital. Here we bridge this gap by constructing a globally comparable database of 164 countries from 2000 to 2017. The data represent 98% of the global population and developing economies comprise two-thirds of the included countries. Using this dataset, we show that global progress in learning—a priority Sustainable Development Goal—has been limited, despite increasing enrolment in primary and secondary education. Using an accounting exercise that includes a direct measure of schooling quality, we estimate that the role of human capital in explaining income differences across countries ranges from a fifth to half; this result has an intermediate position in the wide range of estimates provided in earlier papers in the literature. Moreover, we show that average estimates mask considerable heterogeneity associated with income grouping across countries and regions. This heterogeneity highlights the importance of including countries at various stages of economic development when analyzing the role of human capital in economic development. Finally, we show that our database provides a measure of human capital that is more closely associated with economic growth than current measures that are included in the Penn world tables version 9.0 and the human development index of the United Nations (https://doi.org/10.1038/s41586-021-03323-7).

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Clippings+ | Press release (Japanese) | More and more children all over the world are attending school, but what are the benefits? | Education: Progress in learning may not increase with school enrolment | Reddit

See also for more periodic updates: https://wordpress.com/page/hpatrinos.com/2168.

More on the Harmonized Learning Outcomes Dataset: Updates and Additions | When the HLO dataset was launched in 2018, it included 164 countries and territories. Since then, we updated it with 20 new countries and more recent data points for 95 countries. For the updates, 8 come from EGRAs, 8 from PILNA, 3 using PISA and PISA-D, and 1 using TIMSS-equivalent assessment. For more recent data points, 75 are from PISA 2018, 7 from PISA-D, 7 from EGRAs, and 6 from PILNA. The addition of 20 new countries take the percentage of school-age population covered by the database to 99 percent.[1] The updated database was used for the Human Capital Index Update 2020. The database was also used to produce learning loss estimates due to COVID-19. HLO data has also been used in the ECA expanded HCI measure (Measuring Human Capital in Europe and Central Asia). The data is also used in the USAID Country Roadmaps to Self Reliance measure, the World Bank/FCDO/BE2 Smart Buys note, and in Our World in Data. The associated working papers have 175 academic citations (Google Scholar). Since the 2020 Annual Meetings, the team has received more assessments. Recently, results from TIMSS 2019, PASEC 2019 and Southeast Asia Primary Learning Metrics (SEA-PLM) 2019 were released. Additionally, Multiple Indicator Cluster Surveys (MICS), an international household survey that has been implemented in over 115 countries, has included a module on foundational learning skills. This new MICS with module on foundational learning skills has been conducted in 70 countries with datasets available for 36 countries.


[1] We thank Enrique Alasino, Hiroshi Saeki, Janice Heejin Kim, Maria Jose Vargas Mancera, Michelle Belisle (SPC) Rebecca Rhodes (USAID), Ritika D’Souza, Roberta Gatti, Ryoko Tomita, Shwetlena Sabarwal, Toby Linden, Tekabe Ayalew, Timothy Johnston and Xiaoyan Liang for their support in obtaining the data.