Measuring Human Capital Using Global Learning Data
URL: https://doi.org/10.1038/s41586-021-03323-7
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 analyse 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 analysing 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.
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Metadata last updated | July 7, 2023 |
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